Hamid Alinejad-Rokny

Dr Rokny (PhD, UNSW Sydney, 2019) is the Director of UNSW BioMedical Machine Learning Laboratory (BML), where he leads a team of 25 researchers developing trustworthy artificial intelligence for biology and medicine, spanning medical artificial intelligence, large language models, and bio-machine learning. He supervises a dynamic team of researchers and have successfully led over 60 projects, resulting in 100 high-quality publications in top-tier journals such as Nature Communications, Nature Neuroscience, The Lancet, Cell reports, PLOS Computational Biology, Blood, and A* conferences such as ICLR, NeurIPS, AAAI, and ACL, often as the first or senior author. The impact of my work is evident through a high citation rate [5,900+, h-index 40 Google Scholar] and a high FWCI score (AI= 7.6; Neuroscience= 4.7; Health Informatics= 4.75), which is outstanding considering the career stage. The impact of his leadership is also evidenced by securing significant grants, including a DECRA fellowship, UNSW Scientia fellowship, an NHMRC Ideas grant, and a CSIRO NGGP grant, as well as multiple awards such as Google fellowship, Tour de Cure and MSA fellowships for students under his leadership. Additionally, he actively enhance medical AI and machine learning literacy by collaborating with clinicians and health professionals across Sydney hospitals, including the Gene2Care and PreGen consortia, and NSW Health clinics, demonstrating the practical applications of AI to improve health outcomes. As the Health Theme Leader of the UNSW Data Science Hub, He sets health data science priorities, integrating research with practical health solutions. His organisational skills have led me to orchestrate over 100 seminars on AI in medicine, promoting knowledge sharing and collaboration. Furthermore, He contributes to research direction through roles on panels like NSF-CSIRO influencing funding towards innovative AI and genomics project and HUGO meeting. His commitment to training the next generation is showcased through his leadership in CSIRO’s NGGP, collaborating with industry partners like 23Strands to enhance the capabilities of emerging AI researchers in medical technologies. Notably, He is currently leading several national-level initiatives focused on developing foundation models in AI for Biology and Medicine (ClinAI, OmniST, ARGOS, and Molecular AI). These initiatives represent a significant step forward at the national level and aim to position Australia at the forefront of these emerging GPT-like technologies for individualised medicine. machine learning, genomics, neurodevelopmental disorder, big data analytics, data mining, artificial neural network (ann), clustering, noncoding rna, gene regulation, gene regulatory networks, regulatory mutations, genomic mutations, dna copy number variations, gene expression, bioinformatics, computational biology, chromosome aberrations, chromosome disorders, biomedical engineering, image processing, medical image processing, deep learning