About

Since its inception in 2017, the Machine Learning and the Physical Sciences (ML4PS) workshop has served as a unique gathering space for the growing community spearheading cross-cutting research topics at the intersection of machine learning (ML) and the physical sciences (PS). This includes the applications of ML to problems in the physical sciences (ML for PS) as well as developments in ML motivated by physical insights (PS for ML). The physical sciences are defined inclusively, including but not limited to physics, astronomy, cosmology, chemistry, biophysics, materials science, and Earth science.

The physical sciences pose challenging, high-profile questions that invite innovation and opportunities for cross-pollination between ML researchers and physical scientists. Recent years have seen a tremendous increase in cases where ML models are used for scientific inference and discovery (e.g., geometric deep learning, simulation-based inference), and simultaneously tools and insights from the physical sciences have been used to develop efficient ML models (e.g., diffusion models and physics-informed neural networks). The communities coalescing at this workshop are encouraged to pursue fresh, synergistic solutions to "big science" questions that can spark new approaches in ML.

This year's programming explores the evolving interplay between academia and industry in basic research. Invited talks and panel discussions emphasize the myriad foundational and translational connections between these domains. Furthermore, we ask: how can our community help sustain open, curiosity-driven research in physics and related sciences when traditional funding models are under strain? What role can industry play in supporting fundamental science, and how can the insights emerging from basic research in the physical sciences and ML help catalyze wider innovations in industry and beyond?

NeurIPS 2025

The Machine Learning and the Physical Sciences 2025 workshop will be held on December 6 or 7, 2025 at the San Diego Convention Center in San Diego, Californa (USA) as a part of the 39th annual conference on Neural Information Processing Systems (NeurIPS). The workshop is planned to take place in a hybrid format inclusive of virtual participation.

Tentative Schedule

All times are local, i.e. Pacific Standard Time (PST).

8:15am - 8:30am Opening remarks
8:30am - 10:00am Invited talks: Foundational connections between ML & the physical sciences
10:00am - 10:30am Coffee break
10:30am - 11:00am Paper spotlight talks
11:00am - 12:00pm Poster session #1
12:00pm - 1:00pm Lunch break
1:00pm - 2:00pm Panel Discussion: How should we translate ML advances between academia & industry?
Exploring the interplay of academia & industry using weather and climate research as a case study.
2:00pm - 2:30pm Paper spotlight talks
2:30pm - 3:30pm Poster session #2
3:30pm - 4:00pm Coffee break
4:00pm - 5:00pm Panel Discussion: What could the "AlphaFold moment" be for fundamental physics?
A conversation on paradigm-shifting applications across ML and particle/astro/accelerator physics.
5:00pm - 5:15pm Closing remarks

Plenary Speakers

Panelists

Panel Discussion: How should we translate ML advances between academia & industry?
Exploring the interplay of academia & industry using weather and climate research as a case study.
Panel Discussion: What could the "AlphaFold moment" be for fundamental physics?
A conversation on paradigm-shifting applications across ML and particle/astro/accelerator physics.

Program Committee (Reviewers)

We acknowledge the 421 members of the program committee for providing reviews on a very tight schedule and making this workshop possible. They are listed in alphabetical order below.

