Hamid Alinejad-Rokny

UNSW Scientia Lecturer
Senior Lecturer

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 13 researchers 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 Statistical Machine Learning (Ranked 1st) and his Ph.D in Biostatistical Machine Learning from UNSW Australia, Jan 2018.
His research focuses on using cutting-edge statistical machine learning, biostatistics, and Advanced Health Data Analytics techniques in conjunction with health and medical data to understand the mechanisms behind diseases and disorders. 


As a young and early career scientist, Dr Rokny has published 80 publications, including 10 as first & 45 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 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 2023), 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.

Biomedical Informatics (BIOM9540)

Biomedical Engineering (BIOM4951, BIOM4952, BIOM4953)

PUBLICATIONS
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Journal articles
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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
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
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
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
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
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
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
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
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
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
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
MacPhillamy C; Alinejad-Rokny H; Pitchford WS; Low WY, 2022, 'Cross-species enhancer prediction using machine learning', Genomics, 114, pp. 110454, 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, pp. 105426, http://dx.doi.org/10.1016/j.compbiomed.2022.105426
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, pp. e1010241, 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
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
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
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, pp. 869238, http://dx.doi.org/10.3389/fpubh.2022.869238
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
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
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
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
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
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
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
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, pp. 102781, http://dx.doi.org/10.1016/j.jaut.2021.102781
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
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
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
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
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
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
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
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
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
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
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
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
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
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; 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
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
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 - 1891, http://dx.doi.org/10.3390/app10051891
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 & Fuzzy Systems, 38, pp. 4471 - 4483, http://dx.doi.org/10.3233/jifs-191225
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
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, 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; 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
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
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
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
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
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; 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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; 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
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
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
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
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
Preprints
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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, 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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; 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
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
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
Conference Papers
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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
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
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
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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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
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, Springer International Publishing, pp. 384 - 389, http://dx.doi.org/10.1007/978-3-030-78270-2_68
2021
Conference Abstracts
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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

AWARDS
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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 2022-2023
  • ·     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

GRANTS
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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)
  • 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).
Tags
lensArtificial Intelligence
lensOncology
Organisational units
lensChief Investigators