Dr Hamid Alinejad-Rokny
Lecturer

Dr Hamid Alinejad-Rokny

  • Bachelor: Software Engineering, 2004-2009
  • Master: Artificial Intelligence, 2009-2012.
  • Industry: Data Scientist, 2012-2014.
  • Ph.D: Machine Learning and Computational Biology, UNSW Sydney, 2014-2018.
  • Post-Doctoral: Harry Perkins Institute of Medical Research, UWA Australia, 2017-2019.
Engineering
Grad Sch: Biomedical Eng

Dr Rokny joined UNSW on a highly prestigious and competitive UNSW Scientia Program (UNSW Scientia Program aims to attract the best and brightest scientists with outstanding research records in October 2019. Dr Rokny is currently acting as a Scientia Senior Lecturer at UNSW Sydney and adj Associate Professor at Concordia University. He is leading UNSW BioMedical Machine Learning Laboratory (BML) at the UNSW Graduate School of Biomedical Engineering (GSBmE), where he is mentoring a team of 1 post-doc, 2 research assistants, 5 PhDs, 3 Masters, 2 Hons as well as 8 researchers in overseas universities as co-supervisor/mentor. He is also the Heath Data theme Leader of UNSW Data Science Hub. Dr Rokny received his master degree in Artificial Intelligence/Machine Learning (Ranked 1st) and his Ph.D in Systems Biology and Machine Learning from UNSW Australia, Jan 2018.
His research focuses on using cutting-edge Systems Biology and Advanced Health Data Analytics techniques in conjunction with genome-wide data to understand the impact of genomic variants on genetic diseases and disorders. Dr Rokny is currently leading multiple international projects (jointly with UWA, Uni Adelaide, SUT, and Texas Biomed) investigating the impacts of non-coding regulatory variants in genetic diseases (in particular neurodevelopmental disorders and breast cancer) through integration of Hi-C, ChIP-seq, RNA-seq, and genomic variants. He is keen to see accurate diagnostic genomic tools implemented into the clinic to improve the health care and genomic-based treatments in the Australian health system.
As a young and early career scientist, Dr Rokny has published 65 publications, including 10 as first & 35 as senior author. He has also been able to secure several national and international grants/fellowships. Throughput his career, he has received 28 prizes, honours, awards and also was able to secure multiple national and international awards and grants (totally $13.2M as Chief Investigator (CI) including highly competitive tenure-track UNSW Scientia Program Fellowship, CSIRO Next-Generation Graduate Program (leading CI), Australian National Health and Medical Research Council (NHMRC) IDEAS grant, Australian Research Council Discovery Early Career Researcher Award (DECRA 2022), two NHMRC MERIT awards, two international awards for his work on Autism from the International Quebec Autism Research Training (QART) program and the International Fellowship Fonds de recherche du Québec - Santé (FRQS), two awards from UNSW Cellular Genomics Futures Institute, four external and one internal travel grants to present my research at national and international conferences and workshops. He has also received the best presentation prize in prestigious international conference Human Genome Meeting (HUGO) 2019. Dr Rokny also awarded highly competitive international PhD scholarship from UNSW. Additionally, He has been invited to serve as Keynote Speaker and program committee members of national and international conferences including prestigious International HUGO 2020 (HUGO ECR symposium organization team), Pasteur Institute (invited talk), Harry Perkins Institute of Medical Research.

