Data Analysis and Machine Learning for Physics Workshop

Asia/Taipei
Description

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
 
Organizers:
 
Kai-Feng Chen
Miranda C. N. Cheng
Cheng-Wei Chiang
Marco Fazzi
Brandon Robinson
Gary Shiu
Participants
    • 9:30 AM 10:30 AM
      Gurtej Kanwar 1h
    • 10:30 AM 11:00 AM
      coffee/tea 30m
    • 11:00 AM 12:00 PM
      Luigi Del Debbio 1h
    • 12:00 PM 2:00 PM
      Lunch 2h
    • 2:00 PM 3:00 PM
      Mathis Gerdes 1h
    • 3:30 PM 4:30 PM
      Fernando Romero-Lopez 1h
    • 4:30 PM 5:30 PM
      Alberto Ramos Martinez 1h
    • 6:00 PM 7:00 PM
      Reception 1h
    • 9:30 AM 10:30 AM
      Huilin Qu 1h
    • 10:30 AM 11:00 AM
      coffee/tea 30m
    • 11:00 AM 12:00 PM
      Muhammad Usman 1h
    • 12:00 PM 3:00 PM
      Gong Show (PDF attached) 3h
    • 3:30 PM 4:30 PM
      Ryu Hayakawa 1h
    • 4:30 PM 5:30 PM
      Jae-Hun Jung 1h
    • 6:30 PM 7:30 PM
      Banquet (Invited Speakers Only) 1h