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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.

News

🌟 DACON Ranker Special Lecture: Winning Strategies for AI Competitions 🌟 2023.11.30

3nd POSTECH&Peking SIAM Student Chapter Joint Conference 2023.11.01

2023 PSSC Summer Camp 2023.10.04

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고]-상시모집 2023.07.25

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고] 2023.07.14

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구교수 채용 공고] 2023.06.12

Seminar | Joint seminar for probability and mathematical biology 2023.05.02

[POSTECH(포항공과대학교) 수리 데이터과학 연구소 연구계약직 공고] 2023.02.15

Upcoming Events

Schedule

MINDS Seminar Series | Kyemyung Park (UNIST) - Predicting and controlling complex immune behavior to cure immune-related diseases using computational modeling

period : 2023-04-25 ~ 2023-04-25

time : 17:00:00 ~ 18:00

개최 장소 : Math Bldg 208 & Online streaming (Zoom)

Topic : Predicting and controlling complex immune behavior to cure immune-related diseases using computational modeling

개요

Date	2023-04-25 ~ 2023-04-25	Time	17:00:00 ~ 18:00
Speaker	Kyemyung Park	Affiliation	UNIST
Place	Math Bldg 208 & Online streaming (Zoom)	Streaming link	ID : 688 896 1076 / PW : 54321
Topic	Predicting and controlling complex immune behavior to cure immune-related diseases using computational modeling
Contents	Systems biology seeks to build quantitative predictive models of biological system behavior for the predictable manipulation of a given system. Biological systems operate across multiple spatiotemporal scales: from molecules to the organismal level, and from milliseconds to days, and even to decades. A good example of such multiscale behavior is the immune system. A myriad of molecular and cellular players comprises the immune system. They operate throughout the body and interact with each other across space and time. Therefore, predictably affecting the immune system for the desired outcomes (i.e., therapies) requires a better understanding of how the system operates as a whole, which is far beyond merely cataloging constituent molecular and cellular components and their interactions among immediate regulatory neighbors. For this endeavor, I seek to explore immune system behavior in its entirety via mathematical and computational modeling by establishing “scalable” modeling of the immune system to describe the multiscale and complex nature of the immune system in silico, eventually allowing predictive dissection and modulation of the complex immune behavior for treating immune-related diseases. In this seminar, I will highlight some challenges in such scalable immune system modeling and my previous works to overcome those (at least partially) and showcase how such efforts helped elucidate the counterintuitive mechanism of maintaining immune homeostasis. I will also lay out research plans incorporating data-driven (e.g., omics) approaches into multiscale computational modeling to realize in silico immune systems with an example of COVID-19 disease progression dynamics.