Speakers

Rishabh Joshi is a Senior Research Engineer at Google DeepMind, where he works on aligning large language models using reinforcement learning from human feedback (RLHF) and preference‑based optimization within the Gemini post‑training stack. His research aims to make LLMs more helpful, safe, and aligned with human values. He holds a research master’s in Language Technologies from Carnegie Mellon University, where he worked on neural language generation, interpretable keyphrase extraction, and medical entity linking. He actively shares his work through publications, open‑source projects, and his personal website.

Amit is a senior engineer at Google, where he has been working since July 2015 after graduating from IIT Kharagpur with a dual degree in Computer Science and Engineering. Amit's expertise lies in developing software solutions that protect against advanced persistent threats and cyberattacks, having previously worked at IBM as a NextGen Protection System Designer. In his current role at Google, Amit is responsible for designing and implementing software solutions that meet the company's complex business needs. He is well-versed in a range of programming languages and technologies, including software engineering and testing.

Vedant is pursuing a Ph.D. in Computer Science at Université de Montréal, affiliated with Mila, with Aaron Courville as his advisor. His research interests center on deep learning, reinforcement learning, and cognitive inductive biases in learning systems, aiming at more efficient and generalizable artificial agents. He previously completed a Master’s in Computer Science at Université de Montréal, advised by Anirudh Goyal and Yoshua Bengio. Before that, he gained substantial research experience as a Research Intern at Mila, and as a student researcher collaborating with BITS Pilani and TCS Research on neurosymbolic methods, reinforcement learning frameworks, and deep learning for forecasting and perception tasks.

Ajay is a PhD candidate in Cognition & Perception at New York University (2021–2026), where he explores the intersection of cognitive science and machine learning, focusing on human learning of complex tasks, exploration, planning, and reinforcement learning for robotics. He has conducted research at Meta (Reality Labs) on vision‑language models for embodied AI, at Lawrence Livermore National Laboratory on text‑to‑image diffusion for psychophysics, and previously interned at Harvard University, IIT Madras, and Google Summer of Code. He earned his B.E. in Electronics and Communication Engineering from BITS Pilani, Goa.