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  • Inferring circadian phases and quantifying biological desynchrony across single-cell transcriptomes – Dongju Lim

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    In this talk, we discuss the paper “Inferring circadian phases and quantifying biological desynchrony across single-cell transcriptomes” by Andrea Salati et al., bioRxiv, 2026.   Abstract: Single-cell RNA sequencing (scRNA-seq) reveals heterogeneity in circadian clock states across individual cells, yet accurately inferring circadian phase and distinguishing biological desynchrony from technical noise remains challenging. Here, we …

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  • Insulin resistance prediction from wearables and routine blood biomarkers – Hyunji Jeong

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    In this talk, we discuss the paper “Insulin resistance prediction from wearables and routine blood biomarkers” by Ahmed A. Metwally et al., Nature, 2026. Abstract: Insulin resistance (IR), a primary precursor to type 2 diabetes, is characterized by impaired insulin action in tissues1. However, diagnostic methods remain expensive and inaccessible, which hinders early intervention2,3. Here …

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  • Prediction of mood state change based on repeated functional brain imaging and mathematical modeling in premenstrual syndrome – Dayoung Yoon

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    Abstract: Accurately predicting mood fluctuations in mood disorders is critical for early intervention and personalized treatment. This study developed a neurophysiologically grounded mood prediction model by integrating behavioral modeling, electroencephalography, functional magnetic resonance imaging (fMRI), and physiological data from wearable devices in premenstrual syndrome (PMS). First, applying the active inference framework to a risk-taking behavioral …

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  • A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations – Se Jun Ahn

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    In this talk, we discuss the paper "A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations" by Harkirat Sigh Arora et al., npj drug discovery, 2026. Abstract: Antimicrobial resistance poses a major global threat, driven by diminishing efficacy of current treatments and limited new therapies. Combination therapy with existing drugs …

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  • The effect of the fitness gradient – Jakub Svoboda

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    Abstract: Evolutionary biology studies populations of reproducing individuals and how their composition changes over time.An important question is the fixation probability of a single mutant that attempts to invade a homogeneous population.Many real populations experience gradients of chemicals or nutrients that cause mutations to be beneficial in some spatial regions and harmful in others.We will …

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  • Advanced Iterative Methods as Elementary Iterations on Larger Spaces – Jongho Park

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    Abstract: A central goal of scientific computing is to develop accurate and efficient solvers for scientific problems, and this goal is often pursued through sophisticated numerical methods. In modern machine learning, by contrast, the basic optimization procedure is often comparatively simple, typically gradient descent and its variants, while much of the complexity is shifted to …

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  • Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA – Yun Min Song

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    In this talk, we discuss the paper “Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA” by Zhuohan Yu et al., nature communications, 2023. Abstract: Single-cell RNA sequencing provides high-throughput gene expression information to explore cellular heterogeneity at the individual cell level. A major challenge in characterizing high-throughput gene expression …

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  • Topology identifies concurrent cyclic processes in single-cell transcriptomics and androgen receptor function – Seongjin Choi

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    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. Abstract: Standard 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 …

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  • Global Linearization of Nonlinear Dynamics via Koopman Operators: A Gentle Introduction, Applications, and Open Challenges – Hyukpyo Hong

    108, Conference Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

    Abstract: A 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 …

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  • Fast training of accurate physics-informed neural networks without gradient descent – Seunghun Lee

    108, Conference Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

    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. Abstract: Solving 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 …

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  • Infection dynamics at the host and cellular levels – Seong Jun Park

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    Abstract: In 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, …

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  • AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML – Jin Woo Hyun

    B232 Seminar Room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Daejeon, Korea, Republic of

    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. Abstract: Automated 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 …

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