BEGIN:VCALENDAR
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PRODID:-//Biomedical Mathematics Group - ECPv6.17.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20250101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260724T100000
DTEND;TZID=Asia/Seoul:20260724T120000
DTSTAMP:20260713T062127Z
CREATED:20260713T062127Z
LAST-MODIFIED:20260713T062127Z
UID:12700-1784887200-1784894400@www.ibs.re.kr
SUMMARY:Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function - Seongjin Choi
DESCRIPTION:In this talk\, we discuss the paper “Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function” by Kelly Maggs et al.\, bioRxiv\, 2025. \nAbstract: \n\nStandard single-cell RNA-seq analysis frameworks aggregate over-lapping biological processes and impose a single parametrization\, conflating distinct programs. Here\, we introduce a topological framework that detects and disentangles multiple cyclic processes directly from single-cell transcriptomic data. We validate this approach on synthetic datasets and scRNA-seq profiles of human dermal fibroblasts under control conditions and following androgen receptor (AR) silencing\, as well as in vivo mouse prostate regeneration under androgen receptor add-back. We show robust cell cycle structure across conditions\, identify an unbiased AR-linked stress signature related to the senescence and proliferation across organisms\, and uncover cholesterol homeostasis as an AR-linked program in tissue regeneration. This framework enables identification and separation of concurrent cyclic processes from snapshot single-cell data\, revealing complex multi-dimensional regulatory dynamics inaccessible to standard clustering analysis.
URL:https://www.ibs.re.kr/bimag/event/topology-identifies-concurrent-cyclic-processes-in-single-cell-transcriptomics-and-androgen-receptor-function-seongjin-choi/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260728T160000
DTEND;TZID=Asia/Seoul:20260728T170000
DTSTAMP:20260713T132333Z
CREATED:20260713T061641Z
LAST-MODIFIED:20260713T132333Z
UID:12698-1785254400-1785258000@www.ibs.re.kr
SUMMARY:Global Linearization of Nonlinear Dynamics via Koopman Operators: A Gentle Introduction\, Applications\, and Open Challenges - Hyukpyo Hong
DESCRIPTION:Abstract: \nA central challenge of modern dynamical systems theory is to make nonlinear systems tractable without sacrificing fidelity. Koopman operator theory pursues this goal by lifting nonlinear dynamics into a linear\, but infinite dimensional\, operator acting on a function space. This operator-theoretic perspective underlies a broad class of modern data-driven methods\, from dynamic mode decomposition to equation discovery in scientific machine learning for fluid dynamics and neuroscience. Yet this power comes at a price: the operator’s infinite dimensionality poses a fundamental obstacle to computation and practical use\, and finding tractable finite-dimensional approximations remains an open and active challenge. In this talk\, I will first introduce the basic principles of Koopman operator theory and survey some of the results that have made it a cornerstone of modern dynamical systems analysis. I will then briefly describe two of my works on finite-dimensional Koopman representations. Finally\, I will turn to my recent work on non-autonomous dynamical system learning\, in collaboration with Prof. Dae Wook Kim.
URL:https://www.ibs.re.kr/bimag/event/global-linearization-of-nonlinear-dynamics-via-koopman-operators-a-gentle-introduction-applications-and-open-challenges-hyukpyo-hong/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260731T100000
DTEND;TZID=Asia/Seoul:20260731T120000
DTSTAMP:20260730T020723Z
CREATED:20260629T081120Z
LAST-MODIFIED:20260730T020723Z
UID:12661-1785492000-1785499200@www.ibs.re.kr
SUMMARY:Fast training of accurate physics-informed neural networks without gradient descent - Seunghun Lee
DESCRIPTION:In this talk\, we discuss the paper “Fast training of accurate physics-informed neural networks without gradient descent” by Chinmay Datar et al.\, ICLR\, 2026. \nAbstract: \nSolving time-dependent Partial Differential Equations (PDEs) is one of the most critical problems in computational science. While Physics-Informed Neural Networks (PINNs) offer a promising framework for approximating PDE solutions\, their accuracy and training speed are limited by two core barriers: gradient-descent-based iterative optimization over complex loss landscapes and non-causal treatment of time as an extra spatial dimension. We present Frozen-PINN\, a novel PINN based on the principle of space-time separation that leverages random features instead of training with gradient descent\, and incorporates temporal causality by construction. On nine PDE benchmarks\, including challenges like extreme advection speeds\, shocks\, and high-dimensionality\, Frozen-PINNs achieve superior training efficiency and accuracy over state-of-the-art PINNs\, often by several orders of magnitude. Our work addresses longstanding training and accuracy bottlenecks of PINNs\, delivering quickly trainable\, highly accurate\, and inherently causal PDE solvers\, a combination that prior methods could not realize. Our approach challenges the reliance of PINNs on stochastic gradient-descent-based methods and specialized hardware\, leading to a paradigm shift in PINN training and providing a challenging benchmark for the community.
URL:https://www.ibs.re.kr/bimag/event/oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260803T110000
DTEND;TZID=Asia/Seoul:20260803T120000
DTSTAMP:20260728T040536Z
CREATED:20260728T040536Z
LAST-MODIFIED:20260728T040536Z
UID:12743-1785754800-1785758400@www.ibs.re.kr
SUMMARY:Infection dynamics at the host and cellular levels - Seong Jun Park
DESCRIPTION:Abstract: \nIn general\, the rates of infection and removal (whether through recovery or death) are nonlinear functions of the number of infected and susceptible individuals. One of the simplest models for the spread of infectious diseases is the SIR model\, which categorizes individuals as susceptible\, infectious\, recovered or deceased. In this model\, the infection rate\, governing the transition from susceptible to infected individuals\, is given by a linear function of both susceptible and infected populations. Similarly\, the removal rate\, representing the transition from infected to removed individuals\, is a linear function of the number of infected individuals. However\, existing research often overlooks the impact of nonlinear infection and removal rates in infection dynamics. This work presents an analytic expression for the number of infected individuals considering nonlinear infection and removal rates. In particular\, we examine how the number of infected individuals varies as cases emerge and obtain the expression accounting for the number of infected individuals at each moment. Viruses are microscopic infectious agents that require a host cell for replication. Viral replication occurs in several stages\, and the completion time for each stage varies due to differences in the cellular environment. Thus\, the time to complete each stage in viral replication is a random variable. However\, no analytic expression exists for the viral population at the cellular level when the completion time for each process constituting viral replication is a random variable. This study presents a simplified model of viral replication\, treating each stage as a renewal process with independently and identically distributed completion times. Using the proposed model\, we derive an analytical formula for viral populations at the cellular level\, based on viewing viral replication as a birth-death process. The mean viral count is expressed via probability density functions representing the completion time for each step in the replication process. This work validates the results with stochastic simulations. This study provides a new quantitative framework for understanding viral infection dynamics at host and cellular levels.
URL:https://www.ibs.re.kr/bimag/event/infection-dynamics-at-the-host-and-cellular-levels-seong-jun-park/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260807T100000
DTEND;TZID=Asia/Seoul:20260807T120000
DTSTAMP:20260730T084420Z
CREATED:20260730T084420Z
LAST-MODIFIED:20260730T084420Z
UID:12778-1786096800-1786104000@www.ibs.re.kr
SUMMARY:AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML - Jin Woo Hyun
DESCRIPTION:In this talk\, we discuss the paper “AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML” by Patara Trirat et al\, ICML\, 2025. \nAbstract: \nAutomated machine learning (AutoML) accelerates AI development by automating tasks in the development pipeline\, such as optimal model search and hyperparameter tuning. Existing AutoML systems often require technical expertise to set up complex tools\, which is in general time-consuming and requires a large amount of human effort. Therefore\, recent works have started exploiting large language models (LLM) to lessen such burden and increase the usability of AutoML frameworks via a natural language interface\, allowing non-expert users to build their data-driven solutions. These methods\, however\, are usually designed only for a particular process in the AI development pipeline and do not efficiently use the inherent capacity of the LLMs. This paper proposes AutoML-Agent\, a novel multi-agent framework tailored for full-pipeline AutoML\, i.e.\, from data retrieval to model deployment. AutoML-Agent takes user’s task descriptions\, facilitates collaboration between specialized LLM agents\, and delivers deployment-ready models. Unlike existing work\, instead of devising a single plan\, we introduce a retrieval-augmented planning strategy to enhance exploration to search for more optimal plans. We also decompose each plan into sub-tasks (e.g.\, data preprocessing and neural network design) each of which is solved by a specialized agent we build via prompting executing in parallel\, making the search process more efficient. Moreover\, we propose a multi-stage verification to verify executed results and guide the code generation LLM in implementing successful solutions. Extensive experiments on seven downstream tasks using fourteen datasets show that AutoML-Agent achieves a higher success rate in automating the full AutoML process\, yielding systems with good performance throughout the diverse domains.
URL:https://www.ibs.re.kr/bimag/event/automl-agent-a-multi-agent-llm-framework-for-full-pipeline-automl-jin-woo-hyun/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260814T100000
DTEND;TZID=Asia/Seoul:20260814T120000
DTSTAMP:20260730T035435Z
CREATED:20260730T035435Z
LAST-MODIFIED:20260730T035435Z
UID:12774-1786701600-1786708800@www.ibs.re.kr
SUMMARY:Evolution of error correction through a need for speed - Kangmin Lee
DESCRIPTION:In this talk\, we discuss the paper “Evolution of error correction through a need for speed” by Riccardo Ravasio et al.\, Science\, 2026. \nAbstract: \nKinetic proofreading is a class of error-correcting mechanisms in biology that expend energy to avoid mistakes during replication\, transcription\, and translation. Proofreading is typically assumed to evolve when selection for fidelity outweighs costs in energy and the speed of replication. We show that when stalling after misincorporations is accounted for\, proofreading can instead speed up replication. Consistent with data on polymerase mutagenesis\, our results suggest that proofreading can evolve under selection for speed alone. We generalize to multicomponent self-assembly and show that analogous error-correcting processes\, such as dynamic instability\, can likewise emerge purely from selection for rapid assembly. Thus\, nonequilibrium error correction can evolve from selection for speed\, even without direct fidelity advantages. We discuss implications for mutation-rate evolution\, molecular assembly processes\, and models of early life.
