Jim Halverson is an Associate Professor of Physics at Northeastern University in Boston, Massachusetts.
His research is at some of the interfaces between string theory, particle physics, cosmology, mathematics, and deep learning. He is particularly interested in the string landscape and its implications for particle physics and cosmology beyond their standard models. These implications often follow from the structure of extra-dimensional geometries, of which there are many possibilities. Halverson’s research therefore requires importing techniques from mathematics and computer science.
Recently, Halverson’s interest in the interface of physics and deep learning has continued to grow. To that end, he is a co-PI and serves on the institute board of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) and co-organizes Physics ∩ ML.
Board Member and co-PI, from 2020
NSF AI Institute for Artificial Intelligence and Fundamental Interactions
Associate Professor, from 2021
Northeastern University
Assistant Professor, 2015-2021
Northeastern University
Postdoctoral Fellow, 2012-2015
Kavli Institute for Theoretical Physics
PhD in Physics, 2012
University of Pennsylavania
My papers can be found on Google Scholar, including journal information.
Deconstructing the String Landscape
CEA Paris Saclay, November 2023.
to be determined.
Johannesburg Workshop on String Theory
University of Witwatersrand, September 2023.
declined due to family constraints.
String Phenomenology 2023
IBS-CTPU Daejeon, July 2023.
declined due to family constraints.
UNIST Workshop on Geometry, String Theory and Machine Learning
Ulsan University, July 2023.
Phi4 Theory as a Neural Network Field Theory.
Machine Learning for Lattice Field Theory and Beyond
Trento, June 2023.
declined due to family constraints.
Theoretical Physics for Deep Learning
Aspen Center for Physics, June 2023.
declined due to family constraints.
Canadian Mathematical Society Summer Meeting
Ottawa, June 2023.
Searching for Ribbons with Machine Learning.
At the Interface of Physics, Math, and AI
Pollica, May 2023.
declined due to family constraints.
Physics Colloquium
University of Crete, May 2023.
Machine Learning for Theoretical Physics and Math.
Physics Colloquium
University of Crete, May 2023.
Machine Learning for Theoretical Physics and Math.
Colloquium at Center of Mathematical Sciences and Applications
Harvard University, April 2023.
Unexpected Uses of Neural Networks: Field Theory and Metric Flows.
Theoretical Tests of the Landscape
University of Massachusetts, Amherst, April 2023.
Discussion on the Landscape from the Top Down.
Strings and Geometry 2023
University of Pennsylvania, March 2023.
Metric Flows and Calabi-Yau Metrics with Infinite-Width Neural Networks.
Theoretical Physics for Machine Learning
Aspen Center for Physics, March 2023.
declined due to family constraints.
String Data 2022
Cambridge University, December 2022.
Neural Network Metric Flows.
Heidelberg Math and ML Series
Heidelberg University, November 2022.
ML for Pure Mathematics.
Computational Differential Geometry and Its Applications in Physics
Simons Center for Geometry and Physics, November 2022.
Ricci Flow and Neural Network Gradient Descent.
Knot Theory Meets Computer Science
Dublin Institute for Advanced Study, November 2022.
Ricci Flow and Neural Network Gradient Descent.
Physics and Machine Learning
Nature Reviews Physics and Alan Turing Institute, October 2022.
Machine Learning and Theoretical Physics.
Lecture Series: Physics Meets Artificial Intelligence
School at LMU Munich, September 2022.
declined due to family constraints.
Seattle Snowmass Summer Meeting 2022
University of Washington, July 2022.
declined due to family constraints.
String Phenomenology 2022
University of Liverpool, July 2022.
Ricci Flow with Infinite Neural Networks.
Foundations of Machine Learning and its Applications for Scientific Discovery in Physical and Biological Systems Workshop
DC Metro Area, June 2022.
declined due to family constraints.
Lecture Series: Pre-SUSY 2022
University of Ioannina, June 2022.
Machine Learning for High Energy Theory.
Lecture Series: Pre-SUSY 2022
University of Ioannina, June 2022.
Machine Learning for High Energy Theory.
