Applied Maths Seminar: Kim -- Synergy between math modeling and AI to solve human health problems

Prof Jaekyoung Kim (Korea Advanced Institute of Science and Technology) is visiting us
and will give a talk on Monday 13th October at 12pm in Carslaw 375 (note general
unusualness).  You may have recently seen him in the SMH:
https://www.smh.com.au/lifestyle/health-and-wellness/the-best-way-to-get-a-good-night-s-sleep-there-s-a-maths-equation-for-that-20250922-p5mwz9.html 

Title: Synergy between math modeling and AI to solve human health problems 

Abstract: With recent advances in experimental tools and wearable devices, it has become
increasingly easy to collect large volumes of time-series data.  In this talk, I will
demonstrate how such data can be used to uncover hidden structure in complex biological
systems.  First, I will introduce GOBI (General Model-based Inference), a simple yet
scalable method for inferring regulatory networks from time-series data.  GOBI can infer
both gene-regulatory and ecological networks, surpassing traditional causality methods
such as Granger and CCM.  Next, I will present Density-PINN (a physics-informed neural
network) that infers the shape of the time-delay distribution governing interactions
within a network.  This inferred distribution helps identify the number of pathways
responsible for signaling responses to antibiotics, addressing a long-standing question
about the primary sources of cell-to-cell heterogeneity under stress.  Finally, I will
show how combining mathematical modeling with machine learning enables analysis of
large-scale sleep–wake time-series measured by smartwatches.  This approach allowed us
to develop personalized sleep-wake schedules that mitigate daytime sleepiness and reduce
depression risk, and I will briefly discuss translation into a practical app for broader
use.  In particular, this algorithm has been serviced globally via the Galaxy Watch
since last August, demonstrating how mathematical models can be translated into
practical applications.