Dr Rokny (PhD, UNSW Sydney, 2018) is the Director of UNSW BioMedical Machine Learning Laboratory (BML), where he leads a team of 25 researchers developing trustworthy artificial intelligence for biology and medicine, spanning medical artificial intelligence, large language models, and bio-machine learning. He supervises a dynamic team of researchers and have successfully led over 60 projects, resulting in 100 high-quality publications in top-tier journals such as Nature Communications, Nature Neuroscience, The Lancet, Cell reports, PLOS Computational Biology, Blood, and A* conferences such as ICLR, NeurIPS, AAAI, and ACL, often as the first or senior author. The impact of my work is evident through a high citation rate [5,250+, h-index 40 Google Scholar] and a high FWCI score (AI= 7.6; Neuroscience= 4.7; Health Informatics= 4.75), which is outstanding considering the career stage. The impact of his leadership is also evidenced by securing significant grants, including a DECRA fellowship, UNSW Scientia fellowship, an NHMRC Ideas grant, and a CSIRO NGGP grant, as well as multiple awards such as Google fellowship, Tour de Cure and MSA fellowships for students under his leadership. Additionally, he actively enhance medical AI and machine learning literacy by collaborating with clinicians and health professionals across Sydney hospitals, including the Gene2Care and PreGen consortia, and NSW Health clinics, demonstrating the practical applications of AI to improve health outcomes. As the Health Theme Leader of the UNSW Data Science Hub, He sets health data science priorities, integrating research with practical health solutions. His organisational skills have led me to orchestrate over 100 seminars on AI in medicine, promoting knowledge sharing and collaboration. Furthermore, He contributes to research direction through roles on panels like NSF-CSIRO influencing funding towards innovative AI and genomics project and HUGO meeting. His commitment to training the next generation is showcased through his leadership in CSIRO’s NGGP, collaborating with industry partners like 23Strands to enhance the capabilities of emerging AI researchers in medical technologies. Notably, He is currently leading several national-level initiatives focused on developing foundation models in AI for Biology and Medicine (ClinAI, OmniST, ARGOS, and Molecular AI). These initiatives represent a significant step forward at the national level and aim to position Australia at the forefront of these emerging GPT-like technologies for individualised medicine.
Biomedical Informatics (BIOM9540)
Biomedical Engineering (BIOM4951, BIOM4952, BIOM4953)
Preprints
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Chen D; Liu Z; Fang F; Leong CT; Ni S; Argha A; Alinejad-Rokny H; Yang M; Li C, 2026, Expanding before Inferring: Enhancing Factuality in Large Language Models through Premature Layers Interpolation, http://dx.doi.org/10.48550/arxiv.2506.02973
2026
Yang Z; Xu A; Li J; Yan L; Zhou J; Qin Z; Chang H; Chen Y; Chen L; Argha A; Alinejad-Rokny H; Tan M; Cai Y; Yang M, 2026, Structuring Reasoning for Complex Rules Beyond Flat Representations, http://dx.doi.org/10.48550/arxiv.2510.05134
2026
Karami M; Khadijeh ; Jahanian ; Alizadehsani R; Dehzangi I; Gorriz JM; Zhang Y; Wang J; Hajati F; Yang M; Porntaveetus T; Alinejad-Rokny H, 2026, Revolutionizing Genomics with Reinforcement Learning Techniques, http://dx.doi.org/10.48550/arxiv.2302.13268
2026
Chen G; Sun C; Fu C; Wang Q; Huang Z; Wei C; Chen G; Fang F; Argha A; Zhao B; Xu X; Han Q; Alinejad-Rokny H; Qu Q; Li B; Ni S; Yang M; Wei H; Li Y, 2026, Beyond Quantity: Trajectory Diversity Scaling for Code Agents
2026
Ghamsari R; de Graaf C; Thijssen R; You Y; Lovell N; Alinejad-Rokny H; Ritchie M, 2025, Comparative Analysis of Single-Nucleus and Single-Cell RNA Sequencing in Human Bone Marrow Mononuclear Cells: Methodological Insights and Trade-offs, http://dx.doi.org/10.1101/2025.09.08.675012
2025
Zahedi R; Argha A; Farbehi N; Bakhshayeshi I; Ye Y; Lovell NH; Alinejad-Rokny H, 2025, SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics, http://dx.doi.org/10.48550/arxiv.2506.11491
2025
Lee S; Ni S; Wei C; Li S; Fan L; Argha A; Alinejad-Rokny H; Xu R; Gong Y; Yang M, 2025, xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM Jailbreaking, http://dx.doi.org/10.48550/arxiv.2501.16727
2025
Chen D; Fang F; Ni S; Liang F; Hu X; Argha A; Alinejad-Rokny H; Yang M; Li C, 2025, Lower Layers Matter: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused, http://dx.doi.org/10.48550/arxiv.2408.08769
2025
Asgharnezhad H; Shamsi A; Alizadehsani R; Mohammadi A; Alinejad-Rokny H, 2025, Enhancing Monte Carlo Dropout Performance for Uncertainty Quantification, http://dx.doi.org/10.48550/arxiv.2505.15671
2025
Luo R; Lin T-E; Zhang H; Wu Y; Liu X; Yang M; Li Y; Chen L; Li J; Zhang L; Xia X; Alinejad-Rokny H; Huang F, 2025, OpenOmni: Advancing Open-Source Omnimodal Large Language Models with Progressive Multimodal Alignment and Real-Time Self-Aware Emotional Speech Synthesis, http://dx.doi.org/10.48550/arxiv.2501.04561
2025
Ni S; Li S; Wang S; Bi X; Li Y; Gan C; Jin J; Lu Y; Argha A; Alinejad-Rokny H; Si T; Yang M; Wang T, 2025, Decoding Prokaryotic Whole Genomes with a Product-Contextualized Large Language Model, http://dx.doi.org/10.64898/2025.12.03.692003
2025
Sadeghi A; Hajati F; Argha A; Lovell NH; Yang M; Alinejad-Rokny H, 2025, Interpretable graph-based models on multimodal biomedical data
integration: A technical review and benchmarking, http://arxiv.org/abs/2505.01696v1
2025
Doan BG; Shamsi A; Guo X-Y; Mohammadi A; Alinejad-Rokny H; Sejdinovic D; Teney D; Ranasinghe DC; Abbasnejad E, 2025, Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks, http://dx.doi.org/10.48550/arxiv.2407.20891
2025
Zhao J; Xu L; Tan M; Zhang L; Argha A; Alinejad-Rokny H; Yang M, 2025, RxSafeBench: Identifying Medication Safety Issues of Large Language Models in Simulated Consultation, http://dx.doi.org/10.48550/arxiv.2511.04328
2025
Gao Y; Luo Y; Li W; Lan Y; Jiang H; Chen Y; Yi X; Li B; Alinejad-Rokny H; Wang T; Fu L; Yang M; Si T, 2025, Autonomous Liquid-handling Robotics Scripting for Accessible and Responsible Protein Engineering, http://dx.doi.org/10.1101/2025.09.30.679666
2025
Li J; Chen Y; Liu Z; Tan M; Zhang L; Li Y; Luo R; Chen L; Luo J; Argha A; Alinejad-Rokny H; Zhou W; Yang M, 2025, STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation, http://dx.doi.org/10.48550/arxiv.2506.02347
2025
Luo J; Chen L; Luo R; Zhu L; Ao C; Li J; Chen Y; Cheng X; Yang W; Su J; Argha A; Alinejad-Rokny H; Li C; Ni S; Yang M, 2025, PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation, http://dx.doi.org/10.48550/arxiv.2410.01504
2025
Wang Q; Chen G; Wang H; Liu H; Zhu M; Qin Z; Li L; Yue Y; Wang S; Li J; Wu Y; Liu Z; Chen L; Luo R; Fan L; Li J; Zhang L; Xu K; Li C; Alinejad-Rokny H; Ni S; Lin Y; Yang M, 2025, IPBench: Benchmarking the Knowledge of Large Language Models in Intellectual Property, http://dx.doi.org/10.48550/arxiv.2504.15524
2025
Shamsi A; Becirovic R; Argha A; Abbasnejad E; Alinejad-Rokny H; Mohammadi A, 2024, ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance, http://dx.doi.org/10.48550/arxiv.2409.09251
2024
Wang F; Lin J; Alinejad-Rokny H; Ma W; Meng L; Huang L; Yu J; Chen N; Wang Y; Yao Z; Xie W; Li X; Wong K-C, 2024, Unveiling multi-scale architectural features in single-cell Hi-C data using scCAFE, http://dx.doi.org/10.1101/2024.09.10.611762
2024
Truong P; Shen S; Joshi S; Islam MI; Zhong L; Raftery M; Afrasiabi A; Alinejad-Rokny H; Nguyen M; Zou X; Bhuyan GS; Sarowar C; Ghodousi E; Stonehouse O; Mohamed S; Toscan C; Connerty P; Kakadia P; Bohlander S; Michie K; Larsson J; Lock R; Walkley C; Thoms J; Jolly C; Pimanda J, 2024, Genome-Wide CRISPR-Cas9 Screening Identifies a Synergy between Hypomethylating Agents and SUMOylation Blockade in MDS/AML, http://dx.doi.org/10.1101/2024.04.17.589858
2024
Ni S; Wu H; Yang D; Qu Q; Alinejad-Rokny H; Yang M, 2024, Small Language Model as Data Prospector for Large Language Model, http://dx.doi.org/10.48550/arxiv.2412.09990
2024
Rahmani AM; Haider A; Adeli M; Mzoughi O; Gemeay E; Mohammadi M; Alinejad-Rokny H; Khoshvaght P; Hosseinzadeh M, 2024, Enhanced Heart Sound Classification Using Mel Frequency Cepstral Coefficients and Comparative Analysis of Single vs. Ensemble Classifier Strategies, http://dx.doi.org/10.48550/arxiv.2406.00702
2024
Wang Q; Ni S; Liu H; Lu S; Chen G; Feng X; Wei C; Qu Q; Alinejad-Rokny H; Lin Y; Yang M, 2024, AutoPatent: A Multi-Agent Framework for Automatic Patent Generation, http://dx.doi.org/10.48550/arxiv.2412.09796
2024
Zhu J; Tan M; Yang M; Li R; Alinejad-Rokny H, 2024, CollectiveSFT: Scaling Large Language Models for Chinese Medical Benchmark with Collective Instructions in Healthcare, http://dx.doi.org/10.48550/arxiv.2407.19705
2024
Liang Y; Abedini S; Farbehi N; Alinejad-Rokny H, 2024, How chromatin interactions shed light on interpreting non-coding genomic variants: opportunities and future direc-tions, http://dx.doi.org/10.48550/arxiv.2411.17956
2024
Hansun S; Argha A; Bakhshayeshi I; Wicaksana A; Alinejad-Rokny H; Fox GJ; Liaw S-T; Celler BG; Marks GB, 2024, Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review (Preprint), http://dx.doi.org/10.2196/preprints.69068
2024
Javed S; Khan TM; Qayyum A; Alinejad-Rokny H; Sowmya A; Razzak I, 2024, Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images, http://dx.doi.org/10.48550/arxiv.2405.17520
2024
Rahmani AM; Khoshvaght P; Alinejad-Rokny H; Sadeghi S; Asghari P; Arabi Z; Hosseinzadeh M, 2024, A Diagnostic Model for Acute Lymphoblastic Leukemia Using Metaheuristics and Deep Learning Methods, http://dx.doi.org/10.48550/arxiv.2406.18568
