Prof. Geoffrey E. Hinton, Turing award winner (2018) for his foundational research that led to the formation of deep learning. Geoffrey Hinton is known by many to be the godfather of deep learning. Aside from his seminal 1986 paper on backpropagation, Hinton has invented several foundational deep learning techniques throughout his decades-long career. Hinton currently splits his time between the University of Toronto and Google Brain.

Dr. Diederik P. Kingma who played key role in developing the "adam" optimizer (de facto standard for training deep neural nets currently) and the Variational Autoencoders.

Prof. Gérard Biau is a full professor at the Probability, Statistics, and Modeling Laboratory (LPSM) of Sorbonne University, Paris. In 2018, he was awarded the Michel Monpetit - Inria prize by the French Academy of Sciences. He is currently director of Sorbonne Center for Artificial Intelligence (SCAI).

Prof. Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He led the developments of Laplacian Eigenmaps, Graph and Manifold Regularizers, and Spectral Clustering. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Prof. Laurens Van Der Maaten is a Research Scientist at Facebook AI Research (FAIR) in New York. He is the author of the most used dimensionality reduction technique 't-SNE'.

Prof. Leman Akoglu is the Heinz College Dean's Associate Professor of Information Systems at Carnegie Mellon University. Dr. Akoglu’s research interests broadly span machine learning and data mining, and specifically graph mining, pattern discovery and anomaly detection, with applications to fraud and event detection in diverse real-world domains.

Dr. Timnit Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR). She received her PhD from Stanford University, and did a postdoc at Microsoft Research, New York City in the FATE (Fairness Accountability Transparency and Ethics in AI) group, where she studied algorithmic bias and the ethical implications underlying projects aiming to gain insights from data.

Dr. Thomas Kipf is a senior research scientist at Google Brain. He obtained his PhD at the University of Amsterdam working with Max Welling. For his PhD thesis on Deep Learning with Graph-Structured Representations he received the ELLIS PhD Award 2021.