Invited Speakers
Koustuv Saha
Koustuv Saha is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign, where he leads the OnCARE (Online and Connected AI Reflections) lab. His research lies at the intersection of computational social science, social computing, human-centered machine learning, and fairness, accountability, transparency, and ethics (FATE) in AI.
His work focuses on understanding human behavior and wellbeing through social media and online data, combined with multimodal sensing approaches. By integrating perspectives from psychology and social science, his research contributes to theoretical, practical, design, and ethical discussions relevant to researchers, practitioners, and policymakers.
A significant part of his research examines wellbeing in situated contexts such as college campuses and workplaces. He investigates the real-world utility and ecological validity of wellbeing sensing technologies, while critically assessing their assumptions and potential risks. This work aims to inform the responsible design, development, and deployment of such technologies.
Previously, he was a Senior Researcher at Microsoft Research Montréal in the FATE group. He received his Ph.D. in Computer Science from Georgia Tech and his B.Tech in Computer Science and Engineering from IIT Kharagpur, and brings additional industry research experience from his pre-PhD career.
Kristina Lerman
Social Media and Mental Health: An Evolutionary Mismatch
Abstract
The widespread adoption of social media has coincided with growing mental health concerns, including rising anxiety, depression, and body image disturbances among youth. This talk argues that these outcomes stem from a mismatch between the technological affordances of social media and brains evolved for small-scale social life.
Psychological processes that helped humans navigate ancestral environments — such as status seeking, social comparison, and self-evaluation — become harmful when made global, continuous, and quantified. Planetary-scale connectivity exposes users to highly curated realities that distort social norms, while quantified feedback mechanisms (likes, views, shares) transform online interaction into persistent status competition. The ubiquity of phone cameras further encourages self-objectification and continuous performance before an “imaginary audience.”
The talk will also discuss how algorithmic recommendation systems amplify these dynamics by prioritizing emotionally engaging and envy-inducing content, particularly during adolescence, when sensitivity to peer evaluation is heightened. These mechanisms will be illustrated through case studies related to body image concerns on social media, including eating disorder–related pathologies among girls and young women centered on the thin ideal, and risky behaviors among boys and young men pursuing muscular body ideals.
Overall, the talk reframes social media harms not primarily as a consequence of time spent online or addictive platform design, but as the result of platform affordances that systematically reshape social cognition and undermine mental health.