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Alex Zhavoronkov

Founder and CEO, Insilico Medicine

About Alex Zhavoronkov

Alex Zhavoronkov, PhD, is the founder and CEO of Insilico Medicine (insilico.com), a leader in next-generation artificial intelligence technologies for drug discovery, biomarker development, and aging research. At Insilico he pioneered the applications of generative adversarial networks (GANs) and reinforcement learning (RL) for generation of the novel molecular structures and generation of synthetic biological and patient data with the desired properties. He also developed a range of deep multi-modal predictors of biological age using multiple data types. He set up the R&D centers in 6 countries including the US, United Kingdom, Korea, Russia, China, Hong Kong SAR, and Taiwan ROC. Prior to founding Insilico Medicine, he worked in senior roles at ATI Technologies (acquired by AMD in 2006) and NeuroG Neuroinformatics. He is the chief science officer (CSO) of the Biogerontology Research Foundation (BGRF, bg-rf.org.uk), a registered UK charity focusing on age-related diseases. Since 2012 he authored and co-authored over 130 peer-reviewed research papers and 2 books including “The Ageless Generation: How Biomedical Advances Will Transform the Global Economy” (Palgrave Macmillan, 2013). From 2014 to 2018 he presented at over 200 academic and industry conferences. He serves on the editorial boards of Aging, Aging Research Reviews, Trends in Molecular Medicine, Frontiers in Genetics, and chairs the Annual Aging Research, Drug Discovery and AI Forum (6th annual in 2019) at the Basel Life, one of Europe's largest industry events in drug discovery. Dr. Zhavoronkov holds two bachelor degrees from Queen’s University, a master’s in Biotechnology from Johns Hopkins University, and a PhD in Physics and Mathematics from Moscow State University. He is the adjunct professor of artificial intelligence at the Buck Institute for Research on Aging. 

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Biomedical analytics Biomolecular engineering Computational medicine Health informatics Systems biology Computational biology

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