PODCAST · science
The Thesis Review
by Sean Welleck
Each episode of The Thesis Review is a conversation centered around a researcher's PhD thesis, giving insight into their history, revisiting older ideas, and providing a valuable perspective on how their research has evolved (or stayed the same) since.
Episodes
-
[48] Tianqi Chen - Scalable and Intelligent Learning Systems
Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems. Tianqi's PhD thesis is titled "Scalable and...
-
[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models
Niloofar Mireshghallah is a postdoctoral scholar at the University of Washington. Her research focuses on privacy, natural language processing, and the societal implications of machine learning. Niloofar completed her PhD in 2023 at UC San Diego, where she was advised by Taylor Berg-Kirkpatrick....
-
[46] Yulia Tsvetkov - Linguistic Knowledge in Data-Driven NLP
Yulia Tsvetkov is a Professor in the Allen School of Computer Science & Engineering at the University of Washington. Her research focuses on multilingual NLP, NLP for social good, and language generation. Yulia's PhD thesis is titled "Linguistic Knowledge in Data-Driven Natural Language...
-
[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form
Luke Zettlemoyer is a Professor at the University of Washington and Research Scientist at Meta. His work spans machine learning and NLP, including foundational work in large-scale self-supervised pretraining of language models. Luke's PhD thesis is titled "Learning to Map Sentences to Logical...
-
[44] Hady Elsahar - NLG from Structured Knowledge Bases (& Controlling LMs)
Hady Elsahar is a Research Scientist at Naver Labs Europe. His research focuses on Neural Language Generation under constrained and controlled conditions. Hady's PhD was on interactions between Natural Language and Structured Knowledge bases for Data2Text Generation and Relation Extraction &...
-
[43] Swarat Chaudhuri - Logics and Algorithms for Software Model Checking
Swarat Chaudhuri is an Associate Professor at the University of Texas. His lab studies problems at the interface of programming languages, logic and formal methods, and machine learning. Swarat's PhD thesis is titled "Logics and Algorithms for Software Model Checking", which he completed in 2007…
more -
[42] Charles Sutton - Efficient Training Methods for Conditional Random Fields
Charles Sutton is a Research Scientist at Google Brain and an Associate Professor at the University of Edinburgh. His research focuses on deep learning for generating code and helping people write better programs. Charles' PhD thesis is titled "Efficient Training Methods for Conditional Random...
-
[41] Talia Ringer - Proof Repair
Talia Ringer is an Assistant Professor with the Programming Languages, Formal Methods, and Software Engineering group at University of Illinois Urbana-Champaign. Her research focuses on formal verification and proof engineering technologies. Talia's PhD thesis is titled "Proof Repair", which she...
-
[40] Lisa Lee - Learning Embodied Agents with Scalably-Supervised RL
Lisa Lee is a Research Scientist at Google Brain. Her research focuses on building AI agents that can learn and adapt like humans and animals do. Lisa's PhD thesis is titled "Learning Embodied Agents with Scalably-Supervised Reinforcement Learning", which she completed in 2021 at Carnegie Mellon...
-
[39] Burr Settles - Curious Machines: Active Learning with Structured Instances
Burr Settles leads the research group at Duolingo, a language-learning website and mobile app whose mission is to make language education free and accessible to everyone. Burr’s PhD thesis is titled "Curious Machines: Active Learning with Structured Instances", which he completed in 2008 at the...
-
[38] Andrew Lampinen - A Computational Framework for Learning and Transforming Task Representations
Andrew Lampinen is a research scientist at DeepMind. His research focuses on cognitive flexibility and generalization. Andrew’s PhD thesis is titled "A Computational Framework for Learning and Transforming Task Representations", which he completed in 2020 at Stanford University. We talk about...
