The IIST Colloquium Series is a regular forum that brings together students, faculty, and staff from different academic and research backgrounds. It features talks by leading researchers from India and abroad on a wide range of topics, including science, engineering, space science, and interdisciplinary fields. Unlike departmental seminars, these talks are meant to be broadly accessible and of general interest. The series encourages interaction with visiting experts, promotes the exchange of new ideas, and inspires future collaborations.
Recent / Upcoming Colloquium
Colloquium on Artificial Intelligence in Drug Discovery: Bridging High-Content Screening to Target Discovery
- 29-10-2025
- 15:30
About the Speaker - Arvind Rao is a Professor in the Department of Computational Medicine and Bioinformatics at the University of Michigan. His group uses im-age analysis and machine learning methods to link image-derived phenotypes with genetic da-ta, across biological scale (i.e. single cell, tissue and radiology data). Such methods have found application in radiogenomics, drug repurposing based on phenotypic screens and spatial profil-ing in tissue, as well as in spatial transcriptom-ics. Arvind received his PhD in Electrical Engi-neering and Bioinformatics from the University of Michigan, specializing in transcriptional ge-nomics, and was a Lane Postdoctoral Fellow at Carnegie Mellon University, specializing in bi-oimage informatics. He is also a Fellow of Amer-ican Medical Informatics Association (AMIA), The Royal College of Pathology (RCPath) in the UK (by published works) and American Associa-tion for Advancement in Science (AAAS).
Abstract - The emergence of artificial intelligence (AI) is revolutionizing how we approach drug discovery, offering powerful tools that complement traditional laboratory methods through the discovery of driving biological mechanisms. This talk aims to demystify AI applications in life sciences, focusing on two transformative areas: image-based high-content screening and target discovery via deconvolving biological mechanisms of disease. Through real-world examples, we'll explore how AI transforms microscopy data into actionable insights, enabling researchers to analyze complex cellular phenotypes at unprecedented scale and speed. We'll examine how these same AI tools connect with target discovery platforms, creating a seamless pipeline from initial screening to target validation.
Designed specifically for life scientists without requiring computational background, this presentation will illuminate the practical benefits of AI tools in daily research workflows. We'll discuss how AI assists in analyzing vast libraries of compound effects on cells, identifying subtle patterns in biological responses, and prioritizing promising therapeutic targets. By the end of this talk, attendees will gain a clear understanding of AI's role in modern drug discovery, learning how these tools can enhance their research without requiring expertise in programming or machine learning.
