• Ph.D., Cornell University, August 1999

• B.S., Seoul National University , August 1993

• My research focuses on the design and analysis of efficient, reliable, and mathematically grounded algorithms for learning, optimization, and inference, with particular emphasis on two current research directions: Physical AI Safety and Digital Finance. 

• The foundation of my research has been built on three closely connected pillars: global optimization, dynamical systems, and statistical learning. My early work investigated stability analysis of nonlinear dynamical systems, convergence properties of optimization algorithms, equilibrium characterization, and trajectory-based global optimization. A central theme throughout this research has been the strong connection between optimality and equilibrium, using dynamical-system perspectives to solve optimization and learning problems, while applying optimization and topological methods to analyze nonlinear systems. 

• Building on these mathematical foundations, I subsequently developed stable and scalable machine-learning methods, including kernel-based approaches such as support vector machines and Gaussian processes, as well as statistical learning techniques for prediction, clustering, domain adaptation, and data-driven decision making. In parallel, I extended these theoretical and computational tools to computational finance, developing models for derivative pricing, financial forecasting, model calibration, asset allocation, and risk management. 

• My current research brings these foundations together in two major areas.

Physical AI Safety

• • My research in Physical AI Safety focuses on developing intelligent systems that can perceive, reason, and act reliably in the physical world. I study robust perception, predictive modeling, safe decision-making, stable control, and runtime assurance, with particular attention to uncertainty, distribution shifts, adversarial perturbations, and sim-to-real challenges.

  • A key direction is to combine simulation-based safety evaluation with real-world validation, enabling Physical AI systems to be tested, verified, and improved before and during deployment. 

Digital Finance

• • My research in Digital Finance integrates artificial intelligence, computational finance, blockchain, and generative simulation to develop intelligent and secure financial systems. It covers market forecasting, asset pricing, portfolio and risk management, decentralized finance, and digital financial infrastructure.

  • A central goal is to move beyond conventional historical-data analysis toward financial systems that can simulate possible market scenarios, evaluate alternative decisions, and support reliable decision-making under uncertainty.

Physical Ai safety

Safe physical intelligence

• Robust perception & State estimation

• Predictive world models & generative simulation

• Safe planning & robust decision intelligence

• Stable control & verified optimization

• Runtime safety assurance & explainability

Trustworthy ai foundations

• Privacy-preserving & fair physical ai

• Stable & Robust Machine Learning

• Data engineering

Digital Finance

Financial AI & Computational Finance

• Financial Intelligence & Market Forecasting

• Computational Finance & Asset Pricing

• Intelligent Portfolio & Risk Management

Digital assets & Blockchain

• Blockchain, Digital Assets & Decentralized Finance

• Secure Finance Infrastructure & Digital Payments

• Member of the National Academy of Engineering of Korea (Computer Science and Engineering)

• Fellow, Board member: the Asia Pacific Industrial Engineering and Management Society (APIEMS)

• Associate Editor: Applied Stochastic Models in Business and Industry

• Managing Editor, Manuscript Editor: Journal of Industrial Engineering and Management Systems (2009 - 2023).

• Leader for privacy-preserving convergence technology working group (2021)

• Guest Editor: Journal of Intelligent Manufacturing (2015)

• Contacting Associate Editor: Decision Sciences, (2013)

• Editor-in-Chief: Management Science and Financial Engineering (2012 – 2014)

• Associate Editor: International Journal of Management Science (2005 – 2011)

• Organizing Chair for Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS 2014)

• General Organizing Chair for the international workshop on learning, computations, and finance (LCF 2010)

• Programmer Committee for the 7th & 8th international conference on data mining.

• Paper Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks, IEEE Transactions on Automatic Control,  IEEE Transactions on Circuits and Systems, Pattern Recognition, Pattern Recognition Letter, IEEE Transactions on Knowledge Discovery and Data Engineering, IEEE Transactions on System, Man, and Cybernetics, Journal of Machine Learning Research, Electronics Letters, Journal of banking and Finance, International Review of Economics and Finance, Journal of Industrial Engineering and Management Systems, International Journal of Management Science, Annals of Operations Research, Expert Systems with Applications, Applied Soft Computing, Asia-Pacific Journal of Financial Studies, Journal of the Korean Operations Research and Management Science Society, Journal of the Korean Institute of Industrial Engineers, Journal of Korean Mathematics Society, etc.

• Area Chair or Paper Reviewer for NeurIPS, ICML, ICLR, CVPR, AAAI, KDD, etc.