Workshop on Machine Learning and Mathematical Conjecture
Harvard University, CMSA, April 2022.
Machine Learning for Mathematics.
Physics Colloquium
University of Winnipeg, October 2021.
A Triangle of Influence: Bringing Together Physics, Pure Mathematics, and Computer Science.
Physics REBoot Venezuela
Virtual Bootcamp by COF Alumni USB and ICTP’s Physics Without Frontiers, September 2021.
A Triangle of Influence: Bringing Together Physics, Pure Mathematics, and Computer Science.
SUSY 2021
Institute of Theoretical Physics, Chinese Academy of Sciences, August 2021.
The String Landscape and Particle Remnants.
Nankai Symposium on Mathematical Dialogues
The Chern Institute, Nankai University, August 2021.
Statistics and Symmetries of Neural Networks and Quantum Fields.
Machine Learning: Where to Apply in Theoretical Physics
Bethe Forum Overview Seminar, University of Bonn, June 2021.
Recent Results at the Intersection of Machine Learning and Theoretical Physics.
PHENO 2021
University of Pittsburgh, May 2021.
Deep Learning Landscapes.
Lecture Series: Beijing Geometry and Physics Seminar
Yau Mathematical Science Center, Tsinghua University, May 2021.
Complexity, Physics, and Effective Theories of Deep Learning.
Lecture Series: Beijing Geometry and Physics Seminar
Yau Mathematical Science Center, Tsinghua University, May 2021.
Neural Network Theory: GPs, NGPs, and Neural Tangent Kernel
Lecture Series: Beijing Geometry and Physics Seminar
Yau Mathematical Science Center, Tsinghua University, May 2021.
Neural Network Theory: Scale-Invariance and Symmetries via Duality
IAIFI Colloquium
The NSF AI Institute for Artificial Intelligence and Fundamental Interactions, April 2021.
ML for Ab Initio Data: A Tour of Knots and Natural Language.
Accelerate Science Winter School 2021
Cambridge University, February 2021.
A Triangle of Influence: Bringing Together Physics, Pure Mathematics, and Computer Science.
Workshop on Algebraic Geometry and Machine Learning,
Tsinghua Sanya International Mathematics Forum, January 2021.
Knots and Natural Language.
String Data 2020,
CERN, December 2020.
NN-QFT Correspondence.
Physics Meets AI,
LMU Munich, September 2020.
Canceled due to COVID-19.
Machine Learning for Theory,
CERN, July 2020.
Canceled due to COVID-19.
New Ideas in String Phenomenology,
DESY, May 2020.
Canceled due to COVID-19.
Strings and Geometry 2020,
University of Utretcht, April 2020.
Canceled due to COVID-19.
American Physics Society (APS) April Meeting 2020,
Washington DC, April 2020.
String Theory and Deep Learning.
The String Swampland and Quantum Gravity Constraints on Effective Theories,
Kavli Institute for Theoretical Physics, March 2020.
Lessons and Challenges in the Landscape.
Deep Learning and Physics 2019,
Yukawa Institute for Theoretical Physics, October 2019.
Generative Models and Statistical Predictions in String Theory.
Lectures on Machine Learning and String Theory,
Osaka University, October 2019.
Machine Learning and the String Landscape.
Lectures on Machine Learning and String Theory,
Osaka University, October 2019.
Introduction to Machine Learning.
Lectures on Machine Learning and String Theory,
Osaka University, October 2019.
Computational Complexity in Theoretical Physics.
Geometry and Strings 2019,
Oxford University, September 2019.
F-theory on Singular Spaces.
Hammers and Nails 2019,
Weizmann Institute of Science, August 2019.
Applications of Machine Learning to String Theory.
SIAM Conference on Applied Algebraic Geometry,
University of Bern, July 2019.
Knot Theory and Machine Learning.
String Phenomenology 2019,
CERN, June 2019.
Complexity and Random Matrix Approximations.
Simons Collaboration on Special Holonomy in Geometry, Analysis, and Physics,
Kavli Institute for Theoretical Physics, April 2019.
Cosmological Questions for G2 Compactifications at Large N.
At the Crossroads of Machine Learning and Physics,
Kavli Institute for Theoretical Physics, February 2019.
Machine Learning Geometry and String Theory.
Machine Learning Landscape,
International Center for Theoretical Physics, Trieste, December 2018.
Complexity of Machine Learning and Landscapes.
Simons Summer Workshop,
Simons Center for Geometry and Physics, August 2018.
de Sitter Vacua and Computational Complexity.
String Theory Challenges in Particle Physics and Cosmology,
University of Bonn, July 2018.
Geometries, Agents, and Remnants.
Machine Learning and Physics,
Tsinghua University, July 2018.
Reinforcement Learning and the String Landscape.
String Phenomenology 2018,
Warsaw, July 2018.
String Theory and Data Science.
Strings 2018,
Okinawa, June 2018.
String Theory and Data Science.
Machine Learning in Geometry and Physics,
Yau Mathematical Science Center, TSIMF Sanya, June 2018.
On Finding Small Cosmological Constants with Deep Reinforcement Learning.
Strings, Geometry, and Black Holes,
King’s College London, April 2018.
Deep Reinforcement Learning and the Boundary of Weak Coupling.
Workshop on Data Science and String Theory,
LMU Munich, March 2018, with Fabian Ruehle.
Machine Learning Tools for String Theory
Workshop on Data Science and String Theory,
LMU Munich, March 2018.
Anomaly Detection: Mapping the IIB Lamppost with Reinforcement Learning.
Physics and Geometry of F-theory,
IFT-Madrid, March 2018.
A Large Ensemble of F-theory Geometries: the Weak, the Strong, and the Non-Higgsable
Workshop on String Field Theory and String Phenomenology
Harish-Chandra Research Institute, February 2018.
Big Data and the Landscape: A Case Study in F-theory.
String Phenomenology 2017
Virginia Tech, July 2017.
Universality in a Large Ensemble of Geometries.
Theoretical Advanced Studies Institute (TASI)
University of Colorado, Boulder, June 2017.
String Remnants 2.
Theoretical Advanced Studies Institute (TASI)
University of Colorado, Boulder, June 2017.
String Remnants 1.
International Conference on the Interconnection between Particle Physics and Cosmology,
Texas A&M, Corpus Christi, May 2017.
GUTs, Remnants, and the String Landscape.
Superconformal Field Theories in Four or More Dimensions,
Aspen Center for Physics, March 2017.
Dualities of Deformed N=2 SCFTs from Link Monodromy on D3-brane States.
Physics and Geometry of F-theory 2017
International Centre for Theoretical Physics, Trieste, February 2017.
Dualities from Braids and Landscapes from Trees.
The Mathematics and Physics of F-theory,
Virginia Tech, October 2016.
Dualities of Deformed N=2 SCFTs from Link Monodromy on D3-brane States.
Simons Collaboration on Special Holonomy in Geometry, Analysis, and Physics,
Background Lecture, Simons Center for Geometry and Physics, September 2016.
Gauge Enhancement in M-theory on G2 Spaces.
Simons Collaboration on Special Holonomy in Geometry, Analysis, and Physics,
Background Lecture, Simons Center for Geometry and Physics, September 2016.
More on Gauge Enhancement in M-theory on Calabi-Yau Varieties.
Geometry and Topology of Particle Physics,
The Fields Institute, Toronto, August 2016.
D3-brane SCFTs from N=2 Deformations, String Junctions, and Knots.
The Amsterdam String Workshop
University of Amsterdam, July 2016.
Non-Higgsable Clusters and Symmetry in the Landscape.
Special Holonomy Geometry, Mirror, and Supersymmetry,
National Science Foundation FRG Workshop, Harvard University, May 2016.
Gauge Enhancement and Landscapes in G2 Compactifications of M-theory.
F-theory at 20,
Walter Burke Institute, CalTech, February 2016.
Strong coupling and geometrically non-Higgsable seven-branes.
String-Pheno-Cosmo 2015,
Galileo Galilei Institute, October 2015.
The Complex Structure of the F-theory Landscape.
