Organizers

Aaron Courville
Program Committee
Aarti Singh
Program Committee
Alain Rakotomamonjy
Program Committee
Alan A Stocker
Program Committee
Alina Beygelzimer
Program Committee
Amir Globerson
Program Committee
Bio

Amir Globerson received a BSc in computer science and physics from the Hebrew University, and a PhD in computational neuroscience from the Hebrew University. After his PhD, he was a postdoctoral fellow at the University of Toronto and a Rothschild postdoctoral fellow at MIT. He joined the Hebrew University school of computer science in 2008, and moved to the Tel Aviv University School of Computer Science in 2016. He is also a research scientist at Google and is currently on sabbatical at Google NYC. He served as an Associate Editor in Chief for the IEEE Transactions on Pattern Analysis And Machine Intelligence. His work has received several paper awards (at NeurIPS,UAI, and ICML). In 2018 he served as program co-chair for the UAI conference, and in 2019 he was the general co-chair for UAI in Tel Aviv. In 2019 he received the ERC consolidator grant. He is serving as program co-chair at NeurIPS 2023, and will serve as NeurIPS 2024 general chair.

Amos Storkey
Program Committee
Andreas Krause
Program Committee
Aurelie Lozano
Program Committee
Barnabas Poczos
Program Committee
Bharath Sriperumbudur
Program Committee
Bohyung Han
Program Committee
Byron M Yu
Program Committee
Cheng Soon Ong
Program Committee
Chih-Jen Lin
Program Committee
Christoph Lampert
Program Committee
Bio

Christoph Lampert received the PhD degree in mathematics from the University of Bonn in 2003. In 2010 he joined the Institute of Science and Technology Austria (ISTA) first as an Assistant Professor and since 2015 as a Professor. There, he leads the research group for Machine Learning and Computer Vision, and since 2019 he is also the head of ISTA's ELLIS unit.

Claire Monteleoni
Program Committee
Bio

Claire Monteleoni is an associate professor of Computer Science at University of Colorado Boulder. Previously, she was an associate professor at George Washington University, and research faculty at the Center for Computational Learning Systems, at Columbia University. She did a postdoc in Computer Science and Engineering at the University of California, San Diego, and completed her PhD and Masters in Computer Science, at MIT. She holds a Bachelors in Earth and Planetary Sciences from Harvard. Her research focuses on machine learning algorithms and theory for problems including learning from data streams, learning from raw (unlabeled) data, learning from private data, and climate informatics: accelerating discovery in climate science with machine learning. Her work on climate informatics received the Best Application Paper Award at NASA CIDU 2010. In 2011, she co-founded the International Workshop on Climate Informatics, which is now in its fourth year, attracting climate scientists and data scientists from over 14 countries and 26 states.

Clay Scott
Program Committee
Csaba Szepesvari
Program Committee
Cynthia Rudin
Program Committee
Daniel A Braun
Program Committee
David Balduzzi
Program Committee
David Mcallester
Program Committee
Denny Zhou
Program Committee
Dino Sejdinovic
Program Committee
Bio

Dino Sejdinovic is a Professor at the School of Computer and Mathematical Sciences, University of Adelaide. He was previously a Lecturer and an Associate Professor at the Department of Statistics, University of Oxford (2014-2022). He held postdoctoral positions at the Gatsby Computational Neuroscience Unit, University College London (2011-2014) and at the Institute for Statistical Science, University of Bristol (2009-2011). He received a PhD in Electrical and Electronic Engineering from the University of Bristol (2009) and a Diplom in Mathematics and Theoretical Computer Science from the University of Sarajevo (2006).

Elad Hazan
Program Committee
Emily Fox
Program Committee
Emma Brunskill
Program Committee
Eric Xing
Program Committee
Eunho Yang
Program Committee
Florence d'Alche-Buc
Program Committee
Francesco Dinuzzo
Program Committee
Gal Chechik
Program Committee
Greg Mori
Program Committee
Gunnar Rätsch
Program Committee
Hang Li
Program Committee
Honglak Lee
Program Committee
Hsuan-Tien Lin
Program Committee
Bio

