Nov 14 – 17, 2023
Asia/Seoul timezone

Particle physics data is unique and challenging due to its tremendous size and complicated structure stemming from its quantum nature. Rapidly improving quantum-computing technologies could be applied within the particle physics in order to help tackling such computing challenges. The goal of the workshop is to discuss the latest developments in the field of machine learning, quantum computation, and their application in high energy physics, and to brainstorm possible collaborative projects. We hope to bring together experts to better understand this intersection and reach the full potential of quantum computing and machine learning.

Yang Seungtaik Auditorium (E9 building), KAIST (Nov 14 - Nov 16) Room #304, IBS Science Culture Center (Nov 17)
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Invited Speakers

Jack Araz (JLAB)

Eric Chitambar (UIUC)

Lukas Heinrich (TUM)

Michael Kagan (SLAC)

Yingying Li (USTC)

Anindita Maiti (Perimeter Inst.)

Yung-Kyun Noh (Hanyang U)

Michael Spannowsky (IPPP, Durham)

Jesse Stryker (LBNL)

Sangwoon Yoon (KIAS AI) 



Junwoo Bae (KAIST)

K.C. Kong (U of Kansas)

Myeonghun Park (SeoulTech)



This workshop is supported by IBS-CTPU,  KAIST Advanced Institute for Science-X (KAI-X) program, and Seoultech (NRF-2021R1A2C4002551)