String Phenomenology 2015,
University of Madrid, June 2015.
Gauge Enhancement and Landscapes in G2 Compactifications of M-theory.
Stratified Spaces in Geometric and Computational Topology and Physics,
the University of Wisconsin, Madison, April 2015.
Kodaira’s Alternative to Grand Unification.
String / M-Theory Compactifications and Moduli Stabilization,
University of Michigan, March 2015.
Symmetry in the Landscape, Non-Higgsable Clusters, and the Standard Model.
Physics and Geometry of F-theory,
MPI Munich, February 2015.
Symmetry in the Strongly Coupled Landscape.
Physics Colloquium,
Northeastern University, February 2015.
Formal Theory and its Applications to the Standard Model and Beyond.
Physics Colloquium,
Baylor University, January 2015.
Setting Sail in the String Landscape.
Hidden Sector Dark Matter,
Michigan Center for Theoretical Physics, November 2014.
Hidden and Visible Sectors from Non-Higgsable Clusters.
Model Building in the LHC Era,
Aspen Center for Physics, July 2014.
Theoretically Motivated Electroweak Exotics in String Theory.
Geometry and Physics of F-theory,
Heidelberg University, February 2014.
Non-Abelian Gauge Symmetry and the Higgs Mechanism in F-theory.
APS Divisional Meeting,
UC Santa Cruz, August 2013.
New Motivation for WIMP Dark Matter.
Simons Summer Workshop,
Simons Center for Geometry and Physics, July 2013.
Matter in F-theory from Singular Elliptic Fibrations.
String Phenomenology 2011,
the University of Wisconsin, Madison, August 2011.
Instantons in F-theory from Heterotic Duality.
String Vacuum Project Meeting,
University of Pennsylvania, May 2011.
Three Looks at Instantons in F-theory.
String Vacuum Project Meeting,
Ohio State University, November 2014.
Approaching the Landscape: Computability of IIB / F-theory Instantons and Insights from MSSM-containing quivers.
String Vacuum Project Meeting,
Kavli Institute for Theoretical Physics, May 2010.
Instanton Effects in Semi-Realistic MSSM Quivers and F-theory.
IAIFI Workshop,
IAIFI, 2023.
chair of the organizing committee.
IAIFI Summer School,
IAIFI, 2023.
chair of the organizing committee.
IAIFI Workshop,
IAIFI, 2022.
chair of the organizing committee.
IAIFI Summer School,
IAIFI, 2022.
chair of the organizing committee.
Machine Learning: where to apply in Theoretical Physics,
Bethe Forum, University of Bonn, 2022.
member of the organizing committee.
A Deep-Learning Era of Particle Theory,
Mainz Institute for Theoretical Physics, 2022.
member of the organizing committee.
String Phenomenology 2021,
Northeastern University, 2021.
member of the organizing committee.
String Phenomenology 2020,
Northeastern University, 2020.
member of the organizing committee.
Neural Networks and the Data Science Revolution: from Theoretical Physics to Neuroscience, and Back,
Simons Center for Geometry and Physics, January 2020.
member of the organizing committee.
Strings, Geometry, and Data Science,
Simons Center for Geometry and Physics, January 2020.
member of the organizing committee.
String Theory and the Hidden Universe,
Aspen Center for Physics, June 2019.
member of the organizing committee.
Modern Trends in Particle Physics,
A conference in honor of Pran Nath, Northeastern University, May 2019.
member of the organizing committee.
Physics ∩ ML,
Microsoft Research, April 2019.
member of the organizing committee.
PASCOS 2018,
Case Western Reserve University, June 2018.
convener of session on “Unification and String Theory.”
Workshop on Data Science and String Theory,
Northeastern University, November 2017.
member of the organizing committee.
Workshop on String/M-theory Compactifications and Particle Physics,
Michigan Center for Theoretical Physics, March 2015.
member of the organizing committee.
String Vacuum Project Spring Meeting,
University of Pennsylvania, May 2011.
co-organizer.
I teach physics courses at Northeastern University, including:
GitHub repositories contain the most recent iteration of the course. Information regarding past courses are available upon request.