String Data 2024 --- international conference at Kyoto, Dec 10-12 2024

[橋本幸士]

IBISMLの皆さま  (English announcement below)

京都大学にて，以下の国際会議を開催します．

  String Data 2024

  https://mlphys.scphys.kyoto-u.ac.jp/stringdata2024/

  日時：2024年12月10日(火) - 12日(木)

  場所：京都大学基礎物理学研究所

本国際会議は，広くhep-thを中心とした分野と機械学習／データ科学の

交わりを議論する研究会です．本分野に興味のある方のご参加を歓迎します．

AI・機械学習・データ科学は物理学と関係が深く，基礎理論分野も例外ではありません．

String Data国際会議のトピックは，

弦理論のコンパクト化やAdS/CFTのbulk reconstructionだけでなく，

散乱振幅，量子基礎論，重力，相対論，現象論，場の量子論の定義，SFT，など

多岐に及び，また機械学習側への物理学の貢献も多大です．

世界で若手研究者が参入する研究領域となりつつあります．

String Data会議は2017年に始まり，このたびが8回目となります．

このたびは申し込み講演を受け付けますので，物理学x機械学習 に関する研究発表を

よろしくお願いします（物理学分野はhep-thに限らず，広く物理学といたします）．

招待講演者のリスト（一部）は以下のようになっています．

Gabriel Lopes Cardoso (Lisbon, IST)
François Charton (META AI)
Sergei Gukov (Caltech)
James Halverson (Northeastern University)
Song He (Jilin University / Max Planck Institute Potsdam)
Edward Hirst (Queen Mary, University of London)
Vishunu Jejjela (University of the Witwatersrand in Johannesburg)
Hyun-Sik Jeong (Institute for Theoretical Physics UAM-CSIC in Madrid)
Keun-Young Kim (GIST)
Sven Krippendorf (Arnold Sommerfeld Center for Theoretical Physics, LMU Munich)
Anindita Maiti (Perimeter Institute)
Fabian Ruehle (Northeastern University)
Matthew Schwartz (Harvard University)
Rak-Kyeong Seong (UNIST)
Eva Silverstein (Stanford)

みなさまのご参加をお待ちしています．

オーガナイザー

橋本　幸士  (京都大学)

吉田　健太郎  (埼玉大学)　
村田　仁樹  (埼玉工業大学)　
杉下　宗太郎  (京都大学)　
広野　雄士  (大阪大学)　
三内　顕義  (京都大学)　
世田　拓也  (京都大学)　
疋田　泰章  (京都大学)　
棚橋　典大(京都大学)　

主催：

学習物理領域   https://mlphys.scphys.kyoto-u.ac.jp/

京都大学基礎物理学研究所

%%%%%% Announcement in English %%%%%%%%%%%%%%

Dear friends,

We are pleased to announce the upcoming international conference to be held at Kyoto University:

**String Data 2024**  
Website: https://mlphys.scphys.kyoto-u.ac.jp/stringdata2024/
Dates: December 10 (Tuesday) - December 12 (Thursday), 2024  
Venue: Yukawa Institute for Theoretical Physics, Kyoto University

This conference aims to discuss the intersection of theoretical high-energy physics (hep-th) and machine learning/data science. We warmly welcome the participation of those interested in these fields. AI, machine learning, and data science have become deeply intertwined with physics, including fundamental physics areas. Topics at the String Data conference will cover a wide range of subjects, including string theory compactifications, bulk reconstruction in AdS/CFT, scattering amplitudes, foundation of quantum theories, gravity, relativity, phenomenology, quantum field theory definitions, SFT, and many more, covering also contributions from physics to machine learning. This field is attracting many young researchers worldwide.

Since its inauguration in 2017, this time will be the 8th String Data conference. We are now accepting applications for contributed talks, and we encourage presentations on research related to the intersection of physics and machine learning (not limited to hep-th, but broadly encompassing all areas of physics).

Invited Speakers (partial list):
- Gabriel Lopes Cardoso (Lisbon, IST)
- François Charton (META AI)
- Sergei Gukov (Caltech)
- James Halverson (Northeastern University)
- Song He (Jilin University / Max Planck Institute Potsdam)
- Edward Hirst (Queen Mary, University of London)
- Vishunu Jejjela (University of the Witwatersrand in Johannesburg)
- Hyun-Sik Jeong (Institute for Theoretical Physics UAM-CSIC in Madrid)
- Keun-Young Kim (GIST)
- Sven Krippendorf (Arnold Sommerfeld Center for Theoretical Physics, LMU Munich)
- Anindita Maiti (Perimeter Institute)
- Fabian Ruehle (Northeastern University)
- Matthew Schwartz (Harvard University)
- Rak-Kyeong Seong (UNIST)
- Eva Silverstein (Stanford)

We look forward to your participation.

Organizers:
- Koji Hashimoto (Kyoto University)
- Kentaroh Yoshida (Saitama University)
- Masaki Murata (Saitama Institute of Technology)

- Sotaro Sugishita (Kyoto University)
- Yuji Hirono (Osaka University)
- Akiyoshi Sannai (Kyoto University)
- Takuya Yoda (Kyoto University)
- Yasuaki Hikida (Kyoto University)
- Norihiro Tanahashi (Kyoto University)

Supported by: 

- Foundation of "Machine Learning Physics"

   https://mlphys.scphys.kyoto-u.ac.jp/en/

- Yukawa Institute, Kyoto University