Finding what stays true in medical research | Debashis Sahoo | TEDxSanDiegoSalon

Research into reproducibility asks whether stable patterns in biology can make scientific findings more reliable. In this TEDxSanDiegoSalon talk, Debashis Sahoo, an associate professor at UC San Diego, discusses using AI to find invariant biological patterns within the complexity of human biology. He presents the idea that such patterns could point to rules that make medicine more precise and scientific knowledge more trustworthy.

• Using AI to identify invariant patterns in human biology
• Why stable patterns may support more reproducible science
• Possible links to more precise medicine and translational research

What if the key to making science more reproducible is hiding in the patterns that never change? In this talk, Debashis Sahoo explores how AI can help us uncover invariant biological patterns hidden within the enormous complexity of human biology—and how these discoveries could reveal the laws that make science more reliable, medicine more precise, and knowledge more trustworthy. Website: https://sites.google.com/view/debashis-sahoo Twitter/X: @sahoo00 LinkedIn: https://www.linkedin.com/in/sahoodebashis/ Facebook: https://www.facebook.com/debashis.sahoo #ReproducibleScience #AIinBiology #FutureOfMedicine #TEDxSanDiego #TEDx #MooresCancerCenter #Bioinformatics #Boolean Analysis #UCSD #AI Debashis Sahoo is a joint Associate Professor of Computer Science and Engineering and Pediatrics at the University of California, San Diego. He earned his B.Tech. from the Indian Institute of Technology, Kharagpur, and his M.S. and Ph.D. from Stanford University. His research bridges artificial intelligence and biology, developing logical and AI-driven methods to uncover invariant biological rules and predict patient responses. His work has led to advances in cancer and translational research, including the identification of CDX2 as a predictive biomarker in colon cancer (NEJM 2016). He is passionate about working at the intersection of disciplines and fostering collaborations among computational scientists, clinicians, and biologists to address real-world translational challenges. His group focuses on translating AI and logical modeling approaches into clinically actionable diagnostics and therapeutics. https://sites.google.com/view/debashis-sahoo This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx