By Dr Hamid Alinejad-Rokny

Conference Papers

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

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

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

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

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

Conference Abstracts

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

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

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

Preprints

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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, 2024, PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation, http://dx.doi.org/10.48550/arxiv.2410.01504

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

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

Chen D; Fang F; Ni S; Liang F; Hu X; Argha A; Alinejad-Rokny H; Yang M; Li C, 2024, Lower Layers Matter: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused, http://dx.doi.org/10.48550/arxiv.2408.08769

Doan BG; Shamsi A; Guo X-Y; Mohammadi A; Alinejad-Rokny H; Sejdinovic D; Teney D; Ranasinghe DC; Abbasnejad E, 2024, Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks, http://dx.doi.org/10.48550/arxiv.2407.20891

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

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

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

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

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

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

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

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

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

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

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, 2022, 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

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

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

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

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

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

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

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

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

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

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