2024
Jafari M; Shoeibi A; Ghassemi N; Heras J; Ling SH; Beheshti A; Zhang Y-D; Wang S-H; Alizadehsani R; Gorriz JM; Acharya UR; Rokny HA, 2023, Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence, http://dx.doi.org/10.48550/arxiv.2210.14611
2023
Roshanzamir M; Shamsi A; Asgharnezhad H; Alizadehsani R; Hussain S; Moosaei H; Mohammadi A; Acharya UR; Alinejad H, 2023, Quantifying Uncertainty in Automated Detection of Alzheimer’s Patients Using Deep Neural Network, http://dx.doi.org/10.20944/preprints202301.0148.v1
2023
Jafari M; Sadeghi D; Shoeibi A; Alinejad-Rokny H; Beheshti A; García DL; Chen Z; Acharya UR; Gorriz JM, 2023, Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023, http://dx.doi.org/10.48550/arxiv.2309.12202
2023
Subramanian S; Subramanian S; Thoms JAI; Huang Y; Cornejo P; Koch F; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll P; Fajardo DC; Beck D; Curtis D; Yehson K; Antonenas V; Brien TO; Trickett A; Powell J; Lewis I; Pitson S; Gandhi M; Lane S; Vafaee F; Wong E; Göttgens B; Rokny HA; Wong JWH; Pimanda J, 2023, Cell Type-Specific Regulation by a Heptad of Transcription Factors in Human Hematopoietic Stem and Progenitor Cells, http://dx.doi.org/10.1101/2023.04.18.537282
2023
Abedini SS; Akhavan S; Heng J; Alizadehsani R; Dehzangi I; Bauer DC; Rokny H, 2023, A Critical Review of the Impact of Candidate Copy Number Variants on Autism Spectrum Disorders, http://dx.doi.org/10.48550/arxiv.2302.03211
2023
Rahaie Z; Rabiee HR; Alinejad-Rokny H, 2022, DeepGenePrior: A deep learning model to prioritize genes affected by copy number variants, http://dx.doi.org/10.1101/2022.08.22.504862
2022
Rahman MM; Kamal Nasir M; A-Alam N; Islam Khan S; Band S; Dehzangi I; Beheshti A; Alinejad Rokny H, 2022, Hybrid Feature Fusion and Machine Learning Approaches for Melanoma Skin Cancer Detection, http://dx.doi.org/10.20944/preprints202201.0258.v1
2022
Jafari M; Shoeibi A; Khodatars M; Ghassemi N; Moridian P; Delfan N; Alizadehsani R; Khosravi A; Ling SH; Zhang Y-D; Wang S-H; Gorriz JM; Rokny HA; Acharya UR, 2022, Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Review, http://dx.doi.org/10.48550/arxiv.2210.14909
2022
Sharifonnasabi F; Jhanjhi N; John J; Obeidy P; Shamshirband S; Alinejad Rokny H, 2022, Hybrid HCNN-KNN Transfer Learning Model Enhances Age Estimation Accuracy in Orthopantomography, http://dx.doi.org/10.20944/preprints202108.0413.v2
2022
Nasab RZ; Ghamsari MRE; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2022, Deep Learning in Spatially Resolved Transcriptomics: A Comprehensive
Technical View, http://arxiv.org/abs/2210.04453v3
2022
Montazerin M; Rahimian E; Naderkhani F; Atashzar SF; Alinejad-Rokny H; Mohammadi A, 2022, HYDRA-HGR: A Hybrid Transformer-based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information, http://dx.doi.org/10.48550/arxiv.2211.02619
2022
Kazemi A; Hamidieh K; Dashti H; Ghareyazi A; Tahaei MS; Rabiee HR; Alinejad-Rokny H; Dehzangi I, 2022, Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types, http://dx.doi.org/10.21203/rs.3.rs-1567157/v1
2022
Band S; Ardabili S; Yarahmadi A; Pahlevanzadeh B; Kausar Kiani A; Beheshti A; Alinejad Rokny H; Dehzangi I; Mosavi A, 2022, Machine Learning and Internet of Medical Things for Handling COVID-19: Meta-Analysis, http://dx.doi.org/10.20944/preprints202202.0083.v1
2022
Band S; Ardabili S; Yarahmadi A; Pahlevanzadeh B; Kausar Kiani A; Beheshti A; Alinejad Rokny H; Dehzangi I; Chang A; Mosavi A; Moslehpour M, 2022, A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis, http://dx.doi.org/10.20944/preprints202202.0083.v2
2022
Sharifonnasabi F; Jhanjhi N; John J; Obeidy P; Shamshirband S; Alinejad Rokny H; Baz M, 2022, Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography, http://dx.doi.org/10.20944/preprints202108.0413.v3
2022
Parhami P; Fateh M; Rezvani M; Rokny HA, 2022, A benchmarking of deep neural network models for cancer subtyping using single point mutations, http://dx.doi.org/10.1101/2022.07.24.501264
2022
Rezaie N; Bayati M; Tahaei MS; Hamidi M; Khorasani S; Lovell N; Breen J; Rabiee H; Rokny HA, 2021, Somatic point mutations are enriched in long non-coding RNAs with possible regulatory function in breast cancer, http://dx.doi.org/10.21203/rs.3.rs-827525/v1
2021
Kazemi A; Ghareyazi A; Hamidieh K; Dashti H; Tahaei M; Rabiee H; Alinejad Rokny H; Dehzangi A, 2021, Pan-Cancer Integrative Analysis of Whole-Genome <em>De novo</em> Somatic Point Mutations Reveals 17 Cancer Types, http://dx.doi.org/10.20944/preprints202111.0266.v1
2021
Islam Khan MS; Rahman A; Karim MR; Bithi NI; Band SS; Dehzangi A; Alinejad-Rokny H, 2021, CovidMulti-Net: A Parallel-Dilated Multi Scale Feature Fusion Architecture for the Identification of COVID-19 Cases from Chest X-ray Images, http://dx.doi.org/10.1101/2021.05.19.21257430
2021
Hamidi H; Alinejad-Rokny H; Coorens T; Sanghvi R; Lindsay SJ; Rahbari R; Ebrahimi D, 2021, Signatures of Mutational Processes in Human DNA Evolution, http://dx.doi.org/10.1101/2021.01.09.426041
2021
Debnath T; Reza MM; Rahman A; Band S; Alinejad Rokny H, 2021, Four-Layer ConvNet to Facial Emotion Recognition with Minimal Epochs and the Significance of Data Diversity, http://dx.doi.org/10.20944/preprints202105.0424.v1
2021
Rezaie N; Bayati M; Tahaei MS; Hamidi M; Khorasani S; Lovell N; Breen J; Rabiee H; Alinejad-Rokny H, 2021, Somatic point mutations are enriched in long non-coding RNAs with possible regulatory function in breast cancer, http://dx.doi.org/10.1101/2021.07.19.453012
2021
Asgari Y; Heng JIT; Lovell N; Forrest A; Alinejad-Rokny H, 2020, Evidence for enhancer noncoding RNAs (enhancer-ncRNAs) with gene regulatory functions relevant to neurodevelopmental disorders, http://dx.doi.org/10.1101/2020.05.16.087395
2020
Dashti H; Dehzangi A; Bayati M; Breen J; Lovell N; Ebrahimi D; Rabiee H; Alinejad-Rokny H, 2020, Integrative analysis of mutated genes and mutational processes reveals seven colorectal cancer subtypes, http://dx.doi.org/10.1101/2020.05.18.101022
2020
Afrasiabi A; Alinejad-Rokny H; Lovell N; Xu Z; Ebrahimi D, 2020, Insight into the origin of 5’UTR and source of CpG reduction in SARS-CoV-2 genome, http://dx.doi.org/10.1101/2020.10.23.351353
2020
Alinejad-Rokny H; Modegh RG; Rabiee HR; Rezaie N; Tam KT; Forrest ARR, 2020, MaxHiC: robust estimation of chromatin interaction frequency in Hi-C and capture Hi-C experiments, http://dx.doi.org/10.1101/2020.04.23.056226
2020
Sharifrazi D; Alizadehsani R; Hassannataj Joloudari J; Shamshirband S; Hussain S; Alizadeh Sani Z; Hasanzadeh F; Shoaibi A; Dehzangi A; Alinejad-Rokny H, 2020, CNN-KCL: Automatic Myocarditis Diagnosis using Convolutional Neural Network Combined with K-means Clustering, http://dx.doi.org/10.20944/preprints202007.0650.v1
2020
Liu N; Low WY; Alinejad-Rokny H; Pederson S; Sadlon T; Barry S; Breen J, 2020, Seeing the forest through the trees: Identifying functional interactions from Hi-C, http://dx.doi.org/10.1101/2020.11.29.402420
2020
Alinejad-Rokny H; Heng JIT; Forrest ARR, 2019, Brain-enriched coding and long non-coding RNA genes are overrepresented in recurrent autism spectrum disorder CNVs, http://dx.doi.org/10.1101/539817
2019
Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest A; Alinejad-Rokny H, 2018, CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes, http://dx.doi.org/10.1101/424960
2018
Alinejad-Rokny H; Zarepour E; Khadijeh Jahanian H; Beheshti A; Dehzangi A, A Multivariate Data Analytics Approach Revealed No Footprint of APOBEC3 Proteins in Hepatitis B Virus Genome, http://dx.doi.org/10.2139/ssrn.3514647
Journal articles
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Li W; Zhang D; Peng E; Shen S; Alinejad-Rokny H; Liu Y; Zheng J; Jiang C; Ye Y, 2026, 'HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning', Advanced Science, http://dx.doi.org/10.1002/advs.202514351
2026
Argha A; Alinejad-Rokny H; Hajati F; Magdy J; Li J; Lim ZZ; Yu J; Yang M; Butcher K; Ooi SY; Lovell NH, 2026, 'ECG-Adapt: A Novel Framework for Robust Electrocardiogram Classification Across Diverse Populations and Recording Conditions', IEEE Transactions on Biomedical Engineering, pp. 1 - 12, http://dx.doi.org/10.1109/TBME.2026.3653051
2026
Intarak N; Ghasemnejad T; Fakhruddin KS; Kamal A; Prommanee S; Jahanian KH; Lovell NH; Alinejad-Rokny H; Porntaveetus T, 2026, 'LRP6 β-Propeller Destabilization: Novel Variant, Phenotype and Diagnostic Implications in Tooth Agenesis', International Dental Journal, 76, http://dx.doi.org/10.1016/j.identj.2025.109367
2026
Flor LS; Spencer CN; Cagney J; Gil GF; Aalruz H; Abd ElHafeez S; Abdelwahab SI; Abdoun M; Abebe M; Abebe Y; Abedi A; Abeldaño Zuñiga RA; Abie A; Abiodun O; Aboagye RG; Abreu LG; Abu Farha RK; Abubakar B; Abuhammad S; Achore M; Adams LC; Adebiyi BO; Adedokun KA; Adegbile OE; Adegoke NA; Adeleke OT; Adeniyi MA; Adesina MA; Adewuyi HO; Adnani QES; Adzigbli LA; Afolabi AA; Afolabi RF; Afzal MS; Afzal S; Agyemang-Duah W; Ahinkorah BO; Ahmad A; Ahmad D; Ahmad MM; Ahmed A; Ahmed A; Ahmed H; Ahmed MS; Ahmed O; Akin-Odanye EO; Akosile W; Akpabio IU; Alam Z; Al-Amer RM; Alansari AN; Alanzi TM; Aleidi SM; Alemu MB; Alhalaiqa FN; Al-Iede M; Alinejad Rokny H; Almagharbeh WT; Al-Mamun M; Almazan JU; Alnaeem MM; Alrimawi I; Alshahrani NZ; Alyahya MSI; Amin TT; Amini S; Amiri S; Amu H; Amzat J; Anderson DB; Anuoluwa BS; Anvari S; Anyasodor AE; Aravkin AY; Arias de la Torre J; Armocida B; Arrieta A; Arumuganainar D; Ashraf T; Aslam B; Asri Y; Athari SS; Atorkey P; Atre SR; Atsbaha AH; Atta JA; Atteraya MS; Azzam AY; Sheeba B; Baghlaf KK; Baig AA; Balcha WF; Balmori-de-la-Miyar J; Bandyopadhyay S; Barik M; Barker-Collo SL; Bashar MA; Bashir S; Bashiri A; Bastan MM, 2026, 'Disease burden attributable to intimate partner violence against females and sexual violence against children in 204 countries and territories, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023', Lancet, 407, pp. 31 - 52, http://dx.doi.org/10.1016/S0140-6736(25)02503-6