Aaron Wang, Abhijith Gandrakota, Abhilash Neog, Abhinanda Ranjit Punnakkal, Abhinav Sagar, Abhiroop Chatterjee, Abhishek Abhishek, Abhishek Chandra, Abhishikth Mallampalli, Aditya Sengar, Adrian Perez Galvan, Adrian Perez-Suay, Adwaita Janardhan Jadhav, Agnimitra Dasgupta, Ahmed Youssef, Aishwarya Jadhav, Aizhan Akhmetzhanova, Ajay Mandyam Rangarajan, Akanksh Shetty, Alan Aspuru-Guzik, Alessandro Lucantonio, Alexander Migala, Alexander Thomas Gagliano, Alexandre Szenicer, Aman Desai, Ameya Daigavane, AmirEhsan Khorashadizadeh, Amit Kumar Jaiswal, Anant Wairagade, Andreas Filipp, Andreas Schachner, Anindita Maiti, Anna Dawid, Anna Jungbluth, Annalena Kofler, Antoine Wehenkel, Antonin Sulc, Arkaprabha Bhandari, Arkaprabha Ganguli, Arshad Rafiq Shaikh, Arvind Mohan, Arvind Ramanathan, Asal Mehradfar, Ashish Kattamuri, Athénaïs Gautier, Atilim Gunes Baydin, Aurelien Dersy, Aviral Prakash, Bariscan Kurtkaya, Barry M Dillon, Batuhan Koyuncu, Ben Meiring, Benjamin D Shaffer, Bharath Ramsundar, Biprateep Dey, Biswarup Bhattacharya, Boyu Zhang, Brecht F. Verbeken, Brian Nord, Bruno Raffin, Carolina Cuesta-Lazaro, Cenk Tüysüz, Charuleka Varadharajan, Chen Li, Chen-Nee Chuah, Cheng Soon Ong, Chi Xie, Chin Chun Ooi, Chinmaya Bhagat, Christina Reissel, Christophe Bonneville, Christopher C. Hall, Chuhong Wang, Chuwei Wang, Claire David, Claire Suen, Conrad M Albrecht, Cristiano De Nobili, Dalei Wu, Daniel Murnane, Daniel Serino, Danielle C. Maddix, Daohan Wang, Darius A Faroughy, David Rousseau, Deborah Bard, Deep Chatterjee, Dhruv V Patel, Dianzhuo Wang, Dikshant Sagar, Dimitra Maoutsa, Dmitry Guskov, Dong Min Roh, Donghun Lee, DİLARA İCKECAN, Eduardo Soares, Edward Berman, Edward Jiang, Elena Pinetti, Elise Özalp, Elyssa Hofgard, Emanuele Usai, Engin Eren, Entao Yang, Eoin Quinn, Eric Chagnon, Fabian Gans, Fabian Ruehle, Fadoua Khmaissia, Fatih Dinc, Fatwir Sheikh Mohammed, Felix Döppel, Fernando Romero-Lopez, Feyi Olalotiti, Finn Henry O'Shea, Floriano Tori, Foteini Dervisi, Francesco Alesiani, Francisco Villaescusa-Navarro, Franco Pellegrini, François Rozet, Gabriel Missael Barco, Gabriel Perdue, Gadi Naveh, Gaia Grosso, Garrett W. Merz, Gary Shiu, George Stein, Georges Tod, Gergana V. Velikova, Gert-Jan Both, Gianni De Fabritiis, Gijs Vermariën, Gilles Louppe, Graham Van Goffrier, Grant M. Rotskoff, Gérôme Andry, Haiqian Yang, Hao Wu, Haowei Ni, Harsh Sharma, Hector Corzo, Henning Kirschenmann, Hongkyu Yoon, Huanghao Mai, Hunor Csala, Ieva Kazlauskaite, Inbar Savoray, Indra Priyadarsini, Indranil Nayak, Irina Espejo Morales, Irtaza Khalid, Ivan Grega, Jack Collins, Jacky H. T. Yip, Jaemyoung Lee, Jasleen Dhillon, Jason McEwen, Jay Chan, Jean-Luc Fattebert, Jenna Pope, Jeongwhan Choi, Jessica Karaguesian, Jeyashree Krishnan, Jiahe Huang, Jianan Zhou, Jianjun Hu, Jie Bu, Jihan K. Zaki, Jochen Garcke, Joe Germany, Joel Janek Dabrowski, John F Wu, John Michael Martyn, Jonas Spinner, Jordi Tura, Jose Manuel Napoles-Duarte, Joseph Gallego, Joshua Isaacson, Joshua S. Speagle, Joshua Yao-Yu Lin, Julia Gonski, Junbo Peng, Junichi Tanaka, Junze Liu, Ka Wa Ho, Kai Fukami, Kamilė Lukošiūtė, Kana Moriwaki, Karla Tame-Narvaez, Katherine Fraser, Kathleen E. Hamilton, Keith Brown, Kenji Komiya, Kevin P. Greenman, Kiri L. Wagstaff, Kishansingh Rajput, Krish Desai, Kshitij Tayal, Kunal Sunil Kasodekar, Kuntal Pal, Kusumakumari Vanteru, Kyriakos Hjikakou, Lalit Ghule, Lars Doorenbos, Laura Manduchi, Leander Thiele, Leonid Didukh, Li Yang, Lin