The Thesis Review

Simon Shaolei Du is an Assistant Professor at the University of Washington. His research focuses on theoretical foundations of deep learning, representation learning, and reinforcement learning. Simon's PhD thesis is titled "Gradient Descent for Non-convex Problems in Modern Machine Learning", which he completed in 2019 at Carnegie Mellon University. We discuss his work related to the theory of gr...

Graham Neubig is an Associate Professor at Carnegie Mellon University. His research focuses on language and its role in human communication, with the goal of breaking down barriers in human-human or human-machine communication through the development of NLP technologies. Graham’s PhD thesis is titled "Unsupervised Learning of Lexical Information for Language Processing Systems", which he completed...

Michela Paganini is a Research Scientist at DeepMind. Her research focuses on investigating ways to compress and scale up neural networks. Michela's PhD thesis is titled "Machine Learning Solutions for High Energy Physics", which she completed in 2019 at Yale University. We discuss her PhD work on deep learning for high energy physics, including jet tagging and fast simulation for the ATLAS experi...

Josef Urban is a Principal Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research focuses on artificial intelligence for large-scale computer-assisted reasoning. Josef's PhD thesis is titled "Exploring and Combining Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics", which he completed in 2004 at Charles University in Prague. We discu...

Dumitru Erhan is a Research Scientist at Google Brain. His research focuses on understanding the world with neural networks. Dumitru's PhD thesis is titled "Understanding Deep Architectures and the Effect of Unsupervised Pretraining", which he completed in 2010 at the University of Montreal. We discuss his work in the thesis on understanding deep networks and unsupervised pretraining, his perspect...

Eero Simoncelli is a Professor of Neural Science, Mathematics, Data Science, and Psychology at New York University. His research focuses on representation and analysis of visual information. Eero's PhD thesis is titled "Distributed Representation & Analysis of Visual Motion", which he completed in 1993 at MIT. We discuss his PhD work which focused on optical flow, which ideas and methods have stay...

Paul Middlebrooks is a neuroscientist and host of the Brain Inspired podcast, which explores the intersection of neuroscience and artificial intelligence. Paul's PhD thesis is titled "Neuronal Correlates of Meta-Cognition in Primate Frontal Cortex", which he completed at the University of Pittsburgh in 2011. We discuss Paul's work on meta-cognition - informally, thinking about thinking - then disc...

Aaron Courville is a Professor at the University of Montreal. His research focuses on the development of deep learning models and methods. Aaron's PhD thesis is titled "A Latent Cause Theory of Classical Conditioning", which he completed at Carnegie Mellon University in 2006. We discuss Aaron's work on the latent cause theory during his PhD, talk about how Aaron moved into machine learning and dee...

Christian Szegedy is a Research Scientist at Google. His research machine learning methods such as the inception architecture, batch normalization and adversarial examples, and he currently investigates machine learning for mathematical reasoning. Christian’s PhD thesis is titled "Some Applications of the Weighted Combinatorial Laplacian" which he completed in 2005 at the University of Bonn. We di...

Been Kim is a Research Scientist at Google Brain. Her research focuses on designing high-performance machine learning methods that make sense to humans. Been's PhD thesis is titled "Interactive and Interpretable Machine Learning Models for Human Machine Collaboration", which she completed in 2015 at MIT. We discuss her work on interpretability, including her work in the thesis on the Bayesian Case...

Adji Bousso Dieng is currently a Research Scientist at Google AI, and will be starting as an assistant professor at Princeton University in 2021. Her research focuses on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data. Her PhD thesis is titled "Deep Probabilistic Graphical Modeling", which she completed in 2020 at Columbia Universi...

Martha White is an Associate Professor at the University of Alberta. Her research focuses on developing reinforcement learning and representation learning techniques for adaptive, autonomous agents learning on streams of data. Her PhD thesis is titled "Regularized Factor Models", which she completed in 2014 at the University of Alberta. We discuss the regularized factor model framework, which unif...

Jacob Andreas is an Assistant Professor at MIT, where he leads the language and intelligence group, focusing on language as a communicative and computational tool. His PhD thesis is titled "Learning from Language" which he completed in 2018 at UC Berkeley. We discuss compositionality and neural module networks, the intersection of RL and language, and translating a neural communication channel cal...

Chelsea Finn is an Assistant Professor at Stanford University, where she leads the IRIS lab that studies intelligence through robotic interaction at scale. Her PhD thesis is titled "Learning to Learn with Gradients", which she completed in 2018 at UC Berkeley. Chelsea received the prestigious ACM Doctoral Dissertation Award for her work in the thesis. We discuss machine learning for robotics, focu...

Kenneth Stanley is a researcher at OpenAI, where he leads the team on Open-endedness. Previously he was a Professor Computer Science at the University of Central Florida, cofounder of Geometric Intelligence, and head of Core AI research at Uber AI labs. His PhD thesis is titled "Efficient Evolution of Neural Networks through Complexification", which he completed on 2004 at the University of Texas....

He He is an Assistant Professor at New York University. Her research focuses on enabling reliable communication in natural language between machine and humans, including topics in text generation, robust language understanding, and dialogue systems. Her PhD thesis is titled "Sequential Decisions and Predictions in NLP", which she completed in 2016 at the University of Maryland. We talk about the i...

John Schulman is a Research Scientist and co-founder of Open AI. John co-leads the reinforcement learning team, researching algorithms that safely and efficiently learn by trial and error and by imitating humans. His PhD thesis is titled "Optimizing Expectations: From Deep Reinforcement Learning to Stochastic Computation Graphs", which he completed in 2016 at Berkeley. We talk about his work on st...

Yoon Kim is currently a Research Scientist at the MIT-IBM AI Watson Lab, and will be joining MIT as an assistant professor in 2021. Yoon’s research focuses on machine learning and natural language processing. His PhD thesis is titled "Deep Latent Variable Models of Natural Language", which he completed in 2020 at Harvard University. We discuss his work on uncovering latent structure in natural lan...

Julian Togelius is an Associate Professor at New York University, where he co-directs the NYU Game Innovation Lab. His research is at the intersection of computational intelligence and computer games. His PhD thesis is titled "Optimization, Imitation, and Innovation: Computational Intelligence and Games", which he completed in 2007. We cover his work in the thesis on AI for games and games for AI,...

Sebastian Nowozin is currently a Researcher at Microsoft Research Cambridge. His research focuses on probabilistic deep learning, consequences of model misspecification, understanding agent complexity in order to improve learning efficiency, and designing models for reasoning and planning. His PhD thesis is titled "Learning with Structured Data: Applications to Computer Vision", which he completed...

Sebastian Ruder is currently a Research Scientist at Deepmind. His research focuses on transfer learning for natural language processing, and making machine learning and NLP more accessible. His PhD thesis is titled "Neural Transfer Learning for Natural Language Processing", which he completed in 2019. We cover transfer learning from philosophical and technical perspectives, and talk about its soc...

Colin Raffel is currently a Senior Research Scientist at Google Brain, and soon to be an assistant professor at the University of North Carolina. His recent work focuses on transfer learning and learning from limited labels. His thesis is titled "Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching", which we discuss along with the connections t...

Gus Xia is an assistant professor at New York University Shanghai. His research explores machine learning for music, with a goal of building intelligent systems that understand and extend musical creativity and expression. His PhD thesis is titled Expressive Collaborative Music Performance via Machine Learning, which we discuss in depth along with his ongoing research at the NYU Shanghai Music X L...

[00] The Thesis Review Podcast - Introduction by Sean Welleck