国際ワークショップ "Machine Learning at HEP" のご案内

[akinori tanaka]

IBISMLメーリングリストの皆様

理研AIP/iTHEMSの田中です。

機械学習の高エネルギー物理学実験への応用に関する研究会の情報を転送させて頂きます。

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2023年2月23日 - 24日に、KEK 小林ホール + オンラインにて、
国際ワークショップ "Machine Learning at HEP" を開催します。

このワークショップは、2022年7月に同名で開催した国内ワークショップの国際版に、位置付けられるものです。
今回は、高エネルギー物理学実験への機械学習・AI 応用に関する最先端研究をレビューし、さらに今後の研究展開・方向性に関して議論することを目指しております。

口頭発表は招待講演のみとさせていただきますが、ポスターセッションを設けており若手研究者や大学院学生によるポスター発表も大歓迎します。

詳細は、以下のホームページ、または、本メール後半のワークショップ案内文をご覧ください。
https://kds.kek.jp/event/44830/

特に、参加・ポスター発表を希望する方は、以下のRegistrationページ
https://kds.kek.jp/event/44830/registrations/
から登録をお願いします (締切 2月10日。但し、会場の人数制限のため、定員が埋まり次第、早めに締め切る可能性があります)。
限りはありますが、旅費支援が可能です。

多くの方のご参加をお待ちしております。

世話人一同

Contact: ml-at-hep2023-loc at ml.post.kek.jp

Program Committee: Javier Montejo Berlingen (KEK QUP, ATLAS), Kodai Matsuoka (KEK IPNS, BelleII), Gaku Mitsuka (KEK, SuperKEKB), Yu Nakahama (Chair) (KEK QUP & IPNS, ATLAS), Hiroyuki Nakayama (KEK IPNS, BelleII), Sanmay Ganguly (UTokyo ICEPP, ATLAS, BAI), Mihoko Nojiri (KEK IPNS, theory), Junichi Tanaka (UTokyo ICEPP, ATLAS, BAI).

Local Organization Committee: Yuji Chione (KEK QUP, LiteBIRD), Javier Montejo Berlingen (KEK QUP, ATLAS), Daniel Jeans (KEK IPNS, ILC), Kodai Matsuoka (KEK IPNS, BelleII), Kunihiro Nagano (KEK IPNS, ATLAS), Yu Nakahama (Chair) (KEK QUP & IPNS, ATLAS), Hiroyuki Nakayama (KEK IPNS, BelleII), Mihoko Nojiri (KEK IPNS, theory), Hideyuki Oide (KEK IPNS, ATLAS), Volodymyr Takhistov (KEK QUP, theory & Super-Kamiokande).

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(ワークショップ案内文)

Dear all,

We are delighted to announce that the "ML at HEP workshop" will be held at KEK, Tsukuba, Japan, from February 23rd to 24th, 2023. After a successful first domestic workshop on "ML at HEP" in July 2022, this is our first time to organize such an international workshop in Japan by inviting world-leading researchers on Machine-Learning topics in related fields. This workshop also aims to bring together researchers in high energy physics, data science, and related communities.

The scope of the workshop is to overview the state-of-the-art ML applications to high energy physics and beyond, and to provide lively discussions about the directions of ML & AI technical developments in the field.

The topics of the workshop program include:
- Advanced ML techniques useful for HEP,
- Advanced architectures for ML,
- ML applications in HEP and beyond,
- Advanced applications at accelerators and systems, and
- Future directions in ML and AI x HEP and beyond.

The workshop format is hybrid (in-person at KEK and online via zoom). Presentations are given by invited speakers, and no free abstract submission is available in this occasion. An on-site poster session is also scheduled. Please indicate your intention to present a poster on your ML-related work via the registration form. As of January 13th, domestic travel and accommodation support can be provided to a limited number of presenters. If you would like to request it, please contact us via the LOC mailing list by January 31st.

HP: https://kds.kek.jp/event/44830/

Registration:
Registration is now open at https://kds.kek.jp/event/44830/registrations/ , and will close on February 10th. No registration fee is necessary.

List of confirmed speakers with tentative talk titles:
- Sanmay Ganguly (Tokyo) : Particle Flow
- Tobias Golling (Geneva): Generative models
- Lukas Heinrich (TUM): Detector design using differential programing
- Yutaro Iiyama (Tokyo): Quantum ML
- Xiangyang Ju (LBL): Tracking and vertexing in dense pileup environments using DL
- Micheal Kagan (SLAC): Challenges in ML/DL applications for HEP
- Tomoe Kishimoto (KEK): Offline resource evolution for ML/DL
- Jia Liu (Kavli IPMU): Data Driven Discovery in Cosmology
- Ben Nachman (LBL): Anomaly Detection
‪- Tsuyoshi Nomura (Toyota Central R&D Labs., Inc.): Design automation by numerical calculation and optimization
- Kanta Ono (Osaka & KEK): AI-assisted measurements in quantum beam experiments
- Adrian Alan Pol (Princeton): Online compatibilities in ML/DL
- Ryan Roussel (SLAC): Accelerator controls with ML
- Benjamin Schwenker (Goettingen): Beam background prediction with ML

This workshop is hosted co-organized by KEK WPI-QUP (International Center for Quantum-field Measurement Systems for Studies of the Universe and Particles) and IPNS (Institute of Particle and Nuclear Studies), and supported by KEK WPI-QUP, JSPS Grant-in-Aid for Transformative Research Areas (A) 22H05113, and BAI (Institute for AI and Beyond of the University of Tokyo).

Contact:  ml-at-hep2023-loc at ml.post.kek.jp
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Akinori Tanaka 

akinori...@riken.jp