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Session 1 : Extremal combinatorics
Date: September 11 (14:00-17:00) Venue: Information Science Building U414
Balázs Patkós
Affiliation:
Alfréd Rényi Institute of Mathematics, Hungarian Academy of Sciences, HU
Title:
Uniform and non-uniform set system problems for disjointness patterns
戴尚年
Shagnik Das
Affiliation:
Department of Mathematics, National Taiwan University, TW
Title:
Semi-random hypergraph games
Session 2 : Advances in nonlinear dynamics
Date: September 11 (14:00-17:00) Venue: Information Science Building U501
Junsik Bae
Affiliation:
Department of mathematical sciences, Ulsan National Institute of Science and Technology, KR
Title:
Solitary waves of the Euler-Poisson system for ion dynamics
Seungmin Kang
Affiliation:
National Center for Theoretical Sciences (NCTS), TW
Title:
Boundary conditions arising from the diffusion laws
Session 3 : Interdisciplinary research on asymptotic statistics and computational mathematics
Date: September 12 (09:30-12:10) Venue: Information Science Building U602
赤間陽二
Yohji Akama
Affiliation:
Graduate School of Science, Tohoku University, JP
Title:
Asymptotic locations of bounded and unbounded eigenvalues of sample correlation matrices of certain factor models
陳鵬文
Peng-Wen Chen
Affiliation:
Department of Applied Mathematics, National Chun Hsing University, TW
Title:
Phase retrieval by linear algebra
Session 4 : Applications of AI models
Date: September 12 (09:30-12:10) Venue: Information Science Building U501
井手一郎
Ichiro Ide
Affiliation:
Graduate School of Informatics and Mathematical & Data Science Center,
Nagoya University, JP
Title:
Towards the understanding of human perception through generative AI technology
盧鴻興
Horng-Shing Lu
Affiliation:
Kaohsiung Medical University and National Yang Ming Chiao Tung University, TW
Title:
The transformative role of artificial intelligence in precision screening and diagnosis strategies for cardiology healthcare
林嘉文
Chia-Wen Lin
Affiliation:
Department of Electrical Engineering, National Tsing Hua University, TW
Title:
Unleashing the power of deep restoration models: towards versatile, physics-guided generative image augmentation
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