Previous Talks

(including videos and slides)

2024

CECAM55: Fostering Computational Science for Societal Progress, EPFL, Lausanne, Switzerland, September 2-4, 2024. (Thanks, Mario, for subsituting for me!)

CECAM workshop “ML Potentials: From Interface to Solution”, Ruhr-Universität, Bochum, Germany, August 27-29, 2024. (Thanks, Jigyasa, for substituting for me!)

CAMD Summer School on Electronic Structure Theory and Materials Design, Helsingør, Denmark, August 18-23, 2024.

HAMLET-PHYSICS Conference/Workshop, University of Copenhagen, August 19-21, 2024.

The 5th International Conference on Data-Driven Plasma Science, UC Berkeley, August 12-16, 2024. (Thanks, Elyssa, for substituting for me!)

The Role of Theories, Simulation, and Machine Learning in Materials Discovery, Gordon Research Conference, Newry, Maine, July 21-26, 2024.

UChicago AI+Science Summer School, July 15-19, 2024.

Symposium on “Machine learning, simulations and experiments for ultra low-power materials and devices”, Spetses, Greece, July 7-12, 2024.

AI≡Science: Strengthening the Bond Between the Sciences and Artificial Intelligence, Simons Institute at UC Berkeley, June 10-14, 2024. (slides)

Simons Foundation’s ML@Flatiron Seminar Series, New York, NY May 14, 2024.

MIT CSE Community Seminar, April 5 noon-1pm, MIT 45-432, 2024.

Workshop on Machine Learning in Electronic-Structure Theory, IMSI at UChicago, March 25-29, 2024.

Seminar, Simons Center for Computational and Physical Chemistry, New York University, March 25, 2024.

APS March Meeting, Minneapolis, MN, March 3-8, 2024. * Monday: Adriana * Tuesday: Tuong and YuQing * Thursday: Tess and Elyssa

BIDMAP Seminar, UC Berkeley, February 1, 2024.

2023

[REMOTE] Materials Project Seminar, December 14, 2023. (video)

MRS Fall Meeting, Invited Speaker, November 28, 2023.

Applied AI Speaker Series, Argonne National Laboratory, November 15, 2023.

AI in Science Seminar Series, University of Chicago, November 14, 2023.

MolML, MIT, November 8, 2023.

Guest Lecture 6.S898 Deep Learning, MIT, October 3, 2023.

[REMOTE] Panel Discussion on Formal Methods in the Service of Science, IBM 24 Hours of Science, September, 20, 2023.

[REMOTE] Seminar, ORIGINS Data Science Lab (ODSL), Technical University in Munich, August 18, 2023.

GraphEx Workshop, MIT Endicott House, August 15-16, 2023.

IAIFI Summer Workshop, Northeastern University, August 14–18, 2023. (video)

Lecture for Summer Geometry Initiative, MIT, August 3, 2023.

ICML Workshop on TAG-ML, Honolulu, HI, July 28th, 2023. (video)

RSS Workshop on Symmetries in Robot Learning, July 10th, Daegu, Republic of Korea, July 10th, 2023. (video)

MIT Numerical Methods for Partial Differential Equations Seminar, MIT 2-449 4:30-5:30 pm ET, May 10, 2023.

[REMOTE] ML4Materials, Workshop @ ICLR ‘23, Fully Virtual, Kigali Rwanda, May 4 and 5, 2023 (video).

Boston Symmetry Day, Northeastern University, April 7, 2023.

Learning and Emergence in Molecular Systems, IPAM at UCLA, January 23-27, 2023. (video) (slides)

AI Institute for Dynamic Systems Seminar, University of Washington, January 6th, 2023 (video).

2022

Catalyst Conversations, December 15, 2022. (video)

[REMOTE] AI4Science Seminar, Chalmers University of Technology, December 8th, 2022.

[REMOTE] NeurIPS AI4Science Workshop, December 2nd, 2022.

MIT Path of Professorship Workshop – Session: Negotiating the Offer, November 19th, 2022.

[REMOTE] Boston University Materials Day, October 14, 2022.

[REMOTE] CECAM Workshop on Charting large materials dataspaces: AI methods and scalability, CECAM-FR-RA, Grenoble, France, October 10-12, 2022.

[REMOTE] Warwick Centre for Predictive Modelling seminar series, University of Warwick, October 3, 2022.

[REMOTE] Physics-informed machine learning seminar series, Los Alamos National Laboratory, September 29, 2022.

[REMOTE] Symposium on the Future of Computing Research, Early Career Roundtable (video), September 12, 2022.

Barcelona Methods in Molecular Simulation and Machine Learning Workshop (video), Barcelona Biomedical Research Park, CompBioMed, Barcelona, Spain, July 14-16, 2022.

Swiss Equivariant Learning Workshop, CO2 - EPFL, Lasanne, Switzerland, July 11-14, 2022.

Variational Learning for Quantum Matter, Bernoulli Workshop - EPFL, Lausanne, Switzerland, July 4-8, 2022.

NSF Workshop on the Foundations of Machine Learning and its Applications for Scientific Discovery in Physical and Biological Systems , June 24, 2022. (video)

APS March Meeting: Session Z43, March 18, 2022.

McGill University Physics Colloquium, February 25, 2022. (video)

2021

[REMOTE] ELLIS Machine Learning for Molecule Discovery Workshop, December 13, 2021.

Tutorial for Symmetry-Aware Neural Networks for the Material Sciences, MRS 2021 Fall Meeting, November 29, 2021.

[REMOTE] MIT IAIFI Internal Seminar, November 19, 2021.

[REMOTE] Hamilton Institute / MIT CINCS Seminar, November 17, 2021.

[REMOTE] Special Session on Theoretical and Applied perspectives in Machine Learning, AMS Fall Western Sectional Meeting, October 23, 2021.

[REMOTE] Leuven.AI Seminar at KU Leuven, October 7th, 2021.

[REMOTE] Machine Learning Materials Science, ACS Fall Meeting, August 23, 2021. (slides)

[REMOTE] Midday Science Cafe, LBNL and UC Berkeley, May 20, 2021. (video)

[REMOTE] Guest Lecture for 3.100J, MIT, May 17, 2021, 11am ET.

[REMOTE] CMU AI in Physics Planning Institute Seminar, March 31, 2021.

[REMOTE] Cal State Los Angeles Physics Colloqium, March 25, 2021.

[REMOTE] APS March Meeting Session - C21: Machine Learning for Quantum Matter III, March 15, 2021.

[REMOTE] MIT EECS Seminar, February 25, 2021.

[REMOTE] UCB Chemical and Biomolecular Engineering Seminar, February 4, 2020

2020

[REMOTE] Seminar on Euclidean Neural Networks for Physics ∩ ML, November 18, 2020. (slides // video)

[REMOTE] Lecture + Tutorial on e3nn for the Machine learning in Physics, Chemistry and Materials discussion group (MLDG) at the University of Cambridge, November 9, 2020.

[REMOTE] Tutorial on e3nn for the Scientific Machine Learning Mini-Course hosted by CMU, November 5, 2020.

[REMOTE] Keynote (slides) for Applied Computational Sciences symposium (ACOS), October 28, 2020.

[REMOTE] Poster at UC Southern Hub: Frontiers in Machine Learing for the Physical Sciences, October 26, 2020

[REMOTE] Panelist (talk / discussion) on Architecture Design at The Analytical Foundations of Deep Learning Workshop hosted by CDTI and UC Berkeley, October 23, 2020.

[REMOTE] Lightning Talk on e3nn at the New York Scientific Data Summit, October 20-23, 2020.

[REMOTE] What you get for free with Euclidean Neural Networks, Seminar at FHI Berlin (slides), September 23, 2020.

[REMOTE] Unintended Features of E(3)NNs, Workshop on Equivariance and Data Augmentation (video // slides), University of Pennsylvania, September 4, 2020.

[REMOTE] Lecture on Symmetry and Equivariance in ML, Berkeley Lab Deep Learning School (video // slides), Berkeley Lab, September 3, 2020.

[REMOTE] AI/ML for ALS Synchrotron Science Innovation forum (slides), Berkeley Lab, August 11, 2020.

[REMOTE] 1st Workshop on Scientific-Driven Deep Learning (SciDL) (video // slides), July 1, 2020

[REMOTE] Applied Artificial Intelligence Initiative Seminar (slides), UC Santa Cruz, April 8, 2020, Santa Cruz, CA

Center for Computing Research Seminar, Sandia National Laboratory, March 11, 2020, Albuquerque, NM

CECAM-Lorentz workshop on Computing Complex Mechanical Systems, EPFL, January 22-24, 2020, Lausanne, Switzerland

Applied Machine Learning Days – AI and the Molecular World (video), EPFL, January 27-28, 2020, Lausanne, Switzerland

2019

Distinguished Young Academics Data Scientists (DYADS) eScience Institute Seminar (video), University of Washington, Seattle, WA

E(3) Equivariant Neural Network Tutorial, IPAM at UCLA, Los Angeles, CA

Workshop I: From Passive to Active: Generative and Reinforcement Learning with Physics, (video // slides // all talks), IPAM at UCLA, Los Angeles, CA

“People’s Choice” Winner, Berkeley Lab Postdoc Research SLAM! (video // full show), Berkeley Lab, Berkeley, CA

Euclidean Neural Networks for emulating ab initio calculations and generating atomic geometries – Machine Learning for Quantum Matter, Nordita, Sweden

Toward the systematic generation of hypothetical atomic structures: Neural networks and geometric motifs – CNMS User Meeting, Oak Ridge National Laboratory, Oak Ridge, TN

Toward the systematic generation of hypothetical atomic structures: Neural networks and geometric motifs – MolKin2019, Freie Universität Berlin, Germany

Tensor field networks – Machine Learning in Materials Genome, AKSS, Spetses, Greece

Toward the systematic generation of hypothetical atomic structures: Neural networks and geometric motifs – Structure in the Microworld at TGDA@OSU

Tensor Field Networks – Foundational and Applied Data Science for Molecular and Materials Science and Engineering at Lehigh University

Tensor Field Networks – Informal Seminar at the Flatiron Insitute, NYC

A case study of neural networks for scientific data: generating atomic structures – APS March Meeting (abstract)

Toward the systematic generation of hypothetical atomic structures: Neural networks and geometric motifs – SIAM CSE (abstract)

2018

Tensor Field Networks (slides) – NeuRIPs Molecules and Materials Workshop

Becoming an Atomic Architect (slides // video)– Computational Materials at Berkeley

Toward the Systematic Generation of Hypothetical Atomic Structures: Neural Networks and Geometric Motifs – Molecular Foundry Seminar (Berkeley Lab)

ML for Atomic Systems: Challenges and Applications – ML4Science Workshop (Berkeley Lab)

Tensor Field Networks – Google Tech Talk

2017

Ab Automated Ab Initio Search for Ferroelectrics (slides) – Qualifying Exam UC Berkeley Physics Department

An Automated Ab Initio Framework for Identifying New Ferroelectrics – APS March Meeting

2016

Geometry and Electronic Structure of Metal-Organic Chalcogenide Assemblies (slides) – Molecular Foundry Inorganic Facility Seminar

An Automated Ab Initio Approach for Identify Small Band Gap Ferroelectrics – APS March Meeting

2015

Ab Initio Simulations of the Structure and Energetics of Harmonic Honeycomb Iridates – APS March Meeting

2014

A New Spin-anisotropic Harmonic Honeycomb Iridate (slides) – Molecular Foundry Theory Facility Seminar

Spin Ordering Studies of Edge-sharing Iridates – APS March Meeting

2012

Beam Target Optimization for DAEdALUS (slides)– APS April Meeting

2011

Building Neutrino Detectors (slides) – MIT Family Weekend Physics Reception

Light Detection in Liquid Argon Time Project Chambers – Fermilab New Perspectives Conference

Media

The task of magnetic classification suddenly looks easier - November 29, 2022.

Basics2Breakthroughs: Improving machine learnign to make big discoveries - August 9, 2021.

MIT News: A streamlined approach to determining thermal properties of crystalline solids and alloys - April 1, 2021.

ICIAM TV: Lawrence Berkeley National Laboratory - Computational Research Division - July 12, 2019.

Posters

2016

A Self-Assembled Bulk 2D Semiconductor (pdf) – Molecular Foundry Users Meeting

2015

Designing Electronic Properties of Metal-Organic Chalcogenides (pdf) – Molecular Foundry Users Meeting

2011

Acrylic Lightguides for Use in Liquid Argon Time Projection Chambers (pdf) – Fermilab Users Meeting