Professor Hsuan-Tien Lin received a B.S. in Computer Science and Information Engineering from National Taiwan University in 2001, an M.S. and a Ph.D. in Computer Science from California Institute of Technology in 2005 and 2008, respectively. He joined the Department of Computer Science and Information Engineering at National Taiwan University as an assistant professor in 2008 and has been promoted to full professor in 2017. Between 2016 and 2019, he worked as the Chief Data Scientist of Appier, a startup company that specializes in making AI easier for marketing. Currently, he keeps growing with Appier as its Chief Data Science Consultant. From the university, Prof. Lin received the Distinguished Teaching Awards in 2011 and 2021, the Outstanding Mentoring Award in 2013, and five Outstanding Teaching Awards between 2016 and 2020. He co-authored the introductory machine learning textbook Learning from Data and offered two popular Mandarin-teaching MOOCs Machine Learning Foundations and Machine Learning Techniques based on the textbook. He served in the machine learning community as Progam Co-chair of NeurIPS 2020, Expo Co-chair of ICML 2021, and Workshop Chair of NeurIPS 2022 and 2023. He co-led the teams that won the champion of KDDCup 2010, the double-champion of the two tracks …

Huan Xu
Program Committee
Hugo Larochelle
Program Committee
Ian Goodfellow
Program Committee
Ichiro Takeuchi
Program Committee
Ilya Sutskever
Program Committee
Inderjit Dhillon
Program Committee
Issei Sato
Program Committee
Ivor Tsang
Program Committee
James Kwok
Program Committee
Jerry Zhu
Program Committee
Jianbo Shi
Program Committee
Jieping Ye
Program Committee
Jingyi Yu
Program Committee
John Langford
Program Committee
Bio

John Langford is a machine learning research scientist, a field which he says "is shifting from an academic discipline to an industrial tool". He is the author of the weblog hunch.net and the principal developer of Vowpal Wabbit. John works at Microsoft Research New York, of which he was one of the founding members, and was previously affiliated with Yahoo! Research, Toyota Technological Institute, and IBM's Watson Research Center. He studied Physics and Computer Science at the California Institute of Technology, earning a double bachelor's degree in 1997, and received his Ph.D. in Computer Science from Carnegie Mellon University in 2002. He was the program co-chair for the 2012 International Conference on Machine Learning.

Jun Zhu
Program Committee
Kee-Eung Kim
Program Committee
Kenji Fukumizu
Program Committee
Koji Tsuda
Program Committee
Kyunghyun Cho
Program Committee
Bio

Kyunghyun Cho is an associate professor of computer science and data science at New York University and a research scientist at Facebook AI Research. He was a postdoctoral fellow at the Université de Montréal until summer 2015 under the supervision of Prof. Yoshua Bengio, and received PhD and MSc degrees from Aalto University early 2014 under the supervision of Prof. Juha Karhunen, Dr. Tapani Raiko and Dr. Alexander Ilin. He tries his best to find a balance among machine learning, natural language processing, and life, but almost always fails to do so.

Laurens van der Maaten
Program Committee
Le Song
Program Committee
Li Deng
Program Committee
Liwei Wang
Program Committee
Marc Deisenroth
Program Committee
Bio

Professor Marc Deisenroth is the DeepMind Chair in Artificial Intelligence at University College London and the Deputy Director of UCL's Centre for Artificial Intelligence. He also holds a visiting faculty position at the University of Johannesburg and Imperial College London. Marc's research interests center around data-efficient machine learning, probabilistic modeling and autonomous decision making. Marc was Program Chair of EWRL 2012, Workshops Chair of RSS 2013, EXPO-Co-Chair of ICML 2020, and Tutorials Co-Chair of NeurIPS 2021. In 2019, Marc co-organized the Machine Learning Summer School in London. He received Paper Awards at ICRA 2014, ICCAS 2016, and ICML 2020. He is co-author of the book Mathematics for Machine Learning published by Cambridge University Press (2020).

Marco Cuturi
Program Committee
Bio

Marco Cuturi is a research scientist at Apple, in Paris. He received his Ph.D. in 11/2005 from the Ecole des Mines de Paris in applied mathematics. Before that he graduated from National School of Statistics (ENSAE) with a master degree (MVA) from ENS Cachan. He worked as a post-doctoral researcher at the Institute of Statistical Mathematics, Tokyo, between 11/2005 and 3/2007 and then in the financial industry between 4/2007 and 9/2008. After working at the ORFE department of Princeton University as a lecturer between 2/2009 and 8/2010, he was at the Graduate School of Informatics of Kyoto University between 9/2010 and 9/2016 as a tenured associate professor. He joined ENSAE in 9/2016 as a professor, where he is now working part-time. He was at Google between 10/2018 and 1/2022. His main employment is now with Apple, since 1/2022, as a research scientist working on fundamental aspects of machine learning.

