Sean Welleck

The Thesis Review

Science EN ↓ 49 episodes

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.

Author

Sean Welleck

Category

Science

Podcast website

www.wellecks.com

Latest episode

Oct 28, 2024

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Episodes

[48] Tianqi Chen - Scalable and Intelligent Learning Systems 28.10.2024

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 Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his inf...

[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models 15.10.2024

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. Her PhD thesis is titled "Auditing and Mitigating Safety Risks in Large Language Models." We discuss he...

[46] Yulia Tsvetkov - Linguistic Knowledge in Data-Driven NLP 12.08.2023

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 Processing", which she completed in 2016 at CMU. We discuss getting started in research, then move to Yulia's wo...

[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form 25.07.2023

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 Form", which he completed in 2009 at MIT. We talk about his PhD work, the path to the foundational Elmo pa...

[44] Hady Elsahar - NLG from Structured Knowledge Bases (& Controlling LMs) 23.08.2022

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 & Discovery, which he completed in 2019 at the Université de Lyon. We talk about his phd work and how it led...

[43] Swarat Chaudhuri - Logics and Algorithms for Software Model Checking 28.06.2022

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 at the University of Pennsylvania. We discuss reasoning about programs, formal methods & safer machine...

[42] Charles Sutton - Efficient Training Methods for Conditional Random Fields 19.04.2022

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 Fields", which he completed in 2008 at UMass Amherst. We start with his work in the thesis on structured...

[41] Talia Ringer - Proof Repair 30.03.2022

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 completed in 2021 at the University of Washington. We discuss software verification and her PhD work on...

[40] Lisa Lee - Learning Embodied Agents with Scalably-Supervised RL 09.03.2022

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 University. We talk about her work in the thesis on reinforcement learning, including exploration, lear...

[39] Burr Settles - Curious Machines: Active Learning with Structured Instances 02.02.2022

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 University of Wisconsin-Madison. We talk about his work in the thesis on active learning, then chart the...

[38] Andrew Lampinen - A Computational Framework for Learning and Transforming Task Representations 08.01.2022

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 cognitive flexibility in brains and machines, centered around his work in the thesis on meta-mapping. We c...

[37] Joonkoo Park - Neural Substrates of Visual Word and Number Processing 21.12.2021

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 about number and mathematics. Joonkoo’s PhD thesis is titled "Experiential Effects on the Neural Substrate...

[36] Dieuwke Hupkes - Hierarchy and Interpretability in Neural Models of Language Processing 30.11.2021

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 discuss her work on which aspects of hierarchical compositionality and syntactic structure can be learned by...

[35] Armando Solar-Lezama - Program Synthesis by Sketching 06.11.2021

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 synthesis & his work on Sketch, how machine learning's role in program synthesis has evolved over time...

[34] Sasha Rush - Lagrangian Relaxation for Natural Language Decoding 20.10.2021

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 about his work in the thesis on decoding in NLP, how it connects with today, and many interesting topic...

[33] Michael R. Douglas - G/H Conformal Field Theory 01.10.2021

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 completed in 1988 at Caltech. We talk about working with Feynman, Sussman, and Hopfield during his PhD da...

[32] Andre Martins - The Geometry of Constrained Structured Prediction 16.09.2021

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 of Natural Language Syntax", which he completed in 2012 at Carnegie Mellon University and IST. We talk a...

[31] Jay McClelland - Preliminary Letter Identification in the Perception of Words and Nonwords 29.08.2021

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 thesis is titled "Preliminary Letter Identification in the Perception of Words and Nonwords", which he...

[30] Dustin Tran - Probabilistic Programming for Deep Learning 14.08.2021

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 Columbia University. We discuss the intersection of probabilistic modeling and deep learning, including the Ed...

[29] Tengyu Ma - Non-convex Optimization for Machine Learning 01.08.2021

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 2017 at Princeton University. We discuss theory in machine learning and deep learning, including the '...

[28] Karen Ullrich - A Coding Perspective on Deep Latent Variable Models 16.07.2021

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 Amsterdam. We discuss information theory & the minimum description length principle, along with her wor...

[27] Danqi Chen - Neural Reading Comprehension and Beyond 02.07.2021

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 agents. Danqi’s PhD thesis is titled "Neural Reading Comprehension and Beyond", which she completed in 2018...

[26] Kevin Ellis - Algorithms for Learning to Induce Programs 29.05.2021

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 in 2020 at MIT. We discuss Kevin’s work at the intersection of machine learning and program induction,...

[25] Tomas Mikolov - Statistical Language Models Based on Neural Networks 14.05.2021

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 on Neural Networks", which he completed in 2012 at the Brno University of Technology. We discuss compr...

[24] Martin Arjovsky - Out of Distribution Generalization in Machine Learning 30.04.2021

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 on the influential Wasserstein GAN early in his PhD, then discuss his thesis work on out-of-distributi...

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