Li, Line H Clemmensen, Lingxiao Wang, Linnea M. Wolniewicz, Lipi Gupta, Liv Helen Våge, Luca Biggio, Lucas Thibaut Meyer, Ludger Paehler, Lukas Heinrich, M. Sajid, MUHAMMAD AMIN NADIM, Mai H Nguyen, Maksim Zhdanov, Mangeleer Victor, Manish Marwah, Manuel Morales-Alvarado, Maria R. Cervera, Mariel Pettee, Marimuthu Kalimuthu, Marina Meila, Marios Mattheakis, Mary Chriselda Antony Oliver, Mary Idera Salami, Matheus Schossler, Matija Medvidović, Matt L. Sampson, Matt LeBlanc, Matteo Manica, Matthieu Blanke, Maurizio Pierini, Maximilian Dax, Medha Sawhney, Micah Bowles, Michael BAUERHEIM, Michael Churchill, Michael R Douglas, Michelle P. Kuchera, Mike Williams, Mikel Landajuela, Milad Ramezankhani, Milind Malshe, Minoo Jafarlou, Mirali Purohit, Miroslav Kubu, Mit Kotak, Mohammad Shahab Sepehri, Mohammad Sultan, Monika Malik, Mridul Khurana, Myungjoon Kim, Natalie Klein, Navaneetha Krishnan K, Nayantara Mudur, Neel Chatterjee, Negin Forouzesh, Nesar Soorve Ramachandra, Nick McGreivy, Nicole Hartman, Nikolaos Nikolaou, Nils Thuerey, Nischal Reddy Chandra, Nishant Panda, Nishant Sharma, Nolan Smyth, Oleg Savchenko, Olivier Saut, Omar Alterkait, Ondrej Hovorka, Onur Kara, Othmane Rifki, Oz Amram, Ozan Gokdemir, P. Darc, Pankaj Rajak, Pao-Hsiung Chiu, Paul Atzberger, Pedro L. C. Rodrigues, Peer-timo Bremer, Pengcheng Xie, Peter McKeown, Peter Melchior, Peter Sadowski, Peter Steinbach, Phaedon Stelios Koutsourelakis, Phan Nguyen, Pietro Vischia, Pinaki Pal, Pradyun Hebbar, Praneeth reddy Amudala Puchakayala, Prathamesh Dinesh Joshi, Pratik Jawahar, Pritthijit Nath, Qiaohao Liang, Quoc Hoan Tran, Raghav Kansal, Raheem K Hashmani, Rajat Arora, Rasmus F. Ørsøe, Raunak Borker, Redouane Lguensat, Remmy Zen, Ricardo Vinuesa, Rishabh Jain, Rodrigo Vargas-Hernandez, Ryan Hausen, Ryan-Rhys Griffiths, Sachin Alexander Reddy, Sajib Acharjee Dip, Saksham Kapoor, Sam Foreman, Sam Vinko, Sampad B Mohanty, Samuel Bright-Thonney, Sankalp Gilda, Satish Chandran, Satpreet Harcharan Singh, Sebastian Kaltenbach, Sebastian Wagner-Carena, Shahnawaz Ahmed, Shaokai Yang, Shashank Galla, Shehtab Zaman, Shixiao Liang, Shiyu Wang, Shounak Sural, Shreyas Vinaya Sathyanarayana, Shubhendu Trivedi, Siddhant Midha, Siddharth Mishra-Sharma, Simone Manti, Siu Wun Cheung, Sokratis Trifinopoulos, Soledad Villar, Somya Chatterjee, Sreevani Jarugula, Srinadh Reddy Bhavanam, Srinandan Dasmahapatra, Stephen Y. Zhang, Steven Dillmann, Sudhakar Pamidighantam, Sudip K Seal, Sui Tang, Sujeet Bhalerao, Sylvester Kaczmarek, Takashi Matsubara, Taniya Kapoor, Taoli Cheng, Tarun Kumar, Tarun Narayanan, Tejus Gupta, Theodota Lagouri, Thomas Beckers, Thomas Blum, Till Korten, Tobias Buck, Tomasz Szumlak, Tomo Lazovich, Tri Nguyen, Tsuyoshi Okita, V Ashley Villar, Vacslav Glukhov, Vahe Gharakhanyan, Valentina Salvatelli, Vansh Sharma, Vanya Bannihatti Kumar, Ved G. Shah, Vinicius Mikuni, Vishwa Pardeshi, Vispi Nevile Karkaria, Vitus Benson, Vudtiwat Ngampruetikorn, Wei-Cheng Lee, Wenhao Lu, Xian Yeow Lee, Xiang Li, Xiangming Meng, Xiangyang Ju, Xiao-Yong Jin, Xiaohan Yang, Xiaolong Li, Xinyan Li, Yang Liu, Yang Xu, Yangzesheng Sun, Yannik Glaser, Yao Fehlis, Yasin Bakis, Yifan Liu, Yingdong Lu, Yingheng Tang, Yingtao Luo, Yitian Sun, Yixiao Kang, Yizhi Shen, Yolanne Yi Ran Lee, Youngsoo Choi, Youngwoo Cho, Yu Wang, Yuan-Tang Chou, Yukun Song, Yunyi Shen, Yushang Zhao, Zefang Liu, Zesheng Liu, Zhong Chen, Zhuo Chen, Zihan Zhu, Zineb Sordo, Zixi Hu, Zixing Song, Zukang Yang

