Dr Hamid Alinejad-Rokny
Lecturer

Dr Hamid Alinejad-Rokny

  • Bachelor: Software Engineering, 2004-2009
  • Master: Artificial Intelligence, 2009-2011.
  • Industry: Data Scientist, 2011-2014.
  • Ph.D: Machine Learning and Computational Biology, UNSW Australia, 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.  He is now Head of BioMedical Machine Learning Lab (BML), at the UNSW Graduate School of Biomedical Engineering. He is also Heath Data Analytics Program Leader of AI-enabled Processes (AIP) Research Centre. 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, Dec 2017.
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 42publications; he has been able to secure several national and international grants/fellowships. He has received 28 prizes, honours, awards and also was able to secure multiple national and international awards and grants (totally $3.98M as CI) including highly competitive tenure-track UNSW Scientia Program Fellowship, Australian Research Council Discovery Early Career Researcher Award (DECRA 2022), two NHMRC MERIT awards, two international awards for my 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
BioMedical Machine Learning Lab (BML), Graduate School of Biomedical Engineering, Level 1, Room 1002, Biological Sciences Building (E26)
  • 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, Springer International Publishing, pp. 384 - 389, http://dx.doi.org/10.1007/978-3-030-78270-2_68
  • 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, vol. 12, pp. 2420, 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, vol. 127, pp. 102781, http://dx.doi.org/10.1016/j.jaut.2021.102781
    Journal articles | 2022
    Alinejad-Rokny H; Ghavami Modegh R; Rabiee HR; Ramezani Sarbandi E; 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 Comput Biol, vol. 18, pp. e1010241, http://dx.doi.org/10.1371/journal.pcbi.1010241
    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, vol. 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, vol. 12, http://dx.doi.org/10.1038/s41598-022-11173-0
    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; FANTOM consortium ; Chatelain C; Carninci P; de Hoon MJL; Wasserman WW; Bréhélin L; Lecellier C-H, 2022, 'Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.', Nat Commun, vol. 13, pp. 1200, http://dx.doi.org/10.1038/s41467-022-28758-y
    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; 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, vol. 146, pp. 105426, http://dx.doi.org/10.1016/j.compbiomed.2022.105426
    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, vol. 19, pp. 2381 - 2402, http://dx.doi.org/10.3934/MBE.2022110
    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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 12, pp. 1 - 9, http://dx.doi.org/10.3390/genes12020186
    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, vol. 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, vol. 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, vol. 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 & Fuzzy Systems, vol. 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, vol. 10, pp. 1286, 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, vol. 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, vol. 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), vol. 10, pp. 1891 - 1891, 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 4, pp. 20 - 20, http://dx.doi.org/10.1038/s41540-018-0056-1
    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, vol. 4, pp. 49 - 53, http://dx.doi.org/10.1166/jnsne.2017.1114
    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, vol. 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, vol. 9, pp. 36 - 45, http://dx.doi.org/10.1166/asem.2017.1959
    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, vol. 9, pp. 617 - 617, http://dx.doi.org/10.1166/asem.2017.2063
    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, vol. 6, pp. 416 - 424, http://dx.doi.org/10.1166/jmihi.2016.1707
    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, vol. 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, vol. 6, pp. 1202 - 1208, http://dx.doi.org/10.1166/jmihi.2016.1977
    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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 1, pp. 19 - 25, http://dx.doi.org/10.12785/ijlms/010103
    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, vol. 7, pp. 673 - 678, http://dx.doi.org/10.1166/jbns.2013.1162
    Journal articles | 2013
    Parvin H; Minaei-Bidgoli B; Alinejad-Rokny H; Punch WF, 2013, 'Data weighing mechanisms for clustering ensembles', Computers and Electrical Engineering, vol. 39, pp. 1433 - 1450, http://dx.doi.org/10.1016/j.compeleceng.2013.02.004
    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, vol. 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, vol. 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, vol. 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, vol. 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, vol. 5, pp. 1153 - 1163
    Journal articles |
    Rezaie N; Bayati M; Tahaei MS; Hamidi M; Khorasani S; Lovell NH; Breen J; Rabiee HR; Alinejad-Rokny H, '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
  • 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, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000361966000094&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Preprints |
    Alinejad-Rokny H; Heng JIT; Forrest ARR, 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 |
    Alinejad-Rokny H; Modegh RG; Rabiee HR; Rezaie N; Tam KT; Forrest ARR, 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 |
    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
    Preprints |
    Asgari Y; Heng JIT; Lovell N; Forrest ARR; Alinejad-Rokny H, 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 |
    Band S; Ardabili S; Yarahmadi A; Pahlevanzadeh B; Kausar Kiani A; Beheshti A; Alinejad Rokny H; Dehzangi I; Mosavi A, Machine Learning and Internet of Medical Things for Handling COVID-19: Meta-Analysis, http://dx.doi.org/10.20944/preprints202202.0083.v1
    Preprints |
    Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest A; Alinejad-Rokny H, 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
    Preprints |
    Dashti H; Dehzangi A; Bayati M; Breen J; Lovell N; Ebrahimi D; Rabiee HR; Alinejad-Rokny H, Integrative analysis of mutated genes and mutational processes reveals seven colorectal cancer subtypes, http://dx.doi.org/10.1101/2020.05.18.101022
    Preprints |
    Debnath T; Reza MM; Rahman A; Band S; Alinejad Rokny H, 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 |
    Hamidi H; Alinejad-Rokny H; Coorens T; Sanghvi R; Lindsay SJ; Rahbari R; Ebrahimi D, Signatures of Mutational Processes in Human DNA Evolution, http://dx.doi.org/10.1101/2021.01.09.426041
    Preprints |
    Islam Khan MS; Rahman A; Karim MR; Bithi NI; Band SS; Dehzangi A; Alinejad-Rokny H, 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 |
    Kazemi A; Ghareyazi A; Hamidieh K; Dashti H; Tahaei M; Rabiee H; Alinejad Rokny H; Dehzangi A, 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 |
    Kazemi A; Hamidieh K; Dashti H; Ghareyazi A; Tahaei MS; Rabiee HR; Alinejad-Rokny H; Dehzangi I, 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
    Preprints |
    Liu N; Low WY; Alinejad-Rokny H; Pederson S; Sadlon T; Barry S; Breen J, Seeing the forest through the trees: Identifying functional interactions from Hi-C, http://dx.doi.org/10.1101/2020.11.29.402420
    Preprints |
    Rahman MM; Kamal Nasir M; A-Alam N; Islam Khan S; Band S; Dehzangi I; Beheshti A; Alinejad Rokny H, Hybrid Feature Fusion and Machine Learning Approaches for Melanoma Skin Cancer Detection, http://dx.doi.org/10.20944/preprints202201.0258.v1
    Preprints |
    Sharifonnasabi F; Jhanjhi N; John J; Obeidy P; Shamshirband S; Alinejad Rokny H, Hybrid HCNN-KNN Transfer Learning Model Enhances Age Estimation Accuracy in Orthopantomography, http://dx.doi.org/10.20944/preprints202108.0413.v2
    Preprints |
    Sharifrazi D; Alizadehsani R; Hassannataj Joloudari J; Shamshirband S; Hussain S; Alizadeh Sani Z; Hasanzadeh F; Shoaibi A; Dehzangi A; Alinejad-Rokny H, CNN-KCL: Automatic Myocarditis Diagnosis using Convolutional Neural Network Combined with K-means Clustering, http://dx.doi.org/10.20944/preprints202007.0650.v1

Dr Rokny received extensive research funding support relative to career stage (totally 3.98M as CI) in grant, demonstrating an impressive upward research career trajectory. These include:
•    Australian Research Council Discovery Early Career Researcher Award (DECRA 2022 - CIA), Aug 2021, ($462K)
•    The Minor Research Equipment Grant-in-Aid Program Fund (CIA), UNSW SYDNEY, July 2021, (61K) 
•    Research partnership funding CI-C), from PORSPA advance company, May 2021, ($2.1M)
•    GROW Funding, a highly competitive internal funding form USNW SYDNEY, Jun 2021, ($20K)
•    MERIT award offered for NHMRC Investigator Grant (CI-A), WA Dept of Health, Jun 2020, ($95K), declined because of moving to UNSW.
•    NSW Cancer Council (CI-B), in collab with Lowy Cancer Research Centre, Apr 2020, ($100K)
•    UNSW Cellular Genomics Futures Institute grant (CI-D), in collab with Garvan Institute, May 2020, ($50K)
•    UNSW Cellular Genomics Futures Institute grant (CI-B), in collab with UNSW BABS, May 2020, ($50K)
•    Highly competitive tenure-track UNSW Scientia Fellowship Program (CI-A), UNSW, Oct 2019, ($680k)
•    Academic Start-up Funding (ASUF), Faculty of Engineering, UNSW, Dec 2019, ($90K)
•    Highly competitive International Quebec Autism Research Training Fellowship (CI-A), collab with U of Montreal, Nov 2019, ($120K)
•    Highly prestigious Int. Fellowship Fonds de recherche du Québec (CI-A), Santé (FRQS), Oct 2019, ($90K)
•    MERIT award for NHMRC Investigator Grant Application (CI-A), 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:
•    Honorary Lecturer Fellow, University of Macquarie, Oct 2020-current
•    Awarded Travel grant from Institute for Res. in Fundamental Sciences, Iran, invited speaker, ($1.9K), Feb 2020
•    Health Data Analytics Program Leader, AI-enabled Processes (AIP) Research Centre, Dec 2019-curent
•    Awarded MBSJ2019 (42nd Annual Meeting of the Molecular Biology) Travel Award, Japan, ($0.8K), Dec 2019
•    Prize RIKEN-HUGO award for best oral presentation in Human Genome Meeting (HUGO) 2019, South Korea, ($0.2K), Oct 2019
•    Awarded highly competitive tenure-track UNSW Scientia Fellowship Program in Aug 2019 ($680K)
•    Offered, Vice-chancellor fellowship grant from RMIT Australia, ($350K for 3 years), May 2019 (declined in favour of UNSW Scientia Program).
•    Awarded HDR conference support grant from UNSW Sydney, ($3K), Jul 2015
•    Awarded Travel grant from University of Tehran as invited speaker, Tehran, ($2), 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 from the University of Newcastle, Australia, Jul 2012
•    Travel award from Faculty of Engineering, The University Newcastle, Australia, ($1K), Jul 2012
•    Awarded Government scholarship for Bachelor and Master degrees, (tuition fee waived)
•    Dean’s award, for being Top Student during Master’s degree, Science and Research University of Tehran, 2010
•    Honour, Ranked 1 (of 700) with the overall GPA (19.31/20) in Master’s degree (Top Student), 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 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 

Biomedical Informatics (BIOM9540)