KDD 2025 Panel on AI for Science

Artificial Intelligence (AI) is rapidly reshaping the landscape of scientific discovery by enabling the development of novel models that tackle complex, data- and computation-intensive problems. Scientific challenges, in turn, provide rich, use-inspired settings that push the boundaries of AI research. This virtuous cycle is increasingly driven by cross-disciplinary collaboration, where advances in AI and domain sciences co-evolve to accelerate innovation. In this plenary panel, we will examine the opportunities and challenges in designing cutting-edge AI models for scientific discovery, and high- light the transformative potential of cross-disciplinary partnerships in shaping the future of both AI and science.

Authors

Institutions

Publication Details

Published
2025-08-03
DOI
https://doi.org/10.1145/3711896.3742464
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

KDD 2025 Panel on AI for Science

Aidong Zhang, Vipin Kumar, Yan Liu
Big Data and Business Intelligence
article

KDD 2025 Panel on AI for Science

Aidong Zhang, Vipin Kumar, Yan Liu
article en

Abstract

Artificial Intelligence (AI) is rapidly reshaping the landscape of scientific discovery by enabling the development of novel models that tackle complex, data- and computation-intensive problems. Scientific challenges, in turn, provide rich, use-inspired settings that push the boundaries of AI research. This virtuous cycle is increasingly driven by cross-disciplinary collaboration, where advances in AI and domain sciences co-evolve to accelerate innovation. In this plenary panel, we will examine the opportunities and challenges in designing cutting-edge AI models for scientific discovery, and high- light the transformative potential of cross-disciplinary partnerships in shaping the future of both AI and science.

University of Southern California (US), University of Minnesota (US), University of Virginia (US)
Openalex Percentile: Top 67%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

KDD 2025 Panel on AI for Science — Aidong Zhang, Vipin Kumar, et al. · (2025) | TGRS Research Map | TGRS