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International Summer School 2026 

Scientific approach toward nonstationary time series analysis for biomedical artificial intelligence

 

COURSE DESCRIPTION

Advances in sensing and computing technologies now generate complex biomedical datasets across laboratory research, clinical environments, and decentralized home-care settings. These data are nonlinear, nonstationary, and often uncertain, which makes rigorous scientific foundations essential for the next generation of medical AI. This summer school focuses on the science behind data science: how AI models are formulated, analyzed, and quantitatively validated.

In this three-week program, we emphasize the central role of mathematical modeling and interpretability of algorithms used in medical AI. Participants will learn how to build models that encode physiological mechanisms, phenomenological behaviors, and system dynamics, and how these models guide algorithm design and statistical inference. We highlight how proper modeling contributes to interpretability, uncertainty quantification, and reliable clinical insights, and implement such highlight on hands-on practice through real biomedical case studies. Participants will also be introduced to the cycle of research, from idea to analysis to presentation.

Core topics include:

  1. How to perform research.

  2. Mathematical modeling of physiological and biomedical systems, from mechanistic formulations to data-driven structures, together with statistical quantification and uncertainty analysis.

  3. Modern time-frequency analysis for nonstationary signals.

  4. Unsupervised manifold learning for understanding intrinsic geometric structure in high-dimensional data.

  5. Hands-on practice on real world biomedical signals.

The school is designed for PhD, master’s, and advanced undergraduate students interested in data science, medical AI, and interdisciplinary research at the interface of mathematics, statistics, engineering, and medicine.
 

ORGANZIERS

  • Steven Altschuler, Systems pharmacology, University of California, San Francisco
  • Hau-Tieng Wu, Mathematics, New York University/Academia Sinica
  • Lani Wu, Systems pharmacology, University of California, San Francisco
  • Shih-Hsien Yu, Mathematics, Academia Sinica
     

LIST OF INSTRUCTORS

  1. Steven Altschuler, Systems pharmacology, University of California, San Francisco
  2. Stefan Borik, Electrical Engineering, University of Zilina 
  3. Gi-Ren Liu, Mathematics, National Cheng Kung University
  4. Yi-Wen Liu, Electrical Engineering, National Tsing Hua University
  5. Govind Menon, Mathematics, Brown University
  6. Gal Mishne, Data Science, University of California, San Diego
  7. Yusu Wang, Data Science, University of California, San Diego
  8. Hau-Tieng Wu, Mathematics, New York University/Academia Sinica
  9. Lani Wu, Systems pharmacology, University of California, San Francisco
  10. Junho Yang, Statistics, Academia Sinica
     

PREREQUISITES
Advanced senior & PhD level students.

  1. For students from math, stat, EE, CS: linear algebra, multivariable calculus and probability.
  2. For students from biomedicine: linear algebra and basic calculus
  3. All: Matlab or Python.
     

GENERAL INFORMATION

Time: July 1st (Wednesday)-July 21 (Tuesday): 3 weeks.
Location: IOM, Academia Sinica in the Astromathematics building
Application website: via MATHJOBS https://www.mathjobs.org/jobs/list/27980  (available on Jan 15th)

VENUE

This summer school will be hosted in Taipei, the vibrant capital of Taiwan, with lectures given in the Astromathematics building. Taiwan, historically known as Formosa, offers international students a unique blend of democracy1, safety2, and freedom3. As one of Asia's most open and progressive societies, Taiwan fosters an inclusive environment where people can freely express themselves and thrive. Known for its recent technological advancements, particularly in semiconductors and AI, Taipei is a hub for innovation and opportunity. The dynamic food scene, from local street delicacies to international cuisines, reflects a rich cultural fusion of Japanese, Chinese, and indigenous influences. With its commitment to democracy and cutting-edge technology, Taiwan is not only a safe place to study but also an exciting gateway to the future. Moreover, Taiwan is celebrated for its rich biodiversity and breathtaking natural landscapes. From the towering mountains to scenic coastlines, students can immerse themselves in nature, hiking, cycling, or simply enjoying the great outdoors during weekends.

 1 World Population Review - Democracy Index by Country 2025
 2 World Population Review - Safest Countries in the World 2025 
 3 Freedom House - Countries and Territories

 

MORE INFORMATION

Email: hautiengw@gmail.com

CONTACT

For administrative supports, please contact
Email: conference@gmail.math.sinica.edu.tw
*Notice: Please include [Summer School 2026] in the subject line of your email, thank you!
 

 

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