2026
Guo ZZ; Wu R; Li W; Yang K; Ying X; Alinejad-Rokny H; Ye Y, 2026, 'Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases', Science Bulletin, http://dx.doi.org/10.1016/j.scib.2026.01.034
2026
Bakhshayeshi I; Hosseini MM; Argha A; Zahedi R; Lovell NH; Alinejad-Rokny H, 2026, 'CLinNET: An Interpretable and Uncertainty-Aware Deep Learning Framework for Multi-Modal Clinical Genomics', Advanced Science, http://dx.doi.org/10.1002/advs.202512842
2026
Foroutannia A; Shoeibi A; Beheshti A; Alinejad-Rokny H; Ling SH; Lam HK, 2026, 'Advancing autonomous driving systems: A 3-dimensional U-Net framework for object detection via fusion of camera and LiDAR sensors', Information Sciences, 741, http://dx.doi.org/10.1016/j.ins.2026.123215
2026
Ghasemnejad T; Liang Y; Jahanian KH; Eidi M; Salmaninejad A; Abedini SS; Horta F; Lovell NH; Porntaveetus T; Grosser M; Aarabi M; Alinejad-Rokny H, 2026, 'Comprehensive evaluation of ACMG/AMP-based variant classification tools', Bioinformatics, 42, http://dx.doi.org/10.1093/bioinformatics/btaf623
2026
Shamsi A; Becirovic R; Alinejad-Rokny H; Mohammadi A; Argha A, 2025, 'Gradient surgery: A necessity for robust test-time adaptation for detecting casting defects', Engineering Applications of Artificial Intelligence, 161, http://dx.doi.org/10.1016/j.engappai.2025.112039
2025
Hosseinzadeh M; Tanveer J; Rahmani AM; Alanazi A; Zaidi MM; Aurangzeb K; Alinejad-Rokny H; Porntaveetus T; Lee SW, 2025, 'A comprehensive survey of golden jacal optimization and its applications', Computer Science Review, 56, http://dx.doi.org/10.1016/j.cosrev.2025.100733
2025
Lee SW; Tanveer J; Rahmani AM; Alinejad-Rokny H; Khoshvaght P; Zare G; Malekpour Alamdari P; Hosseinzadeh M, 2025, 'SFGCN: Synergetic fusion-based graph convolutional networks approach for link prediction in social networks', Information Fusion, 114, http://dx.doi.org/10.1016/j.inffus.2024.102684
2025
Wang F; Lin J; Alinejad-Rokny H; Ma W; Meng L; Huang L; Yu J; Chen N; Wang Y; Yao Z; Xie W; Wong KC; Li X, 2025, 'Unveiling Multi-Scale Architectural Features in Single-Cell Hi-C Data Using scCAFE', Advanced Science, 12, http://dx.doi.org/10.1002/advs.202416432
2025
Hansun S; Argha A; Bakhshayeshi I; Wicaksana A; Alinejad-Rokny H; Fox GJ; Liaw ST; Celler BG; Marks GB, 2025, 'Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review', Journal of Medical Internet Research, 27, http://dx.doi.org/10.2196/69068
2025
Ahmadi-Dastgerdi N; Hosseini-Nejad H; Alinejad-Rokny H, 2025, 'A hardware-efficient on-implant spike compression processor based on VQ-DAE for brain-implantable microsystems', Medical and Biological Engineering and Computing, 63, pp. 2047 - 2056, http://dx.doi.org/10.1007/s11517-025-03317-x
2025
Yu Z; Chen R; Gui P; Wang W; Razzak I; Alinejad-Rokny H; Zeng X; Shang X; Zhang L; Yang X; Yu H; Huang W; Lu H; van Wijngaarden P; He M; Zhu Z; Ge Z, 2025, 'A cross population study of retinal aging biomarkers with longitudinal pre-training and label distribution learning', Npj Digital Medicine, 8, http://dx.doi.org/10.1038/s41746-025-01751-7
2025
Du Y; Zhao Y; Li J; Wang J; You S; Zhang Y; Zhang L; Yang J; Alinejad-Rokny H; Cheng S; Shao C; Zou D; Ye Y, 2025, 'PLXDC1+ Tumor-Associated Pancreatic Stellate Cells Promote Desmoplastic and Immunosuppressive Niche in Pancreatic Ductal Adenocarcinoma', Advanced Science, 12, http://dx.doi.org/10.1002/advs.202415756
2025
Zobeiri A; Rezaee A; Hajati F; Argha A; Alinejad-Rokny H, 2025, 'Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis', International Journal of Medical Informatics, 193, http://dx.doi.org/10.1016/j.ijmedinf.2024.105659
2025
Argha A; Alinejad-Rokny H; Baumgartner M; Schreier G; Celler BG; Redmond SJ; Butcher K; Ooi SY; Lovell NH, 2025, 'A Novel Deep Ensemble Method for Selective Classification of Electrocardiograms', IEEE Transactions on Biomedical Engineering, 72, pp. 833 - 842, http://dx.doi.org/10.1109/TBME.2024.3476088
2025
Hansun S; Argha A; Alinejad-Rokny H; Alizadehsani R; Gorriz JM; Liaw ST; Celler BG; Marks GB, 2025, 'A New Ensemble Transfer Learning Approach with Rejection Mechanism for Tuberculosis Disease Detection', IEEE Transactions on Radiation and Plasma Medical Sciences, 9, pp. 433 - 446, http://dx.doi.org/10.1109/TRPMS.2024.3474708
2025
Sirota SB; Bender RG; Dominguez RMV; Movo A; Swetschinski LR; Araki DT; Han C; Wool EE; He J; Carter A; AJ Jabbar A; Aalipour MA; Aalruz H; Abbasi Dolatabadi Z; Abbastabar H; Abd ElHafeez S; Abdalla AN; Abdalla MA; Abdullah ; Abdallah EM; Abdel Razeq NMI; Abdelkader A; Abd-Elsalam S; Abdelwahab SI; Abdoun M; Abdous A; Abdrabou MM; Abdul Aziz JM; Abdulah DM; Abdullahi A; Abdul-Rahman T; Abdykerimova K; Abebe Getahun H; Abedi A; Abejew AA; Abidi SH; Abil OZ; Abiodun O; Aboagye RG; Abolhassani H; Abonie US; Aborode AT; Abourashed NM; Abtahi D; Abu Z; Abu Farha RK; Abuadas FHA; Abubakar AK; Abubakar U; Abu-Elala N; Abu-Gharbieh E; Abuhelwa AY; Abukhadijah HJ; Abushanab D; Acharya AB; Acharya KP; Acharya S; Achore M; Adal O; Adams LC; Addo IY; Adebisi TA; Adedia D; Adedokun KA; Adegoke NA; Adekanmbi V; Adeleke OT; Adesina MA; Adesola RO; Adetunji CO; Adetunji JB; Adewumi IP; Adhana MT; Adhikary RK; Adiba A; Adiga U; Adnan M; Adnani QES; Affinito G; Afzal S; Agafari GB; Aggarwal N; Agordoh PD; Agrawal A; Agyemang-Duah W; Ahadi M; Ahinkorah BO; Ahmad AA; Ahmad A; Ahmad D; Ahmad F; Ahmad I; Ahmad K; Ahmad MM; Ahmad R; Ahmad S; Ahmad T; Ahmadi A; Ahmadi M; Ahmed A; Lin J; Alinejad-Rokny H; Okeke S; Bhaskar S, 2025, 'Global burden of lower respiratory infections and aetiologies, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023', Lancet Infectious Diseases, pp. S1473-3099(25)00689-9, http://dx.doi.org/10.1016/S1473-3099(25)00689-9
2025
Pushpakumara B; Becirovic R; van Dorst J; Coffey M; Halim J; Beheshti B; Argha A; Alinejad-Rokny H; Ooi C, 2025, '16 Artificial intelligence integrating gut microbiome multi-omics to predict clinical outcomes in children with cystic fibrosis', Journal of Cystic Fibrosis, 24, pp. S9 - S9, http://dx.doi.org/10.1016/s1569-1993(25)01636-4
2025
Naghavi M; Kyu HH; Bhoomadevi A; Aalipour MA; Aalruz H; Ababneh HS; Abafita BJ; Abaraogu UO; Abbafati C; Abbasi M; Abbaspour F; Abbastabar H; Abd Al Magied AHA; Elhafeez SA; Abdalla AN; Abdalla MA; Abdallah EM; Abdeeq BA; Abdel Razeq NMI; Abdelgalil AA; Abdel-Hameed R; Abdelmasseh M; Abdelnabi M; Abdel-Rahman WM; Abdous A; Abdrabou MM; Aziz JMA; Abdulah DM; Abdullahi A; Abdul-Rahman T; Getahun HA; Abedi A; Abedi A; Abedi P; Abejew AA; Zuñiga RAA; Abid SUA; Abidi SH; Abie A; Abiodun OO; Aboagye RG; Abohashem S; Abolhassani H; Abonie US; Abourashed NM; Abouzid M; Abramov D; Abreu LG; Abtahi D; Farha RKA; Abuadas FHA; Abubakar AK; Abu-Elala N; Abu-Gharbieh E; Abuhammad S; Abuhelwa AY; Abukhadijah HJ; Abu-Rmeileh NME; Aburuz S; Abushanab D; Accrombessi MMK; Acharya AB; Acharya A; Adal O; Adams LC; Adamu AA; Addo IY; Adeagbo OA; Adebisi TA; Adedeji IA; Adedokun KA; Adegbile OE; Adegoke NA; Adeleke OT; Adema BG; Aden B; Adesina IA; Adesina MA; Adetunji JB; Adewuyi HO; Adeyeoluwa TE; Adhana MT; Adhikary RK; Adiga U; Parvar TA; Adnan M; Adnani QES; Adoma PO; Adzigbli LA; Adzrago D; Affinito G; Afifi AM; Afoakwah C; Afolabi AA; Afolabi RF; Afrăsânie VA; Afzal S; Agafari GB; Agampodi SB; Agampodi TC; Mitra S; Schutte A; Lin J; Sachdev P; Dai-Keller Z; Sundstorm J; Boufous S; Degenhardt L; Alinejad-Rokny H; Onie S; Maulik PK; Okeke S; Cullen P; Haghdoost F; Pesudovs K; Peden A; Keshri V; Akbarialiabad H; Roehr S; Perez Chacon G; Hunter J; Lennon M; Xu L; Mitchell P; Bhaskar S; Peprah P; Jha V; Saddik B; Ye P, 2025, 'Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023', Lancet, 406, pp. 1811 - 1872, http://dx.doi.org/10.1016/S0140-6736(25)01917-8
2025
Stark BA; DeCleene NK; Desai EC; Hsu JM; Johnson CO; Lara-Castor L; LeGrand KE; A PB; Aalipour MA; Aalruz H; Abafita BJ; Abaraogu UO; Abavisani M; Abbas N; Abbasi M; Abbasian M; Abbastabar H; Abd Al Magied AHA; ElHafeez SA; Abdelalim PA; Abdelfattah OM; Abdel-Hameed PR; Abdelnabi M; Wael M Abdel-Rahman P; Abdi P; Abdisa WM; Abdissa D; Abdous A; Abdullah M; Abdullahi A; Abdykerimova K; Abebe M; Abedi A; Abedi A; Abejew AA; Abhilash ES; Abiodun OO; Abiodun PO; Kasem RA; Aboagye RG; Abohashem S; Abolhassani H; Abonie US; Aborode AT; Abourashed NM; Abramov D; Abreu LG; Abtahi D; Abu Farha RK; Kende Abubakar AK; Abubakar IJ; Abu-Elala N; Abu-Gharbieh E; Abukhadijah HJ; Aburuz S; Abushanab D; Acharya AB; Acharya A; Acharya S; Achore M; Adal O; Adams LC; Adamu LH; Adão R; Addo IY; Adebayo OM; Adebisi TA; Adedia D; Adedokun KA; Adegbile OE; Adegboye OA; Adegoke NA; Adekanmbi V; Adeleke OT; Oluwaseun Adetunji C; Adeyomoye OI; Adha R; Adhikari K; Adhikary RK; Adikusuma W; Parvar TA; Adnan M; Sakilah Adnani QE; Adoma PO; Adzigbli LA; Adzrago D; Afifi AM; Afolabi HA; Afrashteh F; Afrooghe A; Afzal MS; Afzal S; Agampodi SB; Agarwal DM; Agarwal G; Agarwal P; Ageru TA; Aggarwal N; Aghajanian S; Sobrinho CA; Alinejad-Rokny H; Biswas RK; Okeke S; Haghdoost F; Burley C; Wang N; Schutte A; Sachdev P; Lin J; Si Y; Sundstorm J; Peprah P; Bhaskar S; Neal B; Feng X; Xu L; Si L; Saddik B; Ye P, 2025, 'Global, Regional, and National Burden of Cardiovascular Diseases and Risk Factors in 204 Countries and Territories, 1990-2023', Journal of the American College of Cardiology, 86, pp. 2167 - 2243, http://dx.doi.org/10.1016/j.jacc.2025.08.015