-
[37] Joonkoo Park - Neural Substrates of Visual Word and Number Processing
Joonkoo Park is an Associate Professor and Honors Faculty in the Department of Psychological and Brain Sciences at UMass Amherst. He leads the Cognitive and Developmental Neuroscience Lab, focusing on understanding the developmental mechanisms and neurocognitive underpinnings of our knowledge…
more -
[36] Dieuwke Hupkes - Hierarchy and Interpretability in Neural Models of Language Processing
Dieuwke Hupkes is a Research Scientist at Facebook AI Research and the scientific manager of the Amsterdam unit of ELLIS. Dieuwke's PhD thesis is titled, "Hierarchy and Interpretability in Neural Models of Language Processing", which she completed in 2020 at the University of Amsterdam. We…
more -
[35] Armando Solar-Lezama - Program Synthesis by Sketching
Armando Solar-Lezama is a Professor at MIT, and the Associate Director & COO of CSAIL. He leads the Computer Assisted Programming Group, focused on program synthesis. Armando’s PhD thesis is titled, "Program Synthesis by Sketching", which he completed in 2008 at UC Berkeley. We talk about program...
-
[34] Sasha Rush - Lagrangian Relaxation for Natural Language Decoding
Sasha Rush is an Associate Professor at Cornell Tech and researcher at Hugging Face. His research focuses on building NLP systems that are safe, fast, and controllable. Sasha's PhD thesis is titled, "Lagrangian Relaxation for Natural Language Decoding", which he completed in 2014 at MIT. We talk...
-
[33] Michael R. Douglas - G/H Conformal Field Theory
Michael R. Douglas is a theoretical physicist and Professor at Stony Brook University, and Visiting Scholar at Harvard University. His research focuses on string theory, theoretical physics and its relations to mathematics. Michael's PhD thesis is titled, "G/H Conformal Field Theory", which he...
-
[32] Andre Martins - The Geometry of Constrained Structured Prediction
Andre Martins is an Associate Professor at IST and VP of AI Research at Unbabel in Lisbon, Portugal. His research focuses on natural language processing and machine learning. Andre’s PhD thesis is titled, "The Geometry of Constrained Structured Prediction: Applications to Inference and Learning…
more -
[31] Jay McClelland - Preliminary Letter Identification in the Perception of Words and Nonwords
Jay McClelland is a Professor in the Psychology Department and Director of the Center for Mind, Brain, Computation and Technology at Stanford. His research addresses a broad range of topics in cognitive science and cognitive neuroscience, including Parallel Distributed Processing (PDP). Jay's PhD...
-
[30] Dustin Tran - Probabilistic Programming for Deep Learning
Dustin Tran is a research scientist at Google Brain. His research focuses on advancing science and intelligence, including areas involving probability, programs, and neural networks. Dustin’s PhD thesis is titled "Probabilistic Programming for Deep Learning", which he completed in 2020 at…
more -
[29] Tengyu Ma - Non-convex Optimization for Machine Learning
Tengyu Ma is an Assistant Professor at Stanford University. His research focuses on deep learning and its theory, as well as various topics in machine learning. Tengyu's PhD thesis is titled "Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding", which he completed in...
-
[28] Karen Ullrich - A Coding Perspective on Deep Latent Variable Models
Karen Ullrich is a Research Scientist at FAIR. Her research focuses on the intersection of information theory and probabilistic machine learning and deep learning. Karen's PhD thesis is titled "A coding perspective on deep latent variable models", which she completed in 2020 at The University of...
-
[27] Danqi Chen - Neural Reading Comprehension and Beyond
Danqi Chen is an assistant professor at Princeton University, co-leading the Princeton NLP Group. Her research focuses on fundamental methods for learning representations of language and knowledge, and practical systems including question answering, information extraction and conversational…
more -
[26] Kevin Ellis - Algorithms for Learning to Induce Programs
Kevin Ellis is an assistant professor at Cornell and currently a research scientist at Common Sense Machines. His research focuses on artificial intelligence, program synthesis, and neurosymbolic models. Kevin's PhD thesis is titled "Algorithms for Learning to Induce Programs", which he completed...
