The workshop on Topological Data Analysis and Machine Learning for Physics, held in Taipei from May 6–8, 2026, brings together leading researchers working at the intersection of modern data science and fundamental physics. The speakers span a wide range of topics — from topological data analysis in gauge theories and QCD, to machine learning techniques for particle physics including jet tagging, generative inference, and diffusion models, to applications in lattice field theories, quantum computing and condensed matter. The workshop aims to foster cross-disciplinary dialogue and chart new directions for data-driven approaches in theoretical and experimental physics.
Invited speakers:
Luigi Del Debbio (University of Edinburgh)
Mathis Gerdes (MIT)
Jeff Giansiracusa (Durham/Erlangen)
Ryu Hayakawa (Kyoto University)
Jae-Hun Jung (POSTEC)
Gurtej Kanwar (Edinburgh)
Vinicius Mikuni (KMI, Nagoya)
Huilin Qu (CERN)
Alberto Ramos (Universitat de Valencia)
Fernando Romero-Lopez (Bern)
Andrea Tirelli
David Shih (Rutgers)
Muhammad Usman (Melbourne)
Lingxiao Wang (RIKEN)
TBC
Mathis Gerdes (MIT)
Jeff Giansiracusa (Durham/Erlangen)
Ryu Hayakawa (Kyoto University)
Jae-Hun Jung (POSTEC)
Gurtej Kanwar (Edinburgh)
Vinicius Mikuni (KMI, Nagoya)
Huilin Qu (CERN)
Alberto Ramos (Universitat de Valencia)
Fernando Romero-Lopez (Bern)
Andrea Tirelli
David Shih (Rutgers)
Muhammad Usman (Melbourne)
Lingxiao Wang (RIKEN)
TBC
Organizers:
Kai-Feng Chen
Miranda C. N. Cheng
Cheng-Wei Chiang
Marco Fazzi
Brandon Robinson
Gary Shiu