Call for papers

This workshop brings together physical scientists and machine learning researchers who work at the intersection of these fields by:

  • applying machine learning to problems in the physical sciences -- physics, chemistry, astronomy, earth science, biophysics, and related sciences; and
  • using physical insights to understand and/or improve machine learning techniques, for instance building hybrid machine learning algorithms that leverage physical models with machine learning blocks to create interpretable and accurate predictive models.

Accepted contributions will be presented during in-person poster sessions during the workshop. Authors will also have the opportunity to upload an optional short video summary alongside their accepted paper on our website. Selected contributions will be offered 15-minute spotlight talks. We will highlight a small number of submissions containing exceptionally well-documented code and reproducible workflows with a Reproducibility Badge.

Sign up to volunteer as a reviewer: Our community’s success relies on our reviewers – we need you! Please help us ensure a high quality program by registering to review a few papers. Follow this link to nominate yourself and let us know how many papers you would be able to review.

Important dates

  • Submission Deadline: Friday, Aug 29, 2025, 23:59 AoE
  • Author (accept/reject) notification: Monday, Sept 22, 2025, 23:59 AoE
  • Registration support application deadline: October 24, 2025, 23:59 AoE
  • Camera-ready paper and poster deadline: November 14, 2025, 23:59 AoE
  • Workshop: December 6, 2025

Submission tracks

    1. Research: We invite contributions on either completed or high-quality work-in-progress original research in the following areas:

    • ML for Physics: Innovative applications of machine learning to the physical sciences; Machine learning model interpretability for obtaining insights into physical systems; Automating/accelerating elements of the scientific process (experimental design, data collection, statistical analysis, etc.).
    • Physics in ML: Strategies for incorporating scientific knowledge or methods into machine learning models and algorithms; Applications of physical science methods and processes to understand, model, and improve machine learning models and algorithms.
    • Other areas: Any other area related to the subject of the workshop, including but not limited to probabilistic methods that are relevant to physical systems, such as deep generative models, scientific foundation models, probabilistic programming, simulation-based inference, variational inference, causal inference, etc.
    2. Datasets & Benchmarks: We invite contributions describing a dataset and/or corresponding benchmarks at the intersection of ML and Physical Sciences, in particular showcasing the unique nature of physical datasets and forward models in the context of ML applications.

    3. Perspectives: We invite researchers to present compelling and grounded viewpoints on recent directions and open questions at the intersection of ML and Physical Sciences. This track encourages perspectives on past, present, or future challenges that can stimulate productive and respectful conversations on timely topics that will benefit from the ML4PS workshop's attendees' input. Papers should meet standard scientific rigor, including using evidence and reasoning to support claims, including relevant background and context, and attributing others' work via appropriate citations.

Submission instructions

Submissions should be short papers up to 4 pages in length (excluding references).

Full submission guidelines

Organizers

For questions and comments, please contact us at ml4ps@googlegroups.com.

Steering Committee

Team Members

Sponsors

Location

NeurIPS 2025 will take place at the San Diego Convention Center, 111 Harbor Dr, San Diego, CA 92101, United States.