URL:https://www.ibs.re.kr/bimag/event/evolution-of-error-correction-through-a-need-for-speed-kangmin-lee/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260817T160000
DTEND;TZID=Asia/Seoul:20260817T170000
DTSTAMP:20260810T020452Z
CREATED:20260810T020342Z
LAST-MODIFIED:20260810T020452Z
UID:12808-1786982400-1786986000@www.ibs.re.kr
SUMMARY:수학이 공학의 언어라면 - 민태기
DESCRIPTION:  \n이번 세미나에서는 “조선이 만난 아인슈타인”\, “판타 레이” 등을 저술하신 민태기 소장님을 모시고 “수학이 공학의 언어라면”이라는 주제로 강연을 진행할 예정입니다.
URL:https://www.ibs.re.kr/bimag/event/%ec%88%98%ed%95%99%ec%9d%b4-%ea%b3%b5%ed%95%99%ec%9d%98-%ec%96%b8%ec%96%b4%eb%9d%bc%eb%a9%b4-%eb%af%bc%ed%83%9c%ea%b8%b0/
LOCATION:109\, Conference room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2026/08/L20230605095029.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260821T100000
DTEND;TZID=Asia/Seoul:20260821T120000
DTSTAMP:20260730T035554Z
CREATED:20260730T020529Z
LAST-MODIFIED:20260730T035554Z
UID:12772-1787306400-1787313600@www.ibs.re.kr
SUMMARY:Tangent-Space Regularization for Neural-Network Models of Dynamical Systems - Olive Cawiding
DESCRIPTION:In this talk\, we discuss the paper “Tangent-Space Regularization for Neural-Network Models of Dynamical Systems” by Fredrik B Carlson et al\, arXiv (2026). \nAbstract: \nThis work introduces the concept of tangent space regularization for neural-network models of dynamical systems. The tangent space to the dynamics function of many physical systems of interest in control applications exhibits useful properties\, e.g.\, smoothness\, motivating regularization of the model Jacobian along system trajectories using assumptions on the tangent space of the dynamics. Without assumptions\, large amounts of training data are required for a neural network to learn the full non-linear dynamics without overfitting. We compare different network architectures on one-step prediction and simulation performance and investigate the propensity of different architectures to learn models with correct input-output Jacobian. Furthermore\, the influence of L2 weight regularization on the learned Jacobian eigenvalue spectrum\, and hence system stability\, is investigated.
URL:https://www.ibs.re.kr/bimag/event/tangent-space-regularization-for-neural-network-models-of-dynamical-systems-olive-cawiding/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260828T100000
DTEND;TZID=Asia/Seoul:20260828T120000
DTSTAMP:20260730T040743Z
CREATED:20260730T040743Z
LAST-MODIFIED:20260730T040743Z
UID:12776-1787911200-1787918400@www.ibs.re.kr
SUMMARY:Towards a General Intelligence and Interface for Wearable Health Data - Aqsa Awan
DESCRIPTION:In this talk\, we discuss the paper “Towards a General Intelligence and Interface for Wearable Health Data” by Girish Narayanswamy et al.\, arXiv\, 2026. \nAbstract: \nWhile ubiquitous wearable sensors capture a wealth of behavioral and physiological information\, effectively transforming these signals into personalized health insights is challenging. Specifically\, converting low-level sensor data into representations capable of characterizing higher-level states is difficult due to high phenotypic diversity and variation in individual baseline health\, physiology\, and lifestyle factors. Moreover\, collecting wearable data paired with health outcome annotations is laborious and expensive\, and retrospective annotation remains practically unfeasible\, contributing to a scarcity of data with high-quality labels. To overcome these limitations\, we propose a foundation model for wearable health that is pretrained on more than one trillion minutes of unlabeled sensor signals drawn from a large cohort of five million participants. We demonstrate that the joint scaling of model capacity and pretraining data volume leads to systematic improvements in performance\, as evaluated on a diverse set of 35 health prediction tasks\, spanning cardiovascular\, metabolic\, sleep\, and mental health\, as well as lifestyle choices and demographic factors. We find that this population scale representation unlocks label-efficient few-shot learning and generative capabilities for robust daily metric estimation. To further leverage this learned representation\, we deploy a classroom of LLM agents to autonomously search the space of downstream predictive heads built on the model embeddings\, showing broad performance improvements that increase with LLM model capacity. Finally\, we show how integrating these downstream predictors into a Personal Health Agent can support model responses that are more relevant\, contextually aware\, and safe\, and we validate this via 1\,860 ratings from a cohort of clinicians.
URL:https://www.ibs.re.kr/bimag/event/towards-a-general-intelligence-and-interface-for-wearable-health-data-aqsa-awan/
LOCATION:108\, Conference Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
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