2025
Wangsanut T; Khamto N; Alinejad-Rokny H; Pongpom M, 2025, 'Regulatory functions of AcuK and AcuM transcription factors in fungal metabolic adaptation, stress response, and virulence', Frontiers in Cellular and Infection Microbiology, 15, http://dx.doi.org/10.3389/fcimb.2025.1717070
2025
Schumacher AE; Zheng P; Barber RM; Bhoomadevi A; Aalipour MA; Aalruz H; Ababneh HS; Abaraogu UO; Abbafati C; Abbas N; Abbasifard M; Abbaspour F; Abd Al Magied AHA; Elhafeez SA; Abdalla MA; Abdallah EM; Abdel Razeq NMI; Abdel-Hameed R; Abdel-Rahman WM; Abd-Elsalam S; Abdelwahab OA; Abdi P; Abdollahi A; Abdoun M; Abdous A; Abdulah DM; Abdulkader RS; Abdullahi A; Abdulraheem AS; Getahun HAA; Abedi P; Abedi A; Abejew AA; Zuñiga RAA; Abidi SH; Abie A; Abiodun O; Abiodun OO; Aboagye RG; Abohashem S; Abonie US; Abourashed NM; Abouzid M; Abramov D; Abreu LG; Abtahi D; Farha RKA; Abuadas FHA; Abubakar AK; Abubakar B; Abu-Gharbieh E; Abuhammad S; Abuhelwa AY; Abukhadijah HJ; Aburuz S; Abushanab D; Zaid AA; Acharya AB; Achore M; Acuna JM; Adair T; Adams LC; Adebayo OM; Adebisi TA; Adedia D; Adedokun KA; Adegbile OE; Adegoke NA; Adeleke OT; Adesina MA; Adesina IA; Adetokunboh OO; Adeyeoluwa TE; Adhana MT; Adhikari K; Adhikary RK; Adiga U; Parvar TA; Adnan M; Adnani QES; Adzigbli LA; Adzrago D; Affinito G; Afolabi AA; Afolabi RF; Afzal S; Agafari GB; Aggarwal N; Aghaalikhani M; Aghajanian S; Aghamir SMK; Agide FD; Agoi MD; Sobrinho CA; Agrawal A; Agyemang-Duah W; Ahinkorah BO; Ahmad R; Ahmad D; Ahmad F; Mitra S; Schutte A; Arnlov J; Lin J; Sachdev P; Sitas F; Feng X; Boufous S; Degenhardt L; Alinejad-Rokny H; Onie S; Biswas RK; Maulik PK; Okeke S; Haghdoost F; Peden A; Akbarialiabad H; Roehr S; Xu L; Vella A; Mitchell P; Bhaskar S; Peprah P; Saddik B; Ye P, 2025, 'Global age-sex-specific all-cause mortality and life expectancy estimates for 204 countries and territories and 660 subnational locations, 1950–2023: a demographic analysis for the Global Burden of Disease Study 2023', Lancet, 406, pp. 1731 - 1810, http://dx.doi.org/10.1016/S0140-6736(25)01330-3
2025
Farbehi N; Alinejad-Rokny H; Chtanova T; Rnjak-Kovacina J, 2025, 'Spatial and single-cell transcriptomics unravel the complex interplay between the body and medical implants', Cell Biomaterials, 1, http://dx.doi.org/10.1016/j.celbio.2025.100099
2025
Green NFO; Sutton GJ; Pérez-Burillo J; Wang J; Bagot S; Danon HG; Walsh K; Gokool A; Miles SA; Yang G; Herring CA; Liang Y; Pfundstein G; Sytnyk V; Alinejad-Rokny H; Lister R; Rosenbluh J; Gagnon-Bartsch JA; Voineagu I, 2025, 'CRISPRi screening in cultured human astrocytes uncovers distal enhancers controlling genes dysregulated in Alzheimer’s disease', Nature Neuroscience, http://dx.doi.org/10.1038/s41593-025-02154-3
2025
MacPhillamy C; Chen T; Hiendleder S; Williams JL; Alinejad-Rokny H; Low WY, 2024, 'DNA methylation analysis to differentiate reference, breed, and parent-of-origin effects in the bovine pangenome era', Gigascience, 13, http://dx.doi.org/10.1093/gigascience/giae061
2024
Abedini SS; Akhavantabasi S; Liang Y; Heng JIT; Alizadehsani R; Dehzangi I; Bauer DC; Alinejad-Rokny H, 2024, 'A critical review of the impact of candidate copy number variants on autism spectrum disorder', Mutation Research Reviews in Mutation Research, 794, http://dx.doi.org/10.1016/j.mrrev.2024.108509
2024
Sadeghi A; Hajati F; Rezaee A; Sadeghi M; Argha A; Alinejad-Rokny H, 2024, '3DECG-Net: ECG fusion network for multi-label cardiac arrhythmia detection', Computers in Biology and Medicine, 182, http://dx.doi.org/10.1016/j.compbiomed.2024.109126
2024
Razzak I; Naz S; Alinejad-Rokny H; Nguyen TN; Khalifa F, 2024, 'A Cascaded Mutliresolution Ensemble Deep Learning Framework for Large Scale Alzheimer's Disease Detection Using Brain MRIs', IEEE ACM Transactions on Computational Biology and Bioinformatics, 21, pp. 573 - 581, http://dx.doi.org/10.1109/TCBB.2022.3219032
2024
Xue J; Alinejad-Rokny H; Liang K, 2024, 'Navigating micro- and nano-motors/swimmers with machine learning: Challenges and future directions', Chemphysmater, 3, pp. 273 - 283, http://dx.doi.org/10.1016/j.chphma.2024.06.001
2024
Jafari M; Sadeghi D; Shoeibi A; Alinejad-Rokny H; Beheshti A; García DL; Chen Z; Acharya UR; Gorriz JM, 2024, 'Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023', Applied Intelligence, 54, pp. 35 - 79, http://dx.doi.org/10.1007/s10489-023-05155-6
2024
Rahaie Z; Rabiee HR; Alinejad-Rokny H, 2024, 'CNVDeep: deep association of copy number variants with neurocognitive disorders', BMC Bioinformatics, 25, http://dx.doi.org/10.1186/s12859-024-05874-8
2024
Islam S; Mugdha SBS; Dipta SR; Arafat ME; Shatabda S; Alinejad-Rokny H; Dehzangi I, 2024, 'MethEvo: an accurate evolutionary information-based methylation site predictor', Neural Computing and Applications, 36, pp. 201 - 212, http://dx.doi.org/10.1007/s00521-022-07738-9
2024
Zahedi R; Ghamsari R; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2024, 'Deep learning in spatially resolved transcriptfomics: A comprehensive technical view', Briefings in Bioinformatics, 25, http://dx.doi.org/10.1093/bib/bbae082
2024
Ahmadi-Dastgerdi N; Hosseini-Nejad H; Alinejad-Rokny H, 2024, 'A Hardware-Efficient Novelty-Aware Spike Sorting Approach for Brain-Implantable Microsystems', International Journal of Neural Systems, 34, http://dx.doi.org/10.1142/S0129065724500679
2024
Truong P; Shen S; Joshi S; Islam MI; Zhong L; Raftery MJ; Afrasiabi A; Alinejad-Rokny H; Nguyen M; Zou X; Bhuyan GS; Sarowar CH; Ghodousi ES; Stonehouse O; Mohamed S; Toscan CE; Connerty P; Kakadia PM; Bohlander SK; Michie KA; Larsson J; Lock RB; Walkley CR; Thoms JAI; Jolly CJ; Pimanda JE, 2024, 'TOPORS E3 ligase mediates resistance to hypomethylating agent cytotoxicity in acute myeloid leukemia cells', Nature Communications, 15, pp. 7360, http://dx.doi.org/10.1038/s41467-024-51646-6
2024
Hosseinzadeh M; Haider A; Malik MH; Adeli M; Mzoughi O; Gemeay E; Mohammadi M; Alinejad-Rokny H; Khoshvaght P; Porntaveetus T; Rahmani AM, 2024, 'Enhanced heart sound classification using Mel frequency cepstral coefficients and comparative analysis of single vs. ensemble classifier strategies', Plos One, 19, http://dx.doi.org/10.1371/journal.pone.0316645
2024
Shabani N; Beheshti A; Farhood H; Bower M; Garrett M; Alinejad-Rokny H, 2023, 'A Rule-Based Approach for Mining Creative Thinking Patterns from Big Educational Data', Appliedmath, 3, pp. 243 - 267, http://dx.doi.org/10.3390/appliedmath3010014
2023
Wang S; Beheshti A; Wang Y; Lu J; Sheng QZ; Elbourn S; Alinejad-Rokny H, 2023, 'Learning Distributed Representations and Deep Embedded Clustering of Texts', Algorithms, 16, http://dx.doi.org/10.3390/a16030158
2023
Hong L; Modirrousta MH; Hossein Nasirpour M; Mirshekari Chargari M; Mohammadi F; Moravvej SV; Rezvanishad L; Rezvanishad M; Bakhshayeshi I; Alizadehsani R; Razzak I; Alinejad-Rokny H; Nahavandi S, 2023, 'GAN-LSTM-3D: An efficient method for lung tumour 3D reconstruction enhanced by attention-based LSTM', Caai Transactions on Intelligence Technology, http://dx.doi.org/10.1049/cit2.12223
2023
Ghamsari R; Rosenbluh J; Menon AV; Lovell NH; Alinejad-Rokny H, 2023, 'Technological Convergence: Highlighting the Power of CRISPR Single-Cell Perturbation Toolkit for Functional Interrogation of Enhancers', Cancers, 15, http://dx.doi.org/10.3390/cancers15143566
2023
Hansun S; Argha A; Alinejad-Rokny H; Liaw ST; Celler BG; Marks GB, 2023, 'Revisiting Transfer Learning Method for Tuberculosis Diagnosis', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS, http://dx.doi.org/10.1109/EMBC40787.2023.10340441
2023
Rahaie Z; Rabiee HR; Alinejad-Rokny H, 2023, 'DeepGenePrior: A deep learning model for prioritizing genes affected by copy number variants', Plos Computational Biology, 19, http://dx.doi.org/10.1371/journal.pcbi.1011249
2023
Khozeimeh F; Alizadehsani R; Shirani M; Tartibi M; Shoeibi A; Alinejad-Rokny H; Harlapur C; Sultanzadeh SJ; Khosravi A; Nahavandi S; Tan RS; Acharya UR, 2023, 'ALEC: Active learning with ensemble of classifiers for clinical diagnosis of coronary artery disease', Computers in Biology and Medicine, 158, http://dx.doi.org/10.1016/j.compbiomed.2023.106841
2023
Subramanian S; Thoms JAI; Huang Y; Cornejo-Páramo P; Koch FC; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll PS; Chacon-Fajardo D; Beck D; Curtis DJ; Yehson K; Antonenas V; O'Brien T; Trickett A; Powell JA; Lewis ID; Pitson SM; Gandhi MK; Lane SW; Vafaee F; Wong ES; Göttgens B; Alinejad-Rokny H; Wong JWH; Pimanda JE, 2023, 'Genome-wide transcription factor–binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs', Blood, 142, pp. 1448 - 1462, http://dx.doi.org/10.1182/blood.2023021120
2023
Shamsi A; Asgharnezhad H; Bouchani Z; Jahanian K; Saberi M; Wang X; Razzak I; Alizadehsani R; Mohammadi A; Alinejad-Rokny H, 2023, 'A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis', Neural Computing and Applications, 35, pp. 22179 - 22188, http://dx.doi.org/10.1007/s00521-023-08930-1
2023
Wang F; Alinejad-Rokny H; Lin J; Gao T; Chen X; Zheng Z; Meng L; Li X; Wong KC, 2023, 'A Lightweight Framework For Chromatin Loop Detection at the Single-Cell Level', Advanced Science, 10, http://dx.doi.org/10.1002/advs.202303502
2023
Azim SM; Sabab NHN; Noshadi I; Alinejad-Rokny H; Sharma A; Shatabda S; Dehzangi I, 2023, 'Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers', Informatics in Medicine Unlocked, 42, http://dx.doi.org/10.1016/j.imu.2023.101348
2023
Jafari M; Shoeibi A; Khodatars M; Ghassemi N; Moridian P; Alizadehsani R; Khosravi A; Ling SH; Delfan N; Zhang YD; Wang SH; Gorriz JM; Alinejad-Rokny H; Acharya UR, 2023, 'Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review', Computers in Biology and Medicine, 160, http://dx.doi.org/10.1016/j.compbiomed.2023.106998
