Daniel Tarlow is a research scientist at Google Brain in Montreal and an adjunct professor at McGill University. He completed his Ph.D. at the University of Toronto in 2013 on modeling domains with complex structures. Daniel has worked on Neurosymbolic Programming methods such as DeepCoder and TerpreT, and Structured Prediction.

Judith Fan is an assistant professor at the University of California, San Diego, in the Department of Psychology, leading the Cognitive Tools Lab. She employs converging approaches from cognitive science, computational neuroscience, and artificial intelligence to reverse engineer the human mind. In 2016, she obtained a Ph.D. at Princeton University on the role of cognitive actions in learning.

Guy van den Broeck is an associate professor at the University of California, Los Angeles (UCLA), where he directs the Statistical Relational AI (StarAI) lab. His recent research has focused on Neurosymbolic AI, in particular using Probabilistic Circuits, a collection of tractable models for inference on discrete random variables. Guy obtained his Ph.D. at the KU Leuven on lifted inference for StarAI.

Mathias Niepert is a full professor at the University of Stuttgart, leading the Machine Learning and Simulation Science Lab. He is a faculty member at the Max Planck Research School. His work studies learning on structured data and the intersection of Machine Learning with science. At NEC Labs Europe he was a Chief Research Scientist from 2017-2021 and is now a Chief Scientific Advisor. He obtained his Ph.D. from Indiana University.

Tuan Anh Le is a research scientist at Google. He works on Probabilistic Programming and Generative modeling. Tuan Anh adapted the wake-sleep algorithm to generate computer programs. He was a postdoctoral associate at MIT, working with Josh Tenenbaum. Before that, he obtained his Ph.D. in 2019 at the University of Oxford, where he studied amortized inference for probabilistic programming.