Members

Interests: Agentic AI, MLOps, Trustworthy AI for Avian Influenza & Environmental Disasters

M.S. Student. Co-authored a paper on reinforced explainable AI for algal bloom forecasting in Journal of Cleaner Production (SCIE, IF = 10.7 / JCR Top 6.7%, 2025), presented five papers at KSZ, KEEA, KOTIS, and TMES (2024–2025), and received the President’s Award (KEI, 2024).

Interests: Trustworthy AI, Environmental Forecasting, Particulate Matter (PM), Time Series Analysis

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on trustworthy AI for the environment — currently completing a research project and paper on particulate matter (PM) forecasting, and building on that experience toward reliable, explainable prediction models for environmental data. Also interested in broader environmental research and time series forecasting.

Interests: Computational Social Science, LLM-based Synthetic Personas, Sales Forecasting, Simulation

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on computational social science — going beyond simple statistical analysis of sales data by building virtual persona models and integrating them into sales forecasting systems. Interested in simulating how weather and other factors drive each persona’s inflow to sharpen forecasting precision and design targeted customer scenarios, and in extending this work to consumption patterns in unmanned stores as more data becomes available. Also interested in trustworthy AI.

Interests: Computational Social Science, Urban Analytics, Digital Twins, LLM-based Agents

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on computational social science — modeling complex urban phenomena and the interactions of individual agents from data, with a particular interest in simulating human behavior in urban spaces using digital twins and LLM-based synthetic agents. Also interested in spatio-temporal data processing and modeling for infectious disease research.

Interests: Trustworthy AI, Explainable AI (XAI), MLOps, Computational Social Science

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on trustworthy AI for infectious disease forecasting — building prediction models from time-series and unstructured data and validating their reliability with XAI. Also interested in implementing end-to-end MLOps pipelines and analyzing social phenomena and user behavior through computational social science.

Interests: Trustworthy AI, Adversarial Robustness, AI Privacy & Security, Multi-Agent Simulation

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on trustworthy AI for infectious disease — building prediction models robust to adversarial attacks and noise in health data, and modeling complex human behaviors such as compliance and mobility through multi-agent simulations combining spatial-behavioral data with LLM-based synthetic agents. Also interested in systematically auditing data privacy and model security across the deployment pipeline, quantitatively evaluating robustness against threat vectors such as membership inference attacks, model reverse engineering, and data poisoning.

Interests: Computational Social Science, Mental Health & Psychopathology, AI for Human Understanding

Undergraduate Student, Division of Social Science & AI Convergence. Focusing on computational social science — studying major mental health conditions such as depression, bipolar disorder, anxiety, and obsessive-compulsive disorder through data, and combining human psychology with modern AI to deepen our understanding of people. Also interested in conducting the full research cycle — from data collection to modeling and visualization — and in trustworthy AI for infectious disease forecasting.