Yarin Gal is an Associate Professor of Machine Learning at the Computer Science department at the University of Oxford. He is also a Tutorial Fellow in Computer Science at Christ Church, Oxford, a Turing AI Fellow at the Alan Turing Institute, and Director of Research at the UK Government's AI Safety Institute (AISI).
Yarin Gal obtained his PhD from the Cambridge Machine Learning Group, working with Zoubin Ghahramani and funded by the Google Europe Doctoral Fellowship. Prior to that, he studied Computer Science at Oxford for a Master's degree under the supervision of Phil Blunsom.
Before taking up his position at Oxford, Gal was a Research Fellow in Computer Science at St Catharine's College, Cambridge. He has also taught Advanced Machine Learning (2018-2019), Advanced Topics in Machine Learning (2021-2022), and Uncertainty in Deep Learning (2023-2024). In addition, he has taught machine learning at the NASA Frontier Development Lab, helping NASA make use of AI for the space program.
Gal's research interests lie in the fields of linguistics, applied maths, and computer science, particularly the problems found at the intersections of these fields. His current research focuses on developing Bayesian techniques for deep learning, with applications in reinforcement learning. He has also worked on Bayesian modelling, approximate inference, natural language processing, Bayesian nonparametrics, Gaussian processes, inference algorithms for big data, and machine translation.
Gal has achieved notable research accomplishments in Bayesian statistics, approximate Bayesian inference, and Bayesian deep learning. He has also worked on applications such as computer vision, AI safety, and ML interpretability.
Yarin Gal has published extensively in the fields of machine learning, artificial intelligence, probability theory, and statistics. His publications include:
Youtube Title: Yarin Gal - Uncertainty in Deep Learning | MLSS Kraków 2023
Youtube Link: link
Youtube Channel Name: ML in PL
Youtube Channel Link: https://www.youtube.com/@MLinPLAssociation
Yarin Gal - Uncertainty in Deep Learning | MLSS Kraków 2023
Youtube Title: Yarin Gal -. Bayesian Deep Learning
Youtube Link: link
Youtube Channel Name: SMILES - Summer School of Machine Learning at SK
Youtube Channel Link: https://www.youtube.com/@smiles-summerschoolofmachi5505
Yarin Gal -. Bayesian Deep Learning
Youtube Title: Yarin Gal - Bayesian Deep Learning Pt.2
Youtube Link: link
Youtube Channel Name: SMILES - Summer School of Machine Learning at SK
Youtube Channel Link: https://www.youtube.com/@smiles-summerschoolofmachi5505
Yarin Gal - Bayesian Deep Learning Pt.2
Youtube Title: Exploring foundation models - Session 3
Youtube Link: link
Youtube Channel Name: The Alan Turing Institute
Youtube Channel Link: https://www.youtube.com/@TheAlanTuringInstituteUK
Exploring foundation models - Session 3
Youtube Title: Lightning lectures: The art of AI extrapolation | The Royal Society
Youtube Link: link
Youtube Channel Name: The Royal Society
Youtube Channel Link: https://www.youtube.com/@royalsociety
Lightning lectures: The art of AI extrapolation | The Royal Society
Youtube Title: Professor Yarin Gal's Keynote on Human-in-the-loop Bayesian Deep Learning (UNSURE 2020)
Youtube Link: link
Youtube Channel Name: UNSURE Workshop
Youtube Channel Link: https://www.youtube.com/@unsureworkshop8093
Professor Yarin Gal's Keynote on Human-in-the-loop Bayesian Deep Learning (UNSURE 2020)
Youtube Title: ESGW: Artificial Intelligence for Space - Panel Discussion
Youtube Link: link
Youtube Channel Name: spacegeneration
Youtube Channel Link: https://www.youtube.com/@spacegeneration
ESGW: Artificial Intelligence for Space - Panel Discussion
Youtube Title: MIC 2018 - Targeted Dropout and Bitrot
Youtube Link: link
Youtube Channel Name: MIC Media
Youtube Channel Link: https://www.youtube.com/@micmedia5591
MIC 2018 - Targeted Dropout and Bitrot
Youtube Title: Understanding Approximate Inference in Bayesian Neural Networks: A Joint Talk
Youtube Link: link
Youtube Channel Name: OATML research group
Youtube Channel Link: https://www.youtube.com/@oatmlresearchgroup9874
Understanding Approximate Inference in Bayesian Neural Networks: A Joint Talk
Youtube Title: BILLA SONIPAT ALA : Yaaran Gail (Official Video) Guri Nimana | Haryanvi Songs Harayanvi 2022
Youtube Link: link
Youtube Channel Name: White Hill Dhaakad
Youtube Channel Link: https://www.youtube.com/@WhiteHillDhaakad
BILLA SONIPAT ALA : Yaaran Gail (Official Video) Guri Nimana | Haryanvi Songs Harayanvi 2022
Youtube Title: Model Uncertainty in Deep Learning | Lecture 80 (Part 4) | Applied Deep Learning
Youtube Link: link
Youtube Channel Name: Maziar Raissi
Youtube Channel Link: https://www.youtube.com/@maziarraissi3569
Model Uncertainty in Deep Learning | Lecture 80 (Part 4) | Applied Deep Learning
Youtube Title: Evaluating Online Bayesian Inference in Sample-Based Approximate BNNs
Youtube Link: link
Youtube Channel Name: Updatable Machine Learning workshop @ ICML2022
Youtube Channel Link: https://www.youtube.com/@updatablemachinelearningwo9964
Evaluating Online Bayesian Inference in Sample-Based Approximate BNNs
Youtube Title: Trustworthy AI: Bayesian deep learning | AI FOR GOOD DISCOVERY
Youtube Link: link
Youtube Channel Name: AI for Good
Youtube Channel Link: https://www.youtube.com/@AIforGood
Trustworthy AI: Bayesian deep learning | AI FOR GOOD DISCOVERY
Youtube Title: Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
Youtube Link: link
Youtube Channel Name: Alex Kendall
Youtube Channel Link: https://www.youtube.com/@AlexKendallNZ
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
Youtube Title: [ZC5] Toward a Tractable Solution for Human in the loop Reinforcement Learning
Youtube Link: link
Youtube Channel Name: SNU ECE BK21
Youtube Channel Link: https://www.youtube.com/@snuecebk2135
![ZC5] Toward a Tractable Solution for Human in the loop Reinforcement Learning