Varun Sharma is a computational systems biologist and AI researcher pursuing his PhD jointly in the groups of Christoph Bock and Jörg Menche at the Research Center for Molecular Medicine of the Austrian Academy of Sciences (CeMM) and the Ludwig Boltzmann Institute of Network Medicine. He received his B.A. degree from Williams College in Molecular Biology and his MSc in Systems Biology in Ruedi Aebersold’s lab from ETH Zürich. Before his PhD, he worked on AI-driven drug discovery at Relay Therapeutics and Dewpoint Therapeutics in Cambridge, Massachusetts, and subsequently developed deep metric learning approaches for phenotypic drug discovery in Michael Keiser's lab at UCSF. His research focuses on understanding the principles governing multiscale biological self-organization, particularly how collective cellular systems acquire, maintain, and regenerate complex structures. Combining approaches from systems biology, AI, Artificial Life, representation learning, and dynamical systems theory, he investigates how hierarchical organization and interactions across biological scales shape emergent behavior, robustness, and adaptability. More broadly, he is interested in the relationship between biological self-organization, collective intelligence, and the capacity of living systems to construct and maintain internal models of themselves and their environments. Drawing on ideas from active inference, autopoiesis, and theoretical biology, his long-term goal is to identify and incorporate the underlying symmetries and organizational principles of biological collective intelligence into artificial systems. He hopes these insights will enable unconventional therapeutic strategies, accelerate more traditional drug and mechanism discovery, and inform approaches to AI safety and alignment by identifying principles for designing AI and Artificial Life systems whose objectives are compatible with the flourishing of humanity and the broader biosphere.