Phone
+61 2 9385 1725
Location
UNSW BioMedical Machine Learning Lab (BML), Graduate School of Biomedical Engineering, Level 1, Room 1002, Biological Sciences Building (E26)
  • Book Chapters | 2022
    Shabani N; Beheshti A; Farhood H; Bower M; Garrett M; Rokny HA, 2022, 'iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data', in Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, Springer International Publishing, pp. 352 - 356, http://dx.doi.org/10.1007/978-3-031-11647-6_68
    Book Chapters | 2021
    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
  • Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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', 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2023
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2022
    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, http://dx.doi.org/10.1038/s41598-022-06046-5
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2022
    Razzak I; Naz S; Alinejad-Rokny H; Nguyen TN; Khalifa F, 2022, '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, http://dx.doi.org/10.1109/TCBB.2022.3219032
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2022
    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', BLOOD, 140, http://dx.doi.org/10.1182/blood-2022-165713
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2021
    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
    Journal articles | 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
    Journal articles | 2021
    Rezaie N; Bayati M; Tahaei MS; Hamidi M; Khorasani S; Lovell NH; Breen J; Rabiee HR; 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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, http://dx.doi.org/10.1038/s41598-020-58107-2
    Journal articles | 2020
    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
    Journal articles | 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, http://dx.doi.org/10.1186/s12864-020-6636-7
    Journal articles | 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, http://dx.doi.org/10.3390/app10051891
    Journal articles | 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, http://dx.doi.org/10.1016/j.compeleceng.2020.106656
    Journal articles | 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
    Journal articles | 2019
    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, http://dx.doi.org/10.1002/mgg3.507
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2018
    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
    Journal articles | 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
    Journal articles | 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, 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2016
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2015
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2014
    Ebrahimi D; Alinejad-Rokny H; Davenport MP, 2014, 'Insights into the motif preference of APOBEC3 enzymes', PLoS ONE, 9, http://dx.doi.org/10.1371/journal.pone.0087679
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2014
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2013
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 2012
    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
    Journal articles | 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
    Journal articles | 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
    Journal articles | 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
  • Preprints | 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
    Conference Papers | 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
    Conference Papers | 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
    Preprints | 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
    Preprints | 2023
    Karami M; Alizadehsani R; Khadijeh ; Jahanian ; Argha A; Dehzangi I; Alinejad-Rokny H, 2023, Revolutionizing Genomics with Reinforcement Learning Techniques, , http://dx.doi.org/10.48550/arxiv.2302.13268
    Conference Papers | 2023
    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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Conference Papers | 2022
    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
    Preprints | 2022
    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
    Preprints | 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
    Preprints | 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
    Conference Papers | 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
    Preprints | 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
    Preprints | 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://dx.doi.org/10.48550/arxiv.2210.04453
    Preprints | 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
    Preprints | 2022
    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
    Preprints | 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
    Conference Papers | 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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Preprints | 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
    Preprints | 2021
    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
    Preprints | 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
    Preprints | 2020
    Asgari Y; Heng JIT; Lovell N; Forrest ARR; 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
    Preprints | 2020
    Dashti H; Dehzangi A; Bayati M; Breen J; Lovell N; Ebrahimi D; Rabiee HR; 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
    Preprints | 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
    Preprints | 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
    Preprints | 2019
    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
    Preprints | 2018
    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
    Conference Abstracts | 2015
    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 |
    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

Dr Rokny received extensive research funding support relative to career stage (total of $2.75M as sole/leading Chief Investigator (CI) and $10.6M as co-CI), demonstrating an impressive upward research career trajectory. These include:

  • 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)
  • Industry research partnership funding (CID), Australian Digital Domains Group, Nov 2022, ($3.6M)
  • GROW Funding (CIA), a competitive internal funding form USNW SYDNEY, Jun 2022, ($40K)
  • Industry research partnership funding (CIE), from Australian digital companies Truuth/Locii, May 2022, ($3.2M)
  • 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)
  • Industry research partnership funding (CIC), from PORSPA advance company, May 2021, ($2.1M)
  • 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
  • NSW Cancer Council (CIB), in collab with Lowy Cancer Research Centre, Apr 2020, ($100K)
  • 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)

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:

  • ·     Adjunct Research Scientist, CSIRO, Aug 2022-present
  • ·     Honorary Lecturer Fellow, University of Macquarie, Oct 2020-current
  • ·     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’s research focuses on using cutting-edge systems biology and advanced health data analytics techniques in conjunction with genome-wide data to understand the impact of genomic variants on genetic diseases and disorders. He is also interested to develop novel machine learning techniques, in particular, deep convolutional neural network, clustering, clustering, classification, feature selection, and evolutionary algorithms.
Dr Rokny has extensive experience in the analysis of next generation sequencing (NGS) data from different platforms (Roche, SOLiD, Illumina, and Helicos) and protocols (Hi-C, Structural variants, Single point mutations, GWAS, RNA-seq, CAGE, small RNA, ChIP-seq, and Single-cell). The move to UNSW Biomedical Engineering school has allowed him to translate his engineering and medical research on mammalian systems onto clinically relevant questions such as identification of novel biomarkers, drug targets.

Dr. Rokny is currently looking for Research Associate/Assistant, Ph.D/Master/Honours students to join his BML Lab. The research projects will mainly focus on using cutting-edge Medical Artificial Intelligence, Systems Biology and Advanced Health Data Analytics techniques in conjunction with genome-wide data to understand biological and medical related problems.

There are several scholarships available for both international and domestic students. Please see the following links for more information:

  • Key-dates: https://research.unsw.edu.au/key-dates
  • UNSW Post-Graduate Research Scholarship for international students,
  • UNSW Post-Graduate Research Scholarship for domestic students
  • Australia awards and endeavour scholarships and fellowships
  • Determine your eligibility for a scholarship: https://selfassessment.research.unsw.edu.au/
  • Meet English requirement: https://www.unsw.edu.au/english-requirements-policy 

My Research Supervision

PhD & MPhil Students:

  • Coco Xiaoge Huang, PhD student, 2024-2028, (administered by UNSW), co-supervision with Dr Fatemeh Vafaee and Mr Mark Grosser (23Strands company).
  • Rebecca Browne, PhD student, 2024-2028, (administered by UNSW), co-supervision with Prof Nigel Lovell and Dr Reza Argha.
  • Tohid Ghasemnejad, PhD student, 2023-2027, (administered by UNSW), co-supervision with Drs Fabrizzio Horta, Faezeh Marzbanrad, and Mr Mark Grosser (23Strands compnay).
  • Roxana Zahedi Nasab, PhD student, 2023-2027, (administered by UNSW), co-supervision with Prof Nigel Lovell, Dr Reza Argha, and Dr Mo Lotfollahi.
  • Ivan Bakhshayeshi, PhD student, 2023-2027, (administered by UNSW), co-supervision with Prof Nigel Lovell and Dr Reza Argha.
  • Mona (Sedigheh) Abedini, 2023-2027, (administered by UNSW), co-supervision with Dr Fatemeh Vafaee and A/Prof Orazio Vittorio.
  • Md. Mushahidul Islam Shamim, Master by Research (MPhil), 2023-2026, (administered by UNSW), co-supervision with A/Prof Nadeem Kaakoush.
  • Yuheng Liang, Master by Research (MPhil), 2023-2026, (administered by UNSW), co-supervision with Prof Nigel Lovell.
  • Reza Ghamsari, PhD student, 2022-2026, (administered by UNSW).
  • Mehran Piran, PhD student, 2020-2024, (administered by Monash University), co-supervision with Dr Alex Combes.
  • Ali Afrasiabi, PhD student, 2020-2024, (administered by UNSW).
  • Afshar Shamsi, PhD student, 2023-2027, (administered by Concordia University), co-supervision with Assoc Prof Arash Mohammadi.
  • Mahdieh Labani, PhD student, 2021-2025, (administered by Macquarie University), co-supervision with Prof Amin Beheshti.
  • Sunday Offor, PhD student, 2019-2023, (administered by UNSW), co-supervision with Assoc Prof Irina Voineagu.
  • Ted Wong, PhD student, 2019-2025, (administered by University of Sydney), co-supervision with Dr. Boris Guennewig.
  • Callum Macphillamy, PhD student, 2020-2024, (administered by University of Adelaide), co-supervision with Dr Wai Yee Low.
  • Ning Liu, PhD student, 2019-2023, (administered by University of Adelaide), co-supervision with Dr James Breen.
  • Zahra Rahaei, PhD student, 2018-2023, (administered by SUT).

 

Master Students:

  • Rejisa Becirovic, Master student, 2024-2025, (administered by UNSW).
  • Gabrielle Younes, Master student, 2023-2024, (administered by UNSW).
  • Sally Chen, Master student, 2023-2024, (administered by UNSW).
  • Michael De Francesco, Master student, 2023-2024, (administered by UNSW).
  • Aryan Bhatla, Master student, 2023-2024, (administered by UNSW).
  • Ivy Lan Liu, Master student, 2022-2023, (administered by UNSW).
  • Aravind Venkateswaran, Master student, 2022-2023, (administered by UNSW).
  • Sascha Graham, Master student, 2022-2023, (administered by UNSW).
  • Weilin Wu, Master student, 2021-2022, (administered by UNSW).
  • Anthony Xu, Master student, 2021-2022, (administered by UNSW).
  • Yuheng Liang, Master student, 2021-2022, (administered by UNSW).

​​​​​​​

Previous supervision and mentoring:

  • Hanwen Liang, MS student, 2019-2020, (administered by UNSW).
  • Rasaa Ghavami, Master student, 2017-2019. Scholarship awarded for PhD degree from SUT.
  • Narges Rezaei, Honours student, 2018-2019. Scholarship awarded for Ph.D Degree from University of California, US.
  • Masroor Bayati, Honours student, 2017-2018. Scholarship awarded for Ph.D Degree from University of Toronto.
  • Hamed Dashti, Honours student, 2016-2018. Scholarship awarded for Master Degree from University of Zurich.
  • Mahshid Khatami, Master student, 2018-2020, (administered by SUT).
  • Fariba Raoufi, Master student, 2016-2017.

My Teaching

Biomedical Informatics (BIOM9540)

Biomedical Engineering (BIOM4951, BIOM4952, BIOM4953)