2023
Alizadehsani R; Roshanzamir M; Izadi NH; Gravina R; Kabir HMD; Nahavandi D; Alinejad-Rokny H; Khosravi A; Acharya UR; Nahavandi S; Fortino G, 2023, 'Swarm Intelligence in Internet of Medical Things: A Review', Sensors, 23, http://dx.doi.org/10.3390/s23031466
2023
Labani M; Beheshti A; Argha A; Alinejad-Rokny H, 2023, 'A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants', International Journal of Molecular Sciences, 24, http://dx.doi.org/10.3390/ijms24032472
2023
Shoeibi A; Khodatars M; Jafari M; Ghassemi N; Moridian P; Alizadehsani R; Ling SH; Khosravi A; Alinejad-Rokny H; Lam HK; Fuller-Tyszkiewicz M; Acharya UR; Anderson D; Zhang Y; Gorriz JM, 2023, 'Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review', Information Fusion, 93, pp. 85 - 117, http://dx.doi.org/10.1016/j.inffus.2022.12.010
2023
Parhami P; Fateh M; Rezvani M; Alinejad-Rokny H, 2023, 'A comparison of deep neural network models for cluster cancer patients through somatic point mutations', Journal of Ambient Intelligence and Humanized Computing, 14, pp. 10883 - 10898, http://dx.doi.org/10.1007/s12652-022-04351-5
2023
Afrasiabi A; Alinejad-Rokny H; Khosh A; Rahnama M; Lovell N; Xu Z; Ebrahimi D, 2022, 'The low abundance of CpG in the SARS-CoV-2 genome is not an evolutionarily signature of ZAP', Scientific Reports, 12, pp. 2420, http://dx.doi.org/10.1038/s41598-022-06046-5
2022
Debnath T; Reza MM; Rahman A; Beheshti A; Band SS; Alinejad-Rokny H, 2022, 'Four-layer ConvNet to facial emotion recognition with minimal epochs and the significance of data diversity', Scientific Reports, 12, http://dx.doi.org/10.1038/s41598-022-11173-0
2022
Band SS; Ardabili S; Yarahmadi A; Pahlevanzadeh B; Kiani AK; Beheshti A; Alinejad-Rokny H; Dehzangi I; Chang A; Mosavi A; Moslehpour M, 2022, 'A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis', Frontiers in Public Health, 10, http://dx.doi.org/10.3389/fpubh.2022.869238
2022
Rezaie N; Bayati M; Hamidi M; Tahaei MS; Khorasani S; Lovell NH; Breen J; Rabiee HR; Alinejad-Rokny H, 2022, 'Somatic point mutations are enriched in non-coding RNAs with possible regulatory function in breast cancer', Communications Biology, 5, http://dx.doi.org/10.1038/s42003-022-03528-0
2022
MacPhillamy C; Alinejad-Rokny H; Pitchford WS; Low WY, 2022, 'Cross-species enhancer prediction using machine learning', Genomics, 114, http://dx.doi.org/10.1016/j.ygeno.2022.110454
2022
Saberi-Movahed F; Mohammadifard M; Mehrpooya A; Rezaei-Ravari M; Berahmand K; Rostami M; Karami S; Najafzadeh M; Hajinezhad D; Jamshidi M; Abedi F; Mohammadifard M; Farbod E; Safavi F; Dorvash M; Mottaghi-Dastjerdi N; Vahedi S; Eftekhari M; Saberi-Movahed F; Alinejad-Rokny H; Band SS; Tavassoly I, 2022, 'Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods', Computers in Biology and Medicine, 146, http://dx.doi.org/10.1016/j.compbiomed.2022.105426
2022
Grapotte M; Saraswat M; Bessière C; Menichelli C; Ramilowski JA; Severin J; Hayashizaki Y; Itoh M; Tagami M; Murata M; Kojima-Ishiyama M; Noma S; Noguchi S; Kasukawa T; Hasegawa A; Suzuki H; Nishiyori-Sueki H; Frith MC; Abugessaisa I; Aitken S; Aken BL; Alam I; Alam T; Alasiri R; Alhendi AMN; Alinejad-Rokny H; Alvarez MJ; Andersson R; Arakawa T; Araki M; Arbel T; Archer J; Archibald AL; Arner E; Arner P; Asai K; Ashoor H; Astrom G; Babina M; Baillie JK; Bajic VB; Bajpai A; Baker S; Baldarelli RM; Balic A; Bansal M; Batagov AO; Batzoglou S; Beckhouse AG; Beltrami AP; Beltrami CA; Bertin N; Bhattacharya S; Bickel PJ; Blake JA; Blanchette M; Bodega B; Bonetti A; Bono H; Bornholdt J; Bttcher M; Bougouffa S; Boyd M; Breda J; Brombacher F; Brown JB; Bult CJ; Burroughs AM; Burt DW; Busch A; Caglio G; Califano A; Cameron CJ; Cannistraci CV; Carbone A; Carlisle AJ; Carninci P; Carter KW; Cesselli D; Chang JC; Chen JC; Chen Y; Chierici M; Christodoulou J; Ciani Y; Clark EL; Coskun M; Dalby M; Dalla E; Daub CO; Davis CA; de Hoon MJL; de Rie D; Denisenko E; Deplancke B; Detmar M; Deviatiiarov R; Di Bernardo D; Diehl AD; Dieterich LC, 2022, 'Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network (Nature Communications, (2021), 12, 1, (3297), 10.1038/s41467-021-23143-7)', Nature Communications, 13, http://dx.doi.org/10.1038/s41467-022-28758-y
2022
Sharifrazi D; Alizadehsani R; Joloudari JH; Band SS; Hussain S; Sani ZA; Hasanzadeh F; Shoeibi A; Dehzangi A; Sookhak M; Alinejad-Rokny H, 2022, 'CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering', Mathematical Biosciences and Engineering, 19, pp. 2381 - 2402, http://dx.doi.org/10.3934/MBE.2022110
2022
Dashti H; Dehzangi I; Bayati M; Breen J; Beheshti A; Lovell N; Rabiee HR; Alinejad-Rokny H, 2022, 'Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer', BMC Bioinformatics, 23, http://dx.doi.org/10.1186/s12859-022-04652-8
2022
Afrasiabi A; Keane JT; Ong LTC; Alinejad-Rokny H; Fewings NL; Booth DR; Parnell GP; Swaminathan S, 2022, 'Genetic and transcriptomic analyses support a switch to lytic phase in Epstein Barr virus infection as an important driver in developing Systemic Lupus Erythematosus', Journal of Autoimmunity, 127, http://dx.doi.org/10.1016/j.jaut.2021.102781
2022
Labani M; Afrasiabi A; Beheshti A; Lovell NH; Alinejad-Rokny H, 2022, 'PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study', Computational and Structural Biotechnology Journal, 20, pp. 4975 - 4983, http://dx.doi.org/10.1016/j.csbj.2022.09.001
2022
Sharifonnasabi F; Jhanjhi NZ; John J; Obeidy P; Band SS; Alinejad-Rokny H; Baz M, 2022, 'Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography', Frontiers in Public Health, 10, http://dx.doi.org/10.3389/fpubh.2022.879418
2022
Argha A; Celler BG; Alinejad-Rokny H; Lovell NH, 2022, 'Blood Pressure Estimation From Korotkoff Sound Signals Using an End-to-End Deep-Learning-Based Algorithm', IEEE Transactions on Instrumentation and Measurement, 71, http://dx.doi.org/10.1109/TIM.2022.3217865
2022
Subramanian S; Thoms JA; Huang Y; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll PS; Fajardo DC; Beck D; Curtis DJ; Yehson K; Antonenas V; O' Brien T; Trickett A; Powell J; Pitson SM; Gandhi MK; Cornejo P; Wong E; Lane SW; Gottgens B; Rokny HA; Wong JWH; Pimanda JE, 2022, 'Comparative Analysis of Genome-Scale Gene Regulatory Networks in Human Hematopoietic Stem and Myeloid Progenitor Fractions', BLOOD, 140, pp. 2846 - 2848, http://dx.doi.org/10.1182/blood-2022-165620
2022
Labani M; Beheshti A; Lovell NH; Alinejad-Rokny H; Afrasiabi A, 2022, 'KARAJ: An Efficient Adaptive Multi-Processor Tool to Streamline Genomic and Transcriptomic Sequence Data Acquisition', International Journal of Molecular Sciences, 23, http://dx.doi.org/10.3390/ijms232214418
2022
Alinejad-Rokny H; Modegh RG; Rabiee HR; Sarbandi ER; Rezaie N; Tam KT; Forrest ARR, 2022, 'MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments', Plos Computational Biology, 18, http://dx.doi.org/10.1371/journal.pcbi.1010241
2022
Ghareyazi A; Kazemi A; Hamidieh K; Dashti H; Tahaei MS; Rabiee HR; Alinejad-Rokny H; Dehzangi I, 2022, 'Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types', BMC Bioinformatics, 23, http://dx.doi.org/10.1186/s12859-022-04840-6
2022
Pho KH; Akbarzadeh H; Parvin H; Nejatian S; Alinejad-Rokny H, 2021, 'A multi-level consensus function clustering ensemble', Soft Computing, 25, pp. 13147 - 13165, http://dx.doi.org/10.1007/s00500-021-06092-7
2021
Walsh K; Gokool A; Alinejad-Rokny H; Voineagu I, 2021, 'NeuroCirc: an integrative resource of circular RNA expression in the human brain', Bioinformatics, 37, pp. 3664 - 3666, http://dx.doi.org/10.1093/bioinformatics/btab230
2021
MacPhillamy C; Pitchford WS; Alinejad-Rokny H; Low WY, 2021, 'Opportunity to improve livestock traits using 3D genomics', Animal Genetics, 52, pp. 785 - 798, http://dx.doi.org/10.1111/age.13135
2021
Ghareyazi A; Mohseni A; Dashti H; Beheshti A; Dehzangi A; Rabiee HR; Alinejad-Rokny H, 2021, 'Whole-genome analysis of de novo somatic point mutations reveals novel mutational biomarkers in pancreatic cancer', Cancers, 13, http://dx.doi.org/10.3390/cancers13174376
2021
Mahmoudi MR; Akbarzadeh H; Parvin H; Nejatian S; Rezaie V; Alinejad-Rokny H, 2021, 'Consensus function based on cluster-wise two level clustering', Artificial Intelligence Review, 54, pp. 639 - 665, http://dx.doi.org/10.1007/s10462-020-09862-1
2021
Liu N; Low WY; Alinejad-Rokny H; Pederson S; Sadlon T; Barry S; Breen J, 2021, 'Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C', Epigenetics and Chromatin, 14, http://dx.doi.org/10.1186/s13072-021-00417-4
2021
Afrasiabi A; Keane JT; Ik-Tsen Heng J; Palmer EE; Lovell NH; Alinejad-Rokny H, 2021, 'Quantitative neurogenetics: Applications in understanding disease', Biochemical Society Transactions, 49, pp. 1621 - 1631, http://dx.doi.org/10.1042/BST20200732
2021
Grapotte M; Saraswat M; Bessière C; Menichelli C; Ramilowski JA; Severin J; Hayashizaki Y; Itoh M; Tagami M; Murata M; Kojima-Ishiyama M; Noma S; Noguchi S; Kasukawa T; Hasegawa A; Suzuki H; Nishiyori-Sueki H; Frith MC; Abugessaisa I; Aitken S; Aken BL; Alam I; Alam T; Alasiri R; Alhendi AMN; Alinejad-Rokny H; Alvarez MJ; Andersson R; Arakawa T; Araki M; Arbel T; Archer J; Archibald AL; Arner E; Arner P; Asai K; Ashoor H; Astrom G; Babina M; Baillie JK; Bajic VB; Bajpai A; Baker S; Baldarelli RM; Balic A; Bansal M; Batagov AO; Batzoglou S; Beckhouse AG; Beltrami AP; Beltrami CA; Bertin N; Bhattacharya S; Bickel PJ; Blake JA; Blanchette M; Bodega B; Bonetti A; Bono H; Bornholdt J; Bttcher M; Bougouffa S; Boyd M; Breda J; Brombacher F; Brown JB; Bult CJ; Burroughs AM; Burt DW; Busch A; Caglio G; Califano A; Cameron CJ; Cannistraci CV; Carbone A; Carlisle AJ; Carninci P; Carter KW; Cesselli D; Chang JC; Chen JC; Chen Y; Chierici M; Christodoulou J; Ciani Y; Clark EL; Coskun M; Dalby M; Dalla E; Daub CO; Davis CA; de Hoon MJL; de Rie D; Denisenko E; Deplancke B; Detmar M; Deviatiiarov R; Di Bernardo D; Diehl AD; Dieterich LC, 2021, 'Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network', Nature Communications, 12, http://dx.doi.org/10.1038/s41467-021-23143-7
