Welcome to MINDS!

Established in 2020, POSTECH Mathematical Institute for Data Science (MINDS) is the community of researchers in the areas of fundamental data science, machine learning, artificial intelligence, scientific computing, and humanitarian data science. MINDS mission is to provide a platform for collaboration among researchers and to provide various opportunities for students in data science. MINDS also aims to use our data science research to serve our local and global communities pursuing humanitarian data science.


Upcoming Events



MINDS Seminar Series | Kyongmin Yeo (IBM T.J. Watson Research Center) - Towards Foundation Model for Dynamical Systems

period : 2023-11-08 ~ 2023-11-08
time : 14:00:00 ~ 15:30:00
개최 장소 : Math Bldg 404 & Online streaming (Zoom)
Topic : Towards Foundation Model for Dynamical Systems
Date 2023-11-08 ~ 2023-11-08 Time 14:00:00 ~ 15:30:00
Speaker Kyongmin Yeo Affiliation IBM T.J. Watson Research Center
Place Math Bldg 404 & Online streaming (Zoom) Streaming link ID : 688 896 1076 / PW : 54321
Topic Towards Foundation Model for Dynamical Systems
Contents Since the success of large language models, Foundation Model has attracted a great attention. Foundation Model aims to provide a pre-trained model, typically a large deep learning model, that can be easily fine-tuned or re-purposed for a downstream task with a smaller data set. Where there has been much progress in the language and vision domains, Foundation Model for time series data is not relatively well studied. Here, we propose a preliminary Foundation Model targeted to nonlinear dynamical systems. We consider the problem of building a foundation model from a range of dynamical systems and generating a time series data from the foundation model given a short sequence of input data. The foundation model consists of two modules. In the first module, we aim to learn a dictionary of functions. We propose to use a contrastive learning with a hierarchy to build a dictionary of different classes of dynamical systems. Then, we use a denoising diffusion model to generate the time series data from the dictionary. The foundation model can also be used for a forecast of the input sequence.
MinDS MinDS · 2023-10-31 09:16 · Views 334

POSTECH SIAM Student Chapter

🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟

2023 POSTECH & Peking SIAM Student Chapter Joint Conference

2023 PSSC Summer Camp

2022 PSSC Summer Camp

2022 POSTECH & Peking SIAM Student Chapter Joint Conference


Information, Network & Topological Data Analysis


Recent Progress in Data Science and Applications

Fall 2021 Seminar Series

MINDS Seminar Series on Data Science, Machine Learning, and Scientific Computing

Every Tuesdays 05:00 PM


POSTECH SIAM Student Chapter Launched!