-
[25] Tomas Mikolov - Statistical Language Models Based on Neural Networks
Tomas Mikolov is a Senior Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research has covered topics in natural language understanding and representation learning, including Word2Vec, and complexity. Tomas's PhD thesis is titles "Statistical Language Models Based...
-
[24] Martin Arjovsky - Out of Distribution Generalization in Machine Learning
Martin Arjovsky is a postdoctoral researcher at INRIA. His research focuses on generative modeling, generalization, and exploration in RL. Martin's PhD thesis is titled "Out of Distribution Generalization in Machine Learning", which he completed in 2019 at New York University. We discuss his work...
-
[23] Simon Du - Gradient Descent for Non-convex Problems in Modern Machine Learning
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",...
-
[22] Graham Neubig - Unsupervised Learning of Lexical Information
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...
-
[21] Michela Paganini - Machine Learning Solutions for High Energy Physics
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…
more -
[20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics
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...
-
[19] Dumitru Erhan - Understanding Deep Architectures and the Effect of Unsupervised Pretraining
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...
-
[18] Eero Simoncelli - Distributed Representation and Analysis of Visual Motion
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…
more -
[17] Paul Middlebrooks - Neuronal Correlates of Meta-Cognition in Primate Frontal Cortex
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...
-
[16] Aaron Courville - A Latent Cause Theory of Classical Conditioning
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...
-
[15] Christian Szegedy - Some Applications of the Weighted Combinatorial Laplacian
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…
more -
[14] Been Kim - Interactive and Interpretable Machine Learning Models
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...
-
[13] Adji Bousso Dieng - Deep Probabilistic Graphical Modeling
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...
-
[12] Martha White - Regularized Factor Models
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...
-
[11] Jacob Andreas - Learning from Language
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...
-
[10] Chelsea Finn - Learning to Learn with Gradients
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...
-
[09] Kenneth Stanley - Efficient Evolution of Neural Networks through Complexification
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…
more -
[08] He He - Sequential Decisions and Predictions in NLP
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...
-
[07] John Schulman - Optimizing Expectations: From Deep RL to Stochastic Computation Graphs
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…
more -
[06] Yoon Kim - Deep Latent Variable Models of Natural Language
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...
-
[05] Julian Togelius - Computational Intelligence and Games
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…
more -
[04] Sebastian Nowozin - Learning with Structured Data: Applications to Computer Vision
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…
more -
[03] Sebastian Ruder - Neural Transfer Learning for Natural Language Processing
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...
-
[02] Colin Raffel - Learning-Based Methods for Comparing Sequences
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…
more -
[01] Gus Xia - Expressive Collaborative Music Performance via Machine Learning
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...
-
[00] The Thesis Review Podcast - Introduction
[00] The Thesis Review Podcast - Introduction by Sean Welleck
We're indexing this podcast's transcripts for the first time — this can take a minute or two. We'll show results as soon as they're ready.
No matches for "" in this podcast's transcripts.
No topics indexed yet for this podcast.
Loading reviews...
ABOUT THIS SHOW
Each episode of The Thesis Review is a conversation centered around a researcher's PhD thesis, giving insight into their history, revisiting older ideas, and providing a valuable perspective on how their research has evolved (or stayed the same) since.
HOSTED BY
Sean Welleck
CATEGORIES
Loading similar podcasts...
Frequently Asked Questions
How many episodes does The Thesis Review have?
The Thesis Review currently has 49 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.
What is The Thesis Review about?
Each episode of The Thesis Review is a conversation centered around a researcher's PhD thesis, giving insight into their history, revisiting older ideas, and providing a valuable perspective on how their research has evolved (or stayed the same) since.
How often does The Thesis Review release new episodes?
The Thesis Review has 49 episodes. Check the episode list to see recent publication dates and frequency.
Where can I listen to The Thesis Review?
You can listen to The Thesis Review on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.
Who hosts The Thesis Review?
The Thesis Review is created and hosted by Sean Welleck.
URL copied to clipboard!