Maria-Florina Balcan
Program Committee
Marina Meila
Program Committee
Massimiliano Pontil
Program Committee
Matthias Seeger
Program Committee
Mohammad Emtiyaz Khan
Program Committee
Bio

Emtiyaz Khan (also known as Emti) is a team leader at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo where he leads the Approximate Bayesian Inference Team. He is also a visiting professor at the Tokyo University of Agriculture and Technology (TUAT). Previously, he was a postdoc and then a scientist at Ecole Polytechnique Fédérale de Lausanne (EPFL), where he also taught two large machine learning courses and received a teaching award. He finished his PhD in machine learning from University of British Columbia in 2012. The main goal of Emti’s research is to understand the principles of learning from data and use them to develop algorithms that can learn like living beings. For the past 10 years, his work has focused on developing Bayesian methods that could lead to such fundamental principles. The approximate Bayesian inference team now continues to use these principles, as well as derive new ones, to solve real-world problems.

Moritz Grosse-Wentrup
Program Committee
Naonori Ueda
Program Committee
Nati Srebro
Program Committee
Novi Quadrianto
Program Committee
Pavel Laskov
Program Committee
Peter Orbanz
Program Committee
Bio

Peter Orbanz is a research fellow at the University of Cambridge. He holds a PhD degree from ETH Zurich and will join the Statistics Faculty at Columbia University as an Assistant Professor in 2012. He is interested in the mathematical and algorithmic aspects of Bayesian nonparametric models and of related learning technologies.

Remi Munos
Program Committee
René Vidal
Program Committee
Russ Salakhutdinov
Program Committee
Ryota Tomioka
Program Committee
Samory Kpotufe
Program Committee
Samy Bengio
Program Committee
Sebastian Nowozin
Program Committee
Seungjin Choi
Program Committee
Shakir Mohamed
Program Committee
Bio

Shakir Mohamed is a senior staff scientist at DeepMind in London. Shakir's main interests lie at the intersection of approximate Bayesian inference, deep learning and reinforcement learning, and the role that machine learning systems at this intersection have in the development of more intelligent and general-purpose learning systems. Before moving to London, Shakir held a Junior Research Fellowship from the Canadian Institute for Advanced Research (CIFAR), based in Vancouver at the University of British Columbia with Nando de Freitas. Shakir completed his PhD with Zoubin Ghahramani at the University of Cambridge, where he was a Commonwealth Scholar to the United Kingdom. Shakir is from South Africa and completed his previous degrees in Electrical and Information Engineering at the University of the Witwatersrand, Johannesburg.

Shinichi Nakajima
Program Committee
Sinead Williamson
Program Committee
Sinno Jialin Pan
Program Committee
Svetlana Lazebnik
Program Committee
S.V.N. Vishwanathan
Program Committee
Taiji Suzuki
Program Committee
Thomas Gaertner
Program Committee
Tie-Yan Liu
Program Committee
Bio

Tie-Yan Liu is an assistant managing director of Microsoft Research Asia, leading the machine learning research area. He is very well known for his pioneer work on learning to rank and computational advertising, and his recent research interests include deep learning, reinforcement learning, and distributed machine learning. Many of his technologies have been transferred to Microsoft’s products and online services (such as Bing, Microsoft Advertising, Windows, Xbox, and Azure), and open-sourced through Microsoft Cognitive Toolkit (CNTK), Microsoft Distributed Machine Learning Toolkit (DMTK), and Microsoft Graph Engine. He has also been actively contributing to academic communities. He is an adjunct/honorary professor at Carnegie Mellon University (CMU), University of Nottingham, and several other universities in China. He has published 200+ papers in refereed conferences and journals, with over 17000 citations. He has won quite a few awards, including the best student paper award at SIGIR (2008), the most cited paper award at Journal of Visual Communications and Image Representation (2004-2006), the research break-through award (2012) and research-team-of-the-year award (2017) at Microsoft Research, and Top-10 Springer Computer Science books by Chinese authors (2015), and the most cited Chinese researcher by Elsevier (2017). He has been invited to serve as general chair, program committee …

Tomoharu Iwata
Program Committee
Toshiyuki Tanaka
Program Committee
Wee Sun Lee
Program Committee
Bio

Wee Sun Lee is a professor in the Department of Computer Science, National University of Singapore. He obtained his B.Eng from the University of Queensland in 1992 and his Ph.D. from the Australian National University in 1996. He has been a research fellow at the Australian Defence Force Academy, a fellow of the Singapore-MIT Alliance, and a visiting scientist at MIT.