2021
Shamshirband S; Fathi M; Dehzangi A; Chronopoulos AT; Alinejad-Rokny H, 2021, 'A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues', Journal of Biomedical Informatics, 113, http://dx.doi.org/10.1016/j.jbi.2020.103627
2021
Rajaei P; Jahanian KH; Beheshti A; Band SS; Dehzangi A; Alinejad-rokny H, 2021, 'VIRMOTIF: A user-friendly tool for viral sequence analysis', Genes, 12, pp. 1 - 9, http://dx.doi.org/10.3390/genes12020186
2021
Heidari R; Akbariqomi M; Asgari Y; Ebrahimi D; Alinejad-Rokny H, 2021, 'A systematic review of long non-coding RNAs with a potential role in breast cancer', Mutation Research Reviews in Mutation Research, 787, http://dx.doi.org/10.1016/j.mrrev.2021.108375
2021
Hosseinpoor M; Parvin H; Nejatian S; Rezaie V; Bagherifard K; Dehzangi A; Beheshti A; Alinejad-Rokny H, 2020, 'Proposing a novel community detection approach to identify co-interacting genomic regions', Mathematical Biosciences and Engineering, 17, pp. 2193 - 2217, http://dx.doi.org/10.3934/mbe.2020117
2020
Bahrani P; Minaei-Bidgoli B; Parvin H; Mirzarezaee M; Keshavarz A; Alinejad-Rokny H, 2020, 'User and item profile expansion for dealing with cold start problem', Journal of Intelligent and Fuzzy Systems, 38, pp. 4471 - 4483, http://dx.doi.org/10.3233/JIFS-191225
2020
Niu H; Khozouie N; Parvin H; Alinejad-Rokny H; Beheshti A; Mahmoudi MR, 2020, 'An ensemble of locally reliable cluster solutions', Applied Sciences Switzerland, 10, pp. 1891, http://dx.doi.org/10.3390/app10051891
2020
Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest ARR; Alinejad-Rokny H, 2020, 'CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes', Scientific Reports, 10, pp. 1286, http://dx.doi.org/10.1038/s41598-020-58107-2
2020
Niu H; Xu W; Akbarzadeh H; Parvin H; Beheshti A; Alinejad-Rokny H, 2020, 'Deep feature learnt by conventional deep neural network', Computers and Electrical Engineering, 84, pp. 106656, http://dx.doi.org/10.1016/j.compeleceng.2020.106656
2020
Alinejad-Rokny H; Heng JIT; Forrest ARR, 2020, 'Brain-Enriched Coding and Long Non-coding RNA Genes Are Overrepresented in Recurrent Neurodevelopmental Disorder CNVs', Cell Reports, 33, http://dx.doi.org/10.1016/j.celrep.2020.108307
2020
Khakmardan S; Rezvani M; Pouyan AA; Fateh M; Alinejad-Rokny H, 2020, 'MHiC, an integrated user-friendly tool for the identification and visualization of significant interactions in Hi-C data', BMC Genomics, 21, pp. 225, http://dx.doi.org/10.1186/s12864-020-6636-7
2020
Woodward KJ; Stampalia J; Vanyai H; Rijhumal H; Potts K; Taylor F; Peverall J; Grumball T; Sivamoorthy S; Alinejad-Rokny H; Wray J; Whitehouse A; Nagarajan L; Scurlock J; Afchani S; Edwards M; Murch A; Beilby J; Baynam G; Kiraly-Borri C; McKenzie F; Heng JIT, 2019, 'Atypical nested 22q11.2 duplications between LCR22B and LCR22D are associated with neurodevelopmental phenotypes including autism spectrum disorder with incomplete penetrance', Molecular Genetics and Genomic Medicine, 7, pp. e00507, http://dx.doi.org/10.1002/mgg3.507
2019
Masoudiasl I; Vahdat S; Hessam S; Shamshirband S; Alinejad-Rokny H, 2019, 'Proposing an Integrated Method based on Fuzzy Tuning and ICA Techniques to Identify the Most Influencing Features in Breast Cancer', IRANIAN RED CRESCENT MEDICAL JOURNAL, 21, http://dx.doi.org/10.5812/ircmj.92077
2019
Vafaee F; Dashti H; Alinejad-Rokny H, 2018, 'Transcriptomic Data Normalization', Encyclopedia of Bioinformatics and Computational Biology, Elsevier, http://dx.doi.org/10.1016/B978-0-12-809633-8.20209-4
2018
Kalantari A; Kamsin A; Shamshirband S; Gani A; Alinejad-Rokny H; Chronopoulos AT, 2018, 'Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions', Neurocomputing, 276, pp. 2 - 22, http://dx.doi.org/10.1016/j.neucom.2017.01.126
2018
Alinejad-Rokny H; Sadroddiny E; Scaria V, 2018, 'Machine learning and data mining techniques for medical complex data analysis', Neurocomputing, 276, pp. 1, http://dx.doi.org/10.1016/j.neucom.2017.09.027
2018
Vafaee F; Diakos C; Kirschner M; Reid G; Michael M; Horvath LISA; Alinejad-Rokny H; Cheng ZJ; Kuncic Z; Clarke S, 2018, 'A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis', npj Systems Biology and Applications, 4, pp. 20 - 20, http://dx.doi.org/10.1038/s41540-018-0056-1
2018
Poulton C; Baynam G; Yates C; Alinejad-Rokny H; Williams S; Wright H; Woodward KJ; Sivamoorthy S; Peverall J; Shipman P; Ravine D; Beilby J; Heng JIT, 2018, 'A review of structural brain abnormalities in Pallister-Killian syndrome', Molecular Genetics and Genomic Medicine, 6, pp. 92 - 98, http://dx.doi.org/10.1002/mgg3.351
2018
Alinejad-Rokny H; Parvin H; Ahangarikiasari H, 2017, 'Pattern Mining and Identifying Co-Expressed Genes from RNA-Seq Dataset Using a New Swarm Intelligence-Based Clustering (Advanced Science, Engineering and Medicine, Vol. 9(1), pp. 36–45 (2017))', Advanced Science, Engineering and Medicine, 9, pp. 618 - 618, http://dx.doi.org/10.1166/asem.2017.2064
2017
Alinejad-Rokny H; Parvin H; Ahangarikiasari H, 2017, 'Pattern Mining and Identifying Co-Expressed Genes from RNA-Seq Dataset Using a New Swarm Intelligence-Based Clustering', Advanced Science, Engineering and Medicine, 9, pp. 36 - 45, http://dx.doi.org/10.1166/asem.2017.1959
2017
Alinejad-Rokny H, 2017, 'A Method to Avoid Gapped Sequential Patterns in Biological Sequences: Case Study: HIV and Cancer Sequences', Journal of Neuroscience and Neuroengineering, 4, pp. 49 - 53, http://dx.doi.org/10.1166/jnsne.2017.1114
2017
Baghernia A; Pavin H; Mirnabibaboli M; Alinejad-Rokny H, 2017, 'Clustering High-Dimensional Data Stream: A Survey on Subspace Clustering, Projected Clustering on Bioinformatics Applications (Advanced Science, Engineering and Medicine, Vol. 8(9), pp. 749–757 (2016))', Advanced Science, Engineering and Medicine, 9, pp. 617 - 617, http://dx.doi.org/10.1166/asem.2017.2063
2017
Alinejad-Rokny H, 2016, 'Proposing on optimized homolographic motif mining strategy based on parallel computing for complex biological networks', Journal of Medical Imaging and Health Informatics, 6, pp. 416 - 424, http://dx.doi.org/10.1166/jmihi.2016.1707
2016
Lloyd SB; Lichtfuss M; Amarasena TH; Alcantara S; De Rose R; Tachedjian G; Alinejad-Rokny H; Venturi V; Davenport MP; Winnall WR; Kent SJ, 2016, 'High fidelity simian immunodeficiency virus reverse transcriptase mutants have impaired replication in vitro and in vivo', Virology, 492, pp. 1 - 10, http://dx.doi.org/10.1016/j.virol.2016.02.008
2016
Alinejad-Rokny H; Masoud M, 2016, 'A method for hypermutated viral sequences detection in fastq and bam format files', Journal of Medical Imaging and Health Informatics, 6, pp. 1202 - 1208, http://dx.doi.org/10.1166/jmihi.2016.1977
2016
Alinejad-Rokny H; Anwar F; Waters SA; Davenport MP; Ebrahimi D, 2016, 'Source of CpG depletion in the HIV-1 genome', Molecular Biology and Evolution, 33, pp. 3205 - 3212, http://dx.doi.org/10.1093/molbev/msw205
2016
Baghernia A; Pavin H; Mirnabibaboli M; Alinejad-Rokny H, 2016, 'Clustering High-Dimensional Data Stream: A Survey on Subspace Clustering, Projected Clustering on Bioinformatics Applications', Advanced Science, Engineering and Medicine, 8, pp. 749 - 757, http://dx.doi.org/10.1166/asem.2016.1915
2016
Parvin H; Mirnabibaboli M; Alinejad-Rokny H, 2015, 'Proposing a classifier ensemble framework based on classifier selection and decision tree', Engineering Applications of Artificial Intelligence, 37, pp. 34 - 42, http://dx.doi.org/10.1016/j.engappai.2014.08.005
2015
Alinejad-Rokny H; Ebrahimi D, 2015, 'A method to avoid errors associated with the analysis of hypermutated viral sequences by alignment-based methods', Journal of Biomedical Informatics, 58, pp. 220 - 225, http://dx.doi.org/10.1016/j.jbi.2015.10.008
2015
Martyushev AP; Petravic J; Grimm AJ; Alinejad-Rokny H; Gooneratne SL; Reece JC; Cromer D; Kent SJ; Davenport MP, 2015, 'Epitope-specific CD8+ T cell kinetics rather than viral variability determine the timing of immune escape in simian immunodeficiency virus infection', Journal of Immunology, 194, pp. 4112 - 4121, http://dx.doi.org/10.4049/jimmunol.1400793
2015
Minaei-Bidgoli B; Parvin H; Alinejad-Rokny H; Alizadeh H; Punch WF, 2014, 'Effects of resampling method and adaptation on clustering ensemble efficacy', Artificial Intelligence Review, 41, pp. 27 - 48, http://dx.doi.org/10.1007/s10462-011-9295-x
2014
Gooneratne SL; Alinejad-Rokny H; Ebrahimi D; Bohn PS; Wiseman RW; O'Connor DH; Davenport MP; Kent SJ, 2014, 'Linking pig-tailed macaque major histocompatibility complex class I haplotypes and cytotoxic T lymphocyte escape mutations in simian immunodeficiency virus infection', Journal of Virology, 88, pp. 14310 - 14325, http://dx.doi.org/10.1128/JVI.02428-14
2014
Ebrahimi D; Alinejad-Rokny H; Davenport MP; Ebrahimi Mohammadi D, 2014, 'Insights into the motif preference of APOBEC3 enzymes', Plos One, 9, pp. e87679, http://dx.doi.org/10.1371/journal.pone.0087679
2014
Ahmadinia M; Alinejad-Rokny H; Ahangarikiasari H, 2014, 'Data Aggregation in Wireless Sensor Networks Based on Environmental Similarity: A Learning Automata Approach', Journal of Networks, 9, http://dx.doi.org/10.4304/jnw.9.10.2567-2573
2014
