Presentations

119 presentations

2025

18 Mar 2025 — "TBD" at APS Global Physics Summit 2025 (Anaheim, CA)
18 Feb 2025 — "How AI is raising the ambition of physicists" at DESY Physics Colloquium (DESY Hamburg)
28 Jan 2025 — "Emerging Patterns in AI for Science" at Ken Kennedy Institute Distinguished Lecture Series (Rice University)
16 Jan 2025 — "Vision for the next 25 years based on experiences" at PhyStat25 (CERN)

2024

17 Dec 2024 — "Roundtable on P5 and future particle physics programs" at US LUA Annual Meeting (SLAC National Accelerator Laboratory)
20 Sep 2024 — "The intersection of statistics, machine learning, and the physical sciences" at STAMPS@CMU Research Center Launch Event (Carnegie Mellon University, Pittsburgh)
26 Jul 2024 — "Structured Probabilistic Inference & Generative Modeling in Physics" at Structured Probabilistic Inference & Generative Modeling workshop at ICML (Vienna, Austria)
12 Jul 2024 — "Keynote" at SciPy 2024 (Tacoma, WA)
13 Jun 2024 — "Generative AI Panel" at Helmholtz AI Conference 2024 (Düsseldorf, Germany)
12 Jun 2024 — "Keynote" at Helmholtz AI Conference 2024 (Düsseldorf, Germany)
15 May 2024 — "Opening talk" at PhyStat SBI (Munich)
03 May 2024 — "AI for Fundamental Physics" at EuCAIFConf (Amsterdam)
25 Apr 2024 — "Grand combinations at HL-LHC & FAIROS-HEP" at LPC EFT Workshop (Notre Dame)
27 Feb 2024 — "Combining human and artificial intelligence for predictive modeling" at National Predictive Modeling Tool Initiative Annual Meeting (Raleigh, NC)
26 Feb 2024 — "Injecting knowledge and extracting insight: promise and perils" at Explainable AI for Science (XAI4Sci) workshop AAAI 2024 (Vancouver, Canada)
06 Feb 2024 — "Data, Decisions, and Generative AI" at UW-Madison Research Bazaar (University of Wisconsin--Madison)

2023

14 Dec 2023 — "Examples of AI in Physics" at AI 4 Scientific Discovery workshop at NeurIPS (New Orleans)
05 Dec 2023 — "14 years of HistFactory" at PyHF Workshop (CERN)
05 Dec 2023 — "Introducing the FAIROS-HEP Research Coordination Network" at PyHF Workshop (CERN)
27 Nov 2023 — "Learning, Physics, and Graphs" at Learning on Graphs Conference (Virtual)
17 Nov 2023 — "Simulation-Based Inference: The intersection of mechanistic models and inverse problems" at Biomedical Engineering Engineering Seminar (University of Wisconsin--Madison)
16 Nov 2023 — "A practical framework for EFT fits with published likelihoods" at LHC EFT Working Group (CERN)
16 Nov 2023 — "Introducing the FAIROS-HEP Research Coordination Network" at LHC EFT Working Group (CERN)
03 Nov 2023 — "Closeout / Conference Synthesis" at Hammers and Nails 2023 (Ascona, Switzerland)
10 Oct 2023 — "How AI is raising the ambition of physicists" at Hans Jensen Lecture (Heidelberg)
03 Jul 2023 — "From the Higgs boson discovery to simulation-based inference" at GRAPPA 10th Anniversary (Amsterdam)
23 Jun 2023 — "Panel: Scientific Discovery and the Environment" at The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 (CVPR) (Vancouver, Canada)
13 Jun 2023 — "Simulation-Based Inference" at Statistical Challenges in Modern Astronomy VIII (Penn State)
08 May 2023 — "Radically different futures for HEP enabled by AI/ML" at CHEP 2023 (Norfolk)

2022

09 Nov 2022 — "Translational AI" at A Coordinated Ecosystem for HL-LHC Computing R&D (Washington D.C.)
22 Oct 2022 — "Searching for a needle in a haystack: lessons from particle physics" at NASA Unidentified Aerial Phenomena Study Team (Washington D.C.)
18 Sep 2022 — "Machine Learning for Science: Bridging Data-driven and Mechanistic Modelling" at Machine Learning for Science: Bridging Data-driven and Mechanistic Modelling (Dagstuhl, Germany)
23 Jul 2022 — "The intersection of simulation-based inference and agent based modelling (Invited Talk)" at AI4ABM Workshop at the International Conference on Machine Learning (ICML) 2022 (Virtual)
15 Jun 2022 — "Simulation-based inference" at Challenges and Prospects of ML for the Physical Sciences (Flatiron Institute, New York)
14 Jun 2022 — "No Free Lunch: Setting our Expectations for Model-Independent Searches" at Beyond Models (Bonn, Germany)
07 Apr 2022 — "Data Science is on its feet, now where is it going?" at RED Talks (University of Wisconsin-Madison)
08 Mar 2022 — "Causality at the intersection of simulation, inference, science, and learning" at Understanding the nature of Inference: Correlation and Causation. The Franke Program in Science ant the Humanities (Yale (Virtual))
07 Mar 2022 — "How ML is enabling an information-theoretic approach to data analysis and the design of experiments" at APS March Meeting (Las Vegas, NV)
18 Feb 2022 — "Vignettes in physics-inspired AI research" at NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) Public Colloquia (MIT + Virtual)
07 Feb 2022 — "Accelerating Simulation-based Inference" at Seminar for A3D3 (Accelerated Artificial Intelligence Algorithms for Data-Driven Discovery) ((Virtual))
26 Jan 2022 — "Connections and cross pollination from quarks to the cosmos" at Learning and Emergence in Molecular Systems (IPAM, UCLA)

2021

15 Dec 2021 — "Incorporating uncertainty at the LHC" at Information and Statistics in Nuclear Experiment and Theory (ISNET 8) (Michigan State University (Virtual))
13 Dec 2021 — "Inductive bias: lessons learned from physics" at Physical Reasoning and Inductive Biases for the Real World workshop at NeurIPS 2021 (Virtual)
16 Nov 2021 — "Simulation-based inference for gravitational wave astronomy" at Workshop III: Source Inference and Parameter Estimation in Gravitational Wave Astronomy (Institute for Pure and Applied Mathematics (IPAM))
06 Nov 2021 — "Panel: Sins and marvels of AI research" at ML in PL (Machine Learning in Poland) (Virtual)
03 Nov 2021 — "A call to action: Honoring PHYSTAT's 20 year old agreement" at PhyStat Systematics (Virtual)
03 Nov 2021 — "Three approaches to Systematics with Machine Learning" at PhyStat Systematics (Virtual)
18 Sep 2021 — "AI and Physics" at Sparks! Serendipity Forum (CERN)
13 Sep 2021 — "TBD" at STFC Summer School on Data Intensive Science 2021 (Durham / Virtual)
18 Aug 2021 — "Studying the effectiveness of inductive bias with a physics-inspired generative model" at Mathematical and Scientific Machine Learning (MSML21) (Virtual)
18 Aug 2021 — "Systematics in the context of machine learning" at PhyStat-Systematics (Virtual)
04 Aug 2021 — "Simulation-based inference: recent progress and open questions" at Statistical Approaches to Understanding Modern ML Methods (Institute for the Foundations of Data Science, University of Wisconsin-Madison)
04 Aug 2021 — "Machine learning round-table discussion" at A Virtual Tribute to Quark Confinement and the Hadron Spectrum 2021 (Virtual)
12 Jul 2021 — "Explorations at the Physics-AI Interface" at From Quarks to Cosmos with AI 2021 (NSF AI Planning Institute for Data-Driven Discovery in Physics) (Virtual)
08 Jul 2021 — "Thoughts on the expressive power and inductive bias of DeepSets and Tree-Based models" at ML4Jets (Virtual)
08 Jul 2021 — "Simulation-Based Inference" at Applied Cutting-Edge Machine Learning in Cosmology and Particle Physics @ PASC21 (Virtual)
07 Jul 2021 — "MadMiner: a python based tool for simulation-based inference in HEP" at PyHEP 2021 (Virtual)
05 May 2021 — "Explorations at the Physics ∩ ML Interface" at Physics ∩ ML seminar series ((Virtual))
27 Apr 2021 — "Analysis Systems Overview" at IRIS-HEP Annual PI/EB Meeting ((Virtual))
26 Apr 2021 — "An AI revolution in science? Using machine learning for scientific discovery" at University of Cambridge Accelerate Programme for Scientific Discovery ((Virtual))
22 Apr 2021 — "Towards a white paper on public likelihoods" at LHC Re-interpretation Forum ((Virtual))
02 Apr 2021 — "Invited Keynote for AISTATS: Simulation-Based Inference" at AISTATS ((Virtual))
25 Mar 2021 — "Graph Deep Learning for Physics" at Università della Svizzera ((Virtual) Università della Svizzera)
09 Mar 2021 — "Probabilistic Machine Learning for the Physical Sciences" at Advanced Topics in Machine Learning Course (Oxford University)
02 Mar 2021 — "Machine Learning for Precision Measurements" at Unveiling hidden Physics Beyond the Standard Model at the LHC ((Virtual))
22 Feb 2021 — "Quarks, hierarchical clustering, and combinatorial optimization" at Deep Learning and Combinatorial Optimization (Institute Pure and Applied Mathematics (IPAM) (virtual))
18 Feb 2021 — "MadMiner tutorial" at (Re)interpreting the results of new physics searches at the LHC ((Virtual))
11 Jan 2021 — "MadMiner: Machine learning–based inference for particle physics" at LHC EFT Working Group (CERN (Virtual))

2020

18 Dec 2020 — "Some fun examples from the intersection of machine learning and physics" at ML in PL (Poland (Virtual))
08 Dec 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at AI for Atoms (Oak Ridge National Laboratory (Virtual))
03 Dec 2020 — "Machine Learning for high energy physics on and off the lattice" at ECT* Colloqium (European Center for Theoretical Studies in Nuclear Physics and Related Areas) (Virtual)
30 Oct 2020 — "New experimental analysis techniques" at Higgs2020 (Virtual)
26 Oct 2020 — "End-to-End Analysis Vision & AS Grand Challenge" at IRIS-HEP Future Analysis Systems and Facilities Blueprint Workshop (Virtual)
19 Oct 2020 — "Vision: Physics, Machine Learning, and Computing" at 2020 Accelerated Artificial Intelligence for Big-Data Experiments Conference (NCSA (Virtual))
14 Oct 2020 — "Likelihood publishing, RECAST, and simulation-based inference" at PhyStat / CERN EP-IT Data science seminar (CERN (Virtual))
24 Sep 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at NYU Physics Colloquium (New York University (Virtual))
22 Sep 2020 — "Reusable Workflows, active learning, and simulation-based inference" at UCI Symposium on Reproducibility in Machine Learning (Irvine, CA (Virtual))
26 Aug 2020 — "Constraining EFTs and Dark Matter with Simulation-based Inference" at BSM PANDEMIC (Fermilab (Virtual))
10 Aug 2020 — "Lectures on Statistics" at 15th joint Fermilab-CERN Hadron Collider Summer School (Fermilab (Virtual))
21 Jul 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at Machine Learning in Science 2020 (Eberhard Karls Universität Tübingen (Virtual))
17 Jul 2020 — "Likelihood-based models for Simulation-based Inference" at ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (Vienna, Austria (Virtual))
17 Jul 2020 — "Graphs, Trees, and Sets: structured data in physics" at ICML Workshop on Graph Representation Learning (Vienna, Austria (Virtual))
09 Jul 2020 — "Panel Discussion: A community perspective on Equity in HEP" at High Energy Physics Advisory Panel (Virtual)
08 Jul 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at ELLIS SOCIETY: AI4Science Kickoff Workshop (Amsterdam, Netherlands (Virtual))
02 Jul 2020 — "The interplay of Math, Physics, and Machine Learning" at IST seminar series Mathematics, Physics & Machine Learning (Lisbon, Portugal (Virtual))
31 May 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at Tel Aviv University Physics Department Colloquium (Tel Aviv, Israel (Virtual))
29 May 2020 — "Analysis Systems Plans and Goals Closeout" at IRIS-HEP Team Retreat ((Virtual))
29 May 2020 — "Analysis Grand Challenge Closeout" at IRIS-HEP Team Retreat ((Virtual))
28 May 2020 — "Analysis Grand Challenge Proposal" at IRIS-HEP Team Retreat ((Virtual))
28 May 2020 — "IRIS-HEP Innovative Algorithms: R&D and Machine Learning for Jets" at IRIS-HEP Team Retreat ((Virtual))
27 May 2020 — "Analysis Systems Overview and Plans" at IRIS-HEP Team Retreat ((Virtual))
07 May 2020 — "How machine learning can help us get the most out of our highest fidelity physical models" at MIT Physics Department Colloquium (Irvine, CA (Virtual))
17 Mar 2020 — "Future Analysis Systems" at Joint US ATLAS - US CMS Meeting on Facility R&D (Remote)
16 Mar 2020 — "Reusable workflows in particle physics" at Workshop on Accelerating Scientific Discovery through Advanced and Automated Workflows (National Academy of Sciences)
05 Mar 2020 — "Machine Learning and Physics" at Special QU-PCD Colloquium at DESY (CANCELED due to COVID19) (DESY)
03 Mar 2020 — "Machine Learning for Effective Field Theories" at PREFIT20: PRecision Effective FIeld Theory School (DESY)
28 Jan 2020 — "HEPData and IRIS-HEP" at HEPData Advisory Board (IPPP Durham)

2019

19 Nov 2019 — "Flows three ways" at Deep Learning for Physics Seminar Series at Princeton Center for Theoretical Physics (Princeton)
17 Oct 2019 — "Simulation-based inference, interpretability, and experimental design" at Workshop on Interpretable Learning in Physical Sciences Part of the Long Program Machine Learning for Physics and the Physics of Learning (UCLA)
05 Oct 2019 — "Particle Physics in the context of Data Science" at The 6th IEEE International Conference on Data Science and Advanced Analytics (Washington, DC)
30 Sep 2019 — "What does the Revolution in Artificial Intelligence Mean for Physics?" at Joint PITT-CMU Physics Department Colloquium (Carnegie Mellon University)
27 Sep 2019 — "Simulation-based inference, causality, and active learning" at AI and the Scientific Method, ETH, Zurich (ETH, Zurich)
09 Sep 2019 — "The interplay between physically motivated simulations and machine learning" at Machine Learning for Physics and the Physics of Learning Long Program at IPAM (IPAM)
31 Jul 2019 — "Overview and Future directions for ML in particle and astro physics" at Hammers & Nails 2019 (Weizmann Institute)
24 Jun 2019 — "Future areas of focus for ML in particle physics" at ATLAS Software and Computing Week (NYU)
21 Jun 2019 — "Analysis Systems Perspectives and Goals" at Analysis Systems R&D on Scalable Platforms Blueprint meeting (NYU)
19 Jun 2019 — "Reinterpretation Roadmap" at Analysis Systems Topical Meeting (NYU)
14 Jun 2019 — "Advances in Deep Learning motivated by Physics Problems" at Theoretical Physics for Deep Learning (Long Beach, CA)
29 May 2019 — "The Primacy of Experiment" at The Universe Speaks in Numbers (Intitute for Advanced Study)
01 May 2019 — "Future areas of focus for ML in particle physics" at Gotham City Physics X ML (Flatiron Institute)
15 Apr 2019 — "Future areas of focus for ML in particle physics" at 3rd IML Machine Learning Workshop (CERN)
18 Mar 2019 — "Overview of Likelihood-Free Inference for Physics" at Likelihood-Free Inference Workshop (Flatiron Institute, NYC)
13 Mar 2019 — "Experiences with deep learning in particle physics" at Sackler Colloquia on Deep Learning and Science (National Academy of Science, Washington DC)
07 Mar 2019 — "What does the Revolution in Artificial Intelligence Mean for Physics?" at UC Riverside Physics Colloquium (UC-Riverside)
12 Feb 2019 — "Panel Discussion on Machine Learning and Physics" at At the Crossroad of Physics and Machine Learning (KITP)
06 Feb 2019 — "IRIS-HEP Analysis Systems" at IRIS-HEP Steering Board Meeting
25 Jan 2019 — "Inverting simulation: experiences with inverse problems in particle physics" at MATH + X Symposium on Inverse Problems and Deep Learning in Space Exploration (Rice University)

2018

19 Sep 2018 — "What does the Revolution in Artificial Intelligence Mean for Physics?" at Jefferson Lab Colloquium (Jefferson Lab)
07 Sep 2018 — "What does the Revolution in Artificial Intelligence Mean for Physics?" at Harvard Physics Colloquium (Harvard University)