His research interests include machine learning, planning under uncertainty, and approximate inference. His works have won the Test of Time Award at Robotics: Science and Systems (RSS) 2021, the RoboCup Best Paper Award at International Conference on Intelligent Robots and Systems (IROS) 2015, the Google Best Student Paper Award, Uncertainty in AI (UAI) 2014 (as faculty co-author), as well as several competitions and challenges.

He has been an area chair for machine learning and AI conferences such as the Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), the AAAI Conference on Artificial Intelligence (AAAI), and the International Joint Conference on Artificial Intelligence (IJCAI). He was a program, conference and journal track co-chair for the Asian Conference on Machine Learning (ACML), and he is currently the co-chair of the steering committee of ACML.

Xiaofei He
Program Committee
Xinhua Zhang
Program Committee
Yevgeny Seldin
Program Committee
Yuanqing Lin
Program Committee
Zhi-Hua Zhou
Program Committee
Zhouchen Lin
Program Committee
Terrence Sejnowski
President
Marc'Aurelio Ranzato
Demonstration Chairs
Pedro Ortega
Program Chair Assistant
Yung-Kyun Noh
Program Chair Assistant
Corinna Cortes
General Chair
Neil D Lawrence
General Chair
Daniel Lee
Program Chair
Masashi Sugiyama
Program Chair
Ralf Herbrich
Tutorial Chair
Michael Jordan
Workshop Series Editors
Thomas Dietterich
Workshop Series Editors
Bio

Tom Dietterich (AB Oberlin College 1977; MS University of Illinois 1979; PhD Stanford University 1984) is Professor and Director of Intelligent Systems Research at Oregon State University. Among his contributions to machine learning research are (a) the formalization of the multiple-instance problem, (b) the development of the error-correcting output coding method for multi-class prediction, (c) methods for ensemble learning, (d) the development of the MAXQ framework for hierarchical reinforcement learning, and (e) the application of gradient tree boosting to problems of structured prediction and latent variable models. Dietterich has pursued application-driven fundamental research in many areas including drug discovery, computer vision, computational sustainability, and intelligent user interfaces.

Dietterich has served the machine learning community in a variety of roles including Executive Editor of the Machine Learning journal, co-founder of the Journal of Machine Learning Research, editor of the MIT Press Book Series on Adaptive Computation and Machine Learning, and editor of the Morgan-Claypool Synthesis series on Artificial Intelligence and Machine Learning. He was Program Co-Chair of AAAI-1990, Program Chair of NIPS-2000, and General Chair of NIPS-2001. He was first President of the International Machine Learning Society (the parent organization of ICML) and served a term on the NIPS Board of …

Borja Balle
Workshop Chair
Marco Cuturi
Workshop Chair
Bio

Marco Cuturi is a research scientist at Apple, in Paris. He received his Ph.D. in 11/2005 from the Ecole des Mines de Paris in applied mathematics. Before that he graduated from National School of Statistics (ENSAE) with a master degree (MVA) from ENS Cachan. He worked as a post-doctoral researcher at the Institute of Statistical Mathematics, Tokyo, between 11/2005 and 3/2007 and then in the financial industry between 4/2007 and 9/2008. After working at the ORFE department of Princeton University as a lecturer between 2/2009 and 8/2010, he was at the Graduate School of Informatics of Kyoto University between 9/2010 and 9/2016 as a tenured associate professor. He joined ENSAE in 9/2016 as a professor, where he is now working part-time. He was at Google between 10/2018 and 1/2022. His main employment is now with Apple, since 1/2022, as a research scientist working on fundamental aspects of machine learning.

Kilian Q Weinberger
Publications Chair
Pedro Ortega
Program Manager
Yung-Kyun Noh
Program Manager
Mary Ellen Perry
Executive Director
Corinna Cortes
Symposia Chairs
Neil D Lawrence
Symposia Chairs
Marian S Bartlett
Treasurer