Introduction to matrix and tensor factorization models and related stochastic nonconvex and constrained optimization algorithms

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Abstract. Matrix/tensor factorization models such as principal component analysis , nonnegative matrix factorization, and CANDECOM/PARAFAC tensor decomposition provide powerful framework for dimension reduction and interpretable feature extraction, which are important in analyzing high-dimensional data that comes in large volume. Their diverse applications include image denoising and reconstruction, dictionary learning, topic modeling, and network data analysis.

Phase Estimation of Nonlinear State-space Model of the Circadian Pacemaker Using Level Set Kalman Filter and Raw Wearable Data

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Abstract: Circadian rhythm is a robust internal 24 hours timekeeping mechanism maintained by the master circadian pacemaker Suprachiasmatic Nuclei (SCN). Numerous mathematical models have been proposed to capture SCN’s timekeeping mechanism and predict the circadian phase. There has been an increased demand for applying these models to the various unexplored data sets. One potential application

Dynamical System Perspective for Machine Learning

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Abstract: The connection between deep neural networks and ordinary differential equations (ODEs) is an active field of research in machine learning. In this talk, we view the hidden states of a neural network as a continuous object governed by a dynamical system. The underlying vector field is written using a dictionary representation motivated by the

Optimized persistent random walk in zebrafish airineme search process

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

In addition to diffusive signals, cells in tissue also communicate via long, thin cellular protrusions, such as airinemes in zebrafish. Before establishing communication, cellular protrusions must find their target cell. In this talk, we demonstrate that the shapes of airinemes in zebrafish are consistent with a persistent random walk model. The probability of contacting the

Deep Learning-based Uncertainty Quantification for Mathematical Models

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Over the recent years, various methods based on deep neural networks have been developed and utilized in a wide range of scientific fields. Deep neural networks are highly suitable for analyzing time series or spatial data with complicated dependence structures, making them particularly useful for environmental sciences and biosciences where such type of simulation model

TENET+: a tool for reconstructing gene networks by integrating single cell expression and chromatin accessibility data

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Reconstruction of gene regulatory networks (GRNs) is a powerful approach to capture a prioritized gene set controlling cellular processes. In our previous study, we developed TENET a GRN reconstructor from single cell RNA sequencing (scRNAseq). TENET has a superior capability to identify key regulators compared with other algorithms. However, accurate inference of gene regulation is

Circadian Interventions in Shift Workers

This talk will be given online (If you want to join, please send me an email to jaekkim@ibs.re.kr) Abstract Coupling Math with User-Centric Design Shift workers experience profound circadian disruption due to the nature of their work, which often has them on-the-clock at times when their internal clock is sending a strong, sleep-promoting signal. Mathematical

STEM Initiatives for Agricultural 4.0 and Beyond

This talk will be given online. Abstract: The establishment of UN Sustainable Development Goals (SDG) has led to widespread initiative in STEM learning and research in realising these goals. Here, we will look at some of the works that use control engineering approaches for smart farming (also known as Agriculture 4.0) applications that addresses UN

Design frameworks for engineering efficient cell factory performance within host and industrial constraints

This talk will be given online. Abstract: Synthetic biology and microbial biotechnology offer sustainable routes to the manufacture of commodity and high value chemicals from agricultural by-products instead of petrochemical feedstocks. However, engineered gene circuits and metabolic pathways both co-opt the cell’s gene expression machinery for protein/enzyme production and divert metabolic flux away from key

Causal Inference – basics and examples

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Abstract: In real world, people are interested in causality rather than association. For example, pharmaceutical companies want to know effectiveness of their new drugs against diseases. South Korea Government officials are concerned about the effects of recent regulation with respect to an electric car subsidy from United States. Due to this reason, causal inference has

Shift: A mobile application for shift workers leveraging wearable data, mathematical models, and connected devices

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Shift workers experience profound circadian disruption due to the nature of their work, which often has them working at times when their internal clock is sending a strong signal for sleep. Mathematical models can be used to generate recommendations for shift workers that shift their body's clock to better align with their work schedules, to

Developing and designing dynamic mobile applications that transform wearable data with machine learning and mathematical models.

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon

Wearable analytics hold far more potential than sleep tracking or step counting. In recent years, a number of applications have emerged which leverage the massive quantities of data being amassed by wearables around the world, such as real-time mood detection, advanced COVID screening, and heart rate variability analysis. Yet packaging insights from research for success

IBS 의생명수학그룹 Biomedical Mathematics Group
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IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
55 Expo-ro Yuseong-gu Daejeon 34126 South Korea
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