- System Analytics Lab.
- 042-350-3124 hyshin(at)kaist.ac.kr IE B/D E2-2 NO.3106
- DBLP Homepage
Faculty


Hayong Shin
Ph.D. in Industrial Engineering,
KAIST, 1991

Education
- 1985.2 Seoul National University Industrial Engineering B.S.
- 1987.2 KAIST Industrial Engineering M.S.
- 1991.8 KAIST Industrial Engineering Ph.D.
Research experience
- 1991~1993 : LG Electronics (Senior Researcher)
- 1993~1997 : CubicTek Ltd. (Research Director)
- 1997~2001 : DaimlerChrysler Corp. (Senior Specialist)
- 2001~Present : KAIST Dept. of Industrial & Systems Engineering (Assistant/Associate/Full Professor)
- 2005 : Editorial Board Member, Computer-Aided Design Journal
- 2010~2013: Society of CAD/CAM Engineers, Vice President
- 2012~2014 : Editor-In-Chief, Journal of Korean Institute of Industrial Engineers
- 2017~ Present : 'Asssociate Vice President of Office of Admissions' and 'Director of Industrial Engineering & Management Research Institute' and 'Principal of School of Freshman' (Plural Offices), KAIST
Research goal
- Optimal decision making via machine learning
- Stochastic optimization and Monte Carlo simulation
- Geometric modeling under uncertainty
Research area
Geometric Modeling under Uncertainty

We have studied various aspects of geometric modeling. Recently, we use machine learning techniques to handle uncertainty in geometric modeling. We typically use probabilistic graphical models to represent geometric variables tied with observed values.
Recent research projects are :
- 3D Reconstruction from Freehand Ultrasound Images
- Combining volumetric CT and optical scan data
Stochastic Optimization

We are also interested in stochastic optimization problems such as stochastic approximation and simulation optimization. techniques.
Recent research projects are :
- Global root finding with Gaussian Process Regression
- Simulation optimization for military RAM problem
Monte Carlo Simulation

Since many real systems are very large, complex and non-tractable in analytic way, simulation often gives important intuition and approximate solutions. We work on efficient Monte Carlo simulation and other computer experiments.
Some of the research topics in this domain are :
- Denoising Monte Carlo sensitivity estimates
- Bayesian Design of Computer Experiments

We have studied various aspects of geometric modeling. Recently, we use machine learning techniques to handle uncertainty in geometric modeling. We typically use probabilistic graphical models to represent geometric variables tied with observed values.
Recent research projects are :
- 3D Reconstruction from Freehand Ultrasound Images
- Combining volumetric CT and optical scan data
Stochastic Optimization

We are also interested in stochastic optimization problems such as stochastic approximation and simulation optimization. techniques.
Recent research projects are :
- Global root finding with Gaussian Process Regression
- Simulation optimization for military RAM problem
Monte Carlo Simulation

Since many real systems are very large, complex and non-tractable in analytic way, simulation often gives important intuition and approximate solutions. We work on efficient Monte Carlo simulation and other computer experiments.
Some of the research topics in this domain are :
- Denoising Monte Carlo sensitivity estimates
- Bayesian Design of Computer Experiments
Selected publications
- Taesik Lee, Hayong Shin, "Combining syndromic surveillance and ILI data using particle filter for epidemic state estimation", Flexible Service & Manufacturing Journal, published online (2014).
- Kang, Wanmo, Kyoung-Kuk Kim, and Hayong Shin. "Fairing the gamma: an engineering approach to sensitivity estimation." IIE Transactions, 46.4(2014):374-396.
- Seyoun Park, SM Lee, N Kim, JB Seo, Hayong Shin, "Automatic reconstruction of the arterial and venous trees on volumetric chest CT" Medical Physics, 40.7(2013).
- Seyoun Park, BD Jeong, JG Lee, Hayong Shin, "Hybrid grid generation for viscous flow analysis" International Journal for Numerical Methods in Fluids, 71.7(2013):891-909.
- Park