Alinejad-Rokny H; Pourshaban H; Orimi AG; Baboli MM, 2014, 'Network motifs detection strategies and using for bioinformatic networks', Journal of Bionanoscience, 8, pp. 353 - 359, http://dx.doi.org/10.1166/jbns.2014.1245
2014
Mokhtari SM; Alinejad-Rokny H; Jalalifar H, 2014, 'Selection of the best well control system by using fuzzy multiple-attribute decision-making methods', Journal of Applied Statistics, 41, pp. 1105 - 1121, http://dx.doi.org/10.1080/02664763.2013.862218
2014
Jamnejad I; Heidarzadegan A; Parvin H; Alinejad-Rokny H, 2014, 'Localizing program bugs based on program invariant', International Journal of Computing and Digital Systems, 3, pp. 141 - 150, http://dx.doi.org/10.12785/IJCDS/030208
2014
Jamnejad MI; Parvin H; Alinejad-Rokny H; Heidarzadegan A, 2014, 'Proposing a New Method Based on Linear Discriminant Analysis to Build a Robust Classifier', Journal of Bioinformatics and Intelligent Control, 3, pp. 186 - 193, http://dx.doi.org/10.1166/jbic.2014.1086
2014
Parvin H; Alinejad-Rokny H; Minaei-Bidgoli B; Parvin S, 2013, 'A new classifier ensemble methodology based on subspace learning', Journal of Experimental and Theoretical Artificial Intelligence, 25, pp. 227 - 250, http://dx.doi.org/10.1080/0952813X.2012.715683
2013
Parvin H; Minaei-Bidgoli B; Alinejad-Rokny H, 2013, 'A new imbalanced learning and dictions tree method for breast cancer diagnosis', Journal of Bionanoscience, 7, pp. 673 - 678, http://dx.doi.org/10.1166/jbns.2013.1162
2013
Javanmard R; JeddiSaravi K; Alinejad-Rokny H, 2013, 'Proposed a new method for rules extraction using artificial neural network and artificial immune system in cancer diagnosis', Journal of Bionanoscience, 7, pp. 665 - 672, http://dx.doi.org/10.1166/jbns.2013.1160
2013
Ahmadinia M; Meybodi M; Esnaashari M; Alinejad-Rokny H, 2013, 'Energy-efficient and multi-stage clustering algorithm in wireless sensor networks using cellular learning automata', IETE Journal of Research, 59, pp. 774 - 782, http://dx.doi.org/10.4103/0377-2063.126958
2013
Parvin H; Alinejad-Rokny H; Parvin S, 2013, 'A Classifier Ensemble of Binary Classifier Ensembles', International Journal of Learning Management Systems, 1, pp. 37 - 47, http://dx.doi.org/10.12785/ijlms/010204
2013
Parvin H; Alinejad-Rokny H; Parvin S, 2013, 'A New Clustering Ensemble Framework', International Journal of Learning Management Systems, 1, pp. 19 - 25, http://dx.doi.org/10.12785/ijlms/010103
2013
Alinejad-Rokny H; Farzaneh MK; Orimi AG; Pedram MM; Kiasari HA, 2013, 'Proposing a new structure for web mining and personalizing web pages', Journal of Emerging Technologies in Web Intelligence, 5, pp. 287 - 295, http://dx.doi.org/10.4304/jetwi.5.3.287-295
2013
Parvin H; Minaei-Bidgoli B; Alinejad-Rokny H; Punch WF, 2013, 'Data weighing mechanisms for clustering ensembles', Computers and Electrical Engineering, 39, pp. 1433 - 1450, http://dx.doi.org/10.1016/j.compeleceng.2013.02.004
2013
Sadeghi M; Alinejad-Rokny H, 2012, 'On covering of products of T-generalized state machines', Mathematical Sciences Letters, 1, pp. 43 - 52, http://dx.doi.org/10.12785/msl/010106
2012
Alizadeh H; Alinejad-Rokny H; Parvin H; Sohrabi B, 2012, 'A new inference engine: Surface Matching Degree', Applied Mathematical Modelling, http://dx.doi.org/10.1016/j.apm.2012.02.027
2012
Esmaeili L; Minaei-Bidgoli B; Alinejad-Rokny H; Nasiri M, 2012, 'Hybrid recommender system for joining virtual communities', Research Journal of Applied Sciences Engineering and Technology, 4, pp. 500 - 509
2012
Shirvani MH; Alinejad-Rokny H, 2012, 'Performance Assessment of Feasible Scheduling Multiprocessor Tasks Solutions by using DEA FDH method', Information Sciences Letters, 1, pp. 61 - 66, http://dx.doi.org/10.12785/isl/010106
2012
Parvin H; Alinejad-Rokny H; Seyedaghaee NR; Parvin S, 2012, 'A Heuristic Scalable Classifier Ensemble of Binary Classifier Ensembles', Journal of Bioinformatics and Intelligent Control, 1, pp. 163 - 170, http://dx.doi.org/10.1166/jbic.2013.1016
2012
Rokny HA; Pedram MM; Shirgahi H, 2011, 'Discovered motifs with using parallel Mprefixspan method', Scientific Research and Essays, 6, pp. 4220 - 4226, http://dx.doi.org/10.5897/sre11.212
2011
Minaei-Bidgoli B; Parvin H; Alizadeh H; Alinejad-Rokny H; Punch WF, 2011, 'Effects of resampling method and adaptation on clustering ensemble efficacy', Artificial Intelligence Review, pp. 1 - 22, http://dx.doi.org/10.1007/s10462-011-9295-x
2011
Parvin H; Alinejad-Rokny H; Asadi M, 2011, 'An ensemble based approach for feature selection', Australian Journal of Basic and Applied Sciences, 5, pp. 1153 - 1163
2011
Parvin H; Helmi H; Minaei B; Rokny HA; Shirgahi H, 2011, 'Linkage learning based on differences in local optimums of building blocks with one optima', International Journal of Physical Sciences, 6, pp. 3419 - 3425
2011
Conference Papers
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Luo R; Li Y; Chen L; He W; Lin TE; Liu Z; Zhang L; Song Z; Alinejad-Rokny H; Xia X; Liu T; Hui B; Yang M, 2025, 'DEEM: DIFFUSION MODELS SERVE AS THE EYES OF LARGE LANGUAGE MODELS FOR IMAGE PERCEPTION', in 13th International Conference on Learning Representations Iclr 2025, pp. 72484 - 72511
2025
Doan BG; Shamsi A; Guo XY; Mohammadi A; Alinejad-Rokny H; Sejdinovic D; Teney D; Ranasinghe DC; Abbasnejad E, 2025, 'Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks', in Proceedings of the Aaai Conference on Artificial Intelligence, pp. 16298 - 16307, http://dx.doi.org/10.1609/aaai.v39i15.33790
2025
Zhu J; Tan M; Yang M; Li R; Alinejad-Rokny H, 2025, 'CollectiveSFT: Scaling Large Language Models for Chinese Medical Benchmark with Collective Instructions in Healthcare', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 51 - 60, http://dx.doi.org/10.1007/978-981-96-1151-5_6
2025
Li J; Chen Y; Liu Z; Tan M; Zhang L; Li Y; Luo R; Chen L; Luo J; Argha A; Alinejad-Rokny H; Zhou W; Yang M, 2025, 'STORYTELLER: An Enhanced Plot-planning Framework for Coherent and Cohesive Story Generation', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 20818 - 20846, http://dx.doi.org/10.18653/v1/2025.findings-acl.1071
2025
Shamsi A; Becirovic R; Argha A; Abbasnejad E; Alinejad-Rokny H; Mohammadi A, 2025, 'ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance', in 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, pp. 5907 - 5911, presented at 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 05 October 2025 - 08 October 2025, http://dx.doi.org/10.1109/smc58881.2025.11342706
2025
Zhao J; Xu L; Tan M; Zhang L; Argha A; Alinejad-Rokny H; Yang M, 2025, 'RxSafeBench: Identifying Medication Safety Issues of Large Language Models in Simulated Consultation', in 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, pp. 4491 - 4496, presented at 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 15 December 2025 - 18 December 2025, http://dx.doi.org/10.1109/bibm66473.2025.11356353
2025
Zhu K; Zang Q; Jia S; Wu S; Fang F; Li Y; Guo S; Zheng T; Li B; Wu H; Qu X; Yang J; Liu Z; Yue X; Liu J; Lin C; Yang M; Alinejad-Rokny H; Ni S; Huang W; Zhang G, 2025, 'LIME: Less Is More for MLLM Evaluation', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 9086 - 9121, http://dx.doi.org/10.18653/v1/2025.findings-acl.474
2025
Chen G; Fan L; Gong Z; Xie N; Li Z; Liu Z; Li C; Qu Q; Alinejad-Rokny H; Ni S; Yang M, 2025, 'AgentCourt: Simulating Court with Adversarial Evolvable Lawyer Agents', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 5850 - 5865, http://dx.doi.org/10.18653/v1/2025.findings-acl.304
2025
Luo R; Zhang H; Chen L; Lin TE; Liu X; Wu Y; Yang M; Li Y; Wang M; Zeng P; Gao L; Shen HT; Li Y; Alinejad-Rokny H; Xia X; Huang F; Song J, 2025, 'MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 19655 - 19682, http://dx.doi.org/10.18653/v1/2025.findings-acl.1009
2025
Chen D; Liu Z; Fang F; Leong CT; Ni S; Argha A; Alinejad-Rokny H; Yang M; Li C, 2025, 'Expanding before Inferring: Enhancing Factuality in Large Language Models through Premature Layers Interpolation', in Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, pp. 12781 - 12796, presented at Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, - , http://dx.doi.org/10.18653/v1/2025.emnlp-main.645
2025
Sun Y; Chen G; Alinejad-Rokny H; Bao J; Huang Y; Liang B; Wong KF; Yang M; Xu R, 2025, 'Learning First-Order Logic Rules for Argumentation Mining', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 14133 - 14148, http://dx.doi.org/10.18653/v1/2025.acl-long.691
2025
Chen L; Shan R; Wang H; Wang L; Liu Z; Luo R; Wang J; Alinejad-Rokny H; Yang M, 2025, 'CLaSp: In-Context Layer Skip for Self-Speculative Decoding', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 31608 - 31618, http://dx.doi.org/10.18653/v1/2025.acl-long.1525
2025
Lee S; Zhou J; Ao C; Li K; Du X; He S; Wu H; Liu T; Liu J; Alinejad-Rokny H; Yang M; Liang Y; Wen Z; Ni S, 2025, 'Quantification of Large Language Model Distillation', in Proceedings of the Annual Meeting of the Association for Computational Linguistics, pp. 4985 - 5004, http://dx.doi.org/10.18653/v1/2025.acl-long.248
2025
Hansun S; Argha A; Alinejad-Rokny H; Liaw ST; Celler BG; Marks GB, 2024, 'Pulmonary Tuberculosis Detection Using an Ensemble of ConvNeXts', in Ibiomed 2024 Proceedings of the 5th International Conference on Biomedical Engineering 2024, pp. 29 - 33, http://dx.doi.org/10.1109/iBioMed62485.2024.10875706
2024
Montazerin M; Rahimian E; Naderkhani F; Atashzar SF; Alinejad-Rokny H; Mohammadi A, 2023, 'HYDRA-HGR: A Hybrid Transformer-Based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information', in ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, http://dx.doi.org/10.1109/ICASSP49357.2023.10096192
2023
Argha A; Li J; Magdy J; Alinejad-Rokny H; Celler BG; Butcher K; Ooi SY; Lovell NH, 2023, 'Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm', in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS, http://dx.doi.org/10.1109/EMBC40787.2023.10341108
2023
Asgharnezhad H; Shamsi A; Bakhshayeshi I; Alizadehsani R; Chamaani S; Alinejad-Rokny H, 2023, 'Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion', in International Conference on Digital Signal Processing DSP, http://dx.doi.org/10.1109/DSP58604.2023.10167869
2023
Danaei S; Bostani A; Moravvej SV; Mohammadi F; Alizadehsani R; Shoeibi A; Alinejad-Rokny H; Nahavandi S, 2022, 'Myocarditis Diagnosis: A Method using Mutual Learning-Based ABC and Reinforcement Learning', in IEEE Joint 22nd International Symposium on Computational Intelligence and Informatics and 8th International Conference on Recent Achievements in Mechatronics Automation Computer Science and Robotics Cinti Macro 2022 Proceedings, pp. 265 - 270, http://dx.doi.org/10.1109/CINTI-MACRo57952.2022.10029403
2022
Shahabikargar M; Beheshti A; Khatami A; Nguyen R; Zhang X; Alinejad-Rokny H, 2022, 'Domain Knowledge Enhanced Text Mining for Identifying Mental Disorder Patterns', in Proceedings 2022 IEEE 9th International Conference on Data Science and Advanced Analytics Dsaa 2022, http://dx.doi.org/10.1109/DSAA54385.2022.10032346
2022
Khozeimeh F; Roshanzamir M; Shoeibi A; Darbandy MT; Alizadehsani R; Alinejad-Rokny H; Ahmadian D; Khosravi A; Nahavandi S, 2022, 'Importance of Wearable Health Monitoring Systems Using IoMT; Requirements, Advantages, Disadvantages and Challenges', in IEEE Joint 22nd International Symposium on Computational Intelligence and Informatics and 8th International Conference on Recent Achievements in Mechatronics Automation Computer Science and Robotics Cinti Macro 2022 Proceedings, pp. 245 - 250, http://dx.doi.org/10.1109/CINTI-MACRo57952.2022.10029528
2022
Book Chapters
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Shoeibi A; Jafari M; Sadeghi D; Alizadehsani R; Alinejad-Rokny H; Beheshti A; Gorriz JM, 2024, 'Early Diagnosis of Schizophrenia in EEG Signals Using One Dimensional Transformer Model', in , pp. 139 - 149, http://dx.doi.org/10.1007/978-3-031-61140-7_14
2024
Roshanzamir M; Alizadehsani R; Moravvej SV; Joloudari JH; Alinejad-Rokny H; Gorriz JM, 2024, 'Enhancing Interpretability in Machine Learning: A Focus on Genetic Network Programming, Its Variants, and Applications', in , pp. 98 - 107, http://dx.doi.org/10.1007/978-3-031-61140-7_10
2024
Beheshti A; Alinejad-Rokny H; Suero Molina E; Di Ieva A, 2024, 'Understanding Big Data in Neurosurgery', in Advances in Experimental Medicine and Biology, pp. 157 - 175, http://dx.doi.org/10.1007/978-3-031-64892-2_10
2024
Shabani N; Beheshti A; Farhood H; Bower M; Garrett M; Rokny HA, 2022, 'iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data', in , pp. 352 - 356, http://dx.doi.org/10.1007/978-3-031-11647-6_68
2022
Wang S; Beheshti A; Wang Y; Lu J; Sheng QZ; Elbourn S; Alinejad-Rokny H; Galanis E, 2021, 'Assessment2Vec: Learning Distributed Representations of Assessments to Reduce Marking Workload', in Artificial Intelligence in Education, pp. 384 - 389, http://dx.doi.org/10.1007/978-3-030-78270-2_68
2021
Vafaee F; Dashti H; Alinejad-Rokny H, 2019, 'Transcriptomic Data Normalization', in Encyclopedia of Bioinformatics and Computational Biology Abc of Bioinformatics, pp. 364 - 371, http://dx.doi.org/10.1016/B978-0-12-809633-8.20209-4
2019
Conference Abstracts
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Taylor R; Taylor J; Denisenko E; Jones M; Clayton J; Laing N; Forrest A; Alinejad-Rokny H; Ravenscroft G, 2024, 'Mapping human skeletal muscle enhancers to increase rates of genetic diagnosis', in NEUROMUSCULAR DISORDERS, PERGAMON-ELSEVIER SCIENCE LTD, CZECH REPUBLIC, Prague, Vol. 43, presented at 29th International Congress of the World-Muscle-Society (WMS), CZECH REPUBLIC, Prague, 08 October 2024 - 12 October 2024, http://dx.doi.org/10.1016/j.nmd.2024.07.096
2024
Truong P; Shen S; Joshi S; Afrasiabi A; Zhong L; Raftery MJ; Larsson J; Lock RB; Walkley CR; Rokny HA; Thoms JAI; Jolly CJ; Pimanda JE, 2022, 'Genome-Wide CRISPR-Cas9 Screening Identifies a Synergy between Hypomethylating Agents and Sumoylation Blockade in Myelodysplastic Syndromes and Acute Myeloid Leukemia', in BLOOD, ELSEVIER, LA, New Orleans, Vol. 140, presented at 64th Annual Meeting and Exposition of the American-Society-of-Hematology (ASH), LA, New Orleans, 10 December 2022 - 13 December 2022, http://dx.doi.org/10.1182/blood-2022-165713
2022
Gooneratne S; Alinejad-Rokny H; Mohammadi D; Bohn P; Wiseman R; O'Connor D; Davenport M; Kent S, 2015, 'LINKING PIGTAIL MACAQUE MHC I HAPLOTYPES AND CTL ESCAPE MUTATIONS IN SIV INFECTION', in JOURNAL OF MEDICAL PRIMATOLOGY, WILEY-BLACKWELL, Vol. 44, pp. 335 - 335, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000361966000094&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
2015
As a very young early career researcher, Dr Rokny has an exceptional track record in securing a range of national and international awards and prizes, despite my early career status. These include:
- · Millennium Prize for Outstanding EMCR, Lorne Genome, Feb 2025.
- · Adjunct Research Scientist, CSIRO, Aug 2022-2023
- · Honorary Lecturer Fellow, University of Macquarie, Oct 2020-2023
- · Travel support award from Institute for Research in Fundamental Sciences, Iran, invited speaker, ($1.9K), Feb 2020
- · Health Data Analytics Program Leader, AI-enabled Processes (AIP) Research Centre, Dec 2019-curent
- · MBSJ2019 (42nd Annual Meeting of the Molecular Biology) Travel support award, Japan, ($1K), Dec 2019
- · RIKEN-HUGO award for best oral presentation in Human Genome Meeting 2019, South Korea, ($0.2K), Oct 2019
- · Highly competitive tenure-track UNSW Scientia Fellowship Program award in Aug 2019 ($680K)
- · Vice-chancellor fellowship award from RMIT, ($350K), May 2019 (declined in favour of UNSW Scientia Program).
- · HDR conference support award from UNSW Sydney, ($3K), Jul 2015
- · Travel support award from University of Tehran as invited speaker, Tehran, ($2K), Feb 2015
- · Ph.D scholarship from UNSW Sydney, ($87.5K for 3.5 years), Mar 2013
- · Top-up scholarship from the faculty of medicine, UNSW Sydney, ($30K for 3 years), Mar 2013
- · Ph.D Scholarship award from The University of Newcastle, Australia, Jul 2012
- · Travel award from Faculty of Engineering, The University Newcastle, Australia, ($1K), Jul 2012
- · Government scholarships for Bachelor and Master degrees, (tuition fee waived)
- · Dean’s award as ranked 1 student (out of 700 Master students), Science and Research University of Tehran, Sep 2010
Dr Rokny received extensive research funding support relative to career stage (total of $3.5M as sole/leading Chief Investigator (CI) and $10.6M as co-CI), demonstrating an impressive upward research career trajectory. These include:
- Australia's Economic Accelerator, (CIA, Dec 2025, $499K).
- UNSW-Mahidol Joint Seed Grant, (CIA, Nov 2025, $20K).
- Australia's Economic Accelerator, (CIB, March 2025, $200K).
- GESA Paediatric Research Grant (CIB, Nov, 2024)
- UNSW GRIP Award (CIA, Nov, 2024)
- UNSW-SJTU Collaborative Research Grant, (CIA, Nov, 2024)
- Trustworthy Digital Society Grant, (CIA, Oct, 2024)
- Garvan Cellular Genomics Futures Institute Award (CIA, Sep, 2024).
- UNSW Scientia Program Fellowship (variation award) (sole CI), ($800K, Sep 2023).
- CCFA LITWIN IBD Pioneers Program Grant (leading CIB), ($400K, Feb 2023)
- Australian National Health and Medical Research Council (NHMRC) IDEAS grant (CIB), ($600K, Dec 2022)
- CSIRO Next-Generation Graduate Program (leading CI), ($1.7M including $700K for my Lab, Nov 2022)
- GROW Funding (CIA), a competitive internal funding form USNW SYDNEY, Jun 2022, ($40K)
- Tyree Foundation Institute of Health Engineering Catalyst Awards 2021 (sole CI), Nov 2021, ($30K)
- Australian Research Council Discovery Early Career Researcher Award (DECRA 2022 – sole CI), ($462K)
- The Minor Research Equipment Grant-in-Aid Program Fund (sole CI), UNSW SYDNEY, July 2021, ($61K)
- GROW Funding (sole CI), a highly competitive internal funding form USNW SYDNEY, Jun 2021, ($20K)
- MERIT award offered for NHMRC Investigator Grant (sole CI), WA Dept of Health, Jun 2020, ($95K), declined because of moving to UNSW
- UNSW Cellular Genomics Futures Institute grant (CIB), in collab with Garvan Institute, May 2020, ($50K)
- UNSW Cellular Genomics Futures Institute grant (CIC), in collab with UNSW BABS, May 2020, ($50K)
- Highly competitive tenure-track UNSW Scientia Fellowship Program (sole CI), UNSW, Oct 2019, ($680k)
- Academic Start-up Funding (sole CI), Faculty of Engineering, UNSW, Dec 2019, ($90K)
- Highly competitive International Quebec Autism Research Training Fellowship (sole CI), collab with U of Montreal, Nov 2019, ($120K)
- Highly prestigious Int. Fellowship Fonds de recherche du Québec Santé (FRQS) (sole CI), Oct 2019, ($90K)
- MERIT award for NHMRC Investigator Grant Application (sole CI), WA Dept of Health, Sep 2019, ($50K)
Dr. Rokny has been named on several industry funding in collaboration with Macquarie University), These include:
- Industry research partnership funding (CID), from PORSPA advance company, 750K for my Lab, May 2024, ($4.7M).
- Industry research partnership funding (CID), Australian Digital Domains Group, 600K for my Lab, Nov 2022, ($3.6M).
- Industry research partnership funding (CIE), from Australian digital companies Truuth/Locii, May 2022, ($3.2M).
- Industry research partnership funding (CIC), from PORSPA advance company, May 2021, ($2.1M).