Welcome to our video interview series, where we spotlight TILOS faculty and graduate students, as well as conversations with visiting researchers from Industry. In these candid conversations, you'll hear firsthand about their innovative research, they challenges they face, and the journeys that led them toward careers in AI and optimization research.

Machine Learning, Fairness and AI: A Conversation with Adam Kalai

OpenAI researcher Adam Kalai sits down with TILOS Foundations team member Mikhail (Misha) Belkin to discuss his work in machine learning, algorithmic fairness, and artificial intelligence. Kalai has contributed research in areas like fairness in AI models, word embeddings, and human-AI collaboration. He has worked at Microsoft Research and has published influential papers on bias in machine learning models. His work has helped shape discussions on ethical AI and the development of more equitable AI systems.

Building Fast and Reliable Machine Learning Systems with Yian Ma

TILOS Foundations team member Yian Ma talks about his research using scalable inference methods for credible machine learning. This involves designing Bayesian inference methods to quantify uncertainty in the predictions of complex models; understanding computational and statistical guarantees of inference algorithms; and leveraging these scalable algorithms to learn from time series data and perform sequential decision making tasks.

Machine Learning and Mathematics with Tristan Brugère

Tristan Brugère, a Ph.D. student in the Halıcıoğlu Data Science Institute at UC San Diego, discusses his research at The Institute for Learning-enabled Optimization at Scale. Specifically, how he is working on optimal transport and neural networks on graph generative models with applications to chip design.

Using AI to Build Better Wireless Networks with Tara Javidi

TILOS Neworks team member Tara Javidi, an Electrical and Computer Engineering professor at UC San Diego's Jacobs School of Engineering, discusses her research in artificial intelligence and large-scale wireless networks.