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Date: Tue, 7 Apr 2026 23:58:26 +0900
To: sg-l__AT__ml.yukawa.kyoto-u.ac.jp
Subject: [Sg-l:10257] Announcement of KEK Physics seminer (April 17, 2026)
From: Mihoko Nojiri (Sg-l 経由) 

KEK の物理セミナーのお知らせです。
タイトル: Interdisciplinary Machine Learning: Forging Collaborations Across Science

講演者: Vinicius Mikuni 氏 (KMI)

会場: 3号館セミナーホール

日時: 2026年4月17日（金）16:00 -

https://kds.kek.jp/event/59485/

Zoom link:
https://us02web.zoom.us/j/84511164837?pwd=cOfSByaUcYFwuY5VbekrK5XS95kwf3.1
Meeting ID: 845 1116 4837
Passcode: 442205

The past decade has been marked by an exponential increase in the
availability of experimental data across many scientific fields,
leading to unprecedented advances in our understanding of nature
and the universe. Modern data analysis methods based on artificial
intelligence (AI) have been developed to extract maximal information
from these rich datasets. While the scientific questions differ
across fields, the underlying analysis methods often share common c
oncepts and software tools. In this talk, I will highlight
how AI has transformed data analysis across multiple experiments
and how interdisciplinary collaboration between researchers
and methods can accelerate scientific discovery. Examples
include fast simulation frameworks for collider physics,
nuclear physics, astroparticle physics, and weather modeling
applications, as well as scientific foundation models for
collider physics, cosmology, and molecular dynamics.
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高エネルギー加速器研究機構
素粒子原子核研究所
野尻美保子(Mihoko Nojiri)
住所:〒305-0801 つくば市大穂1-1
TEL: 029-864-5323
携帯: 090-7270-3554
Email: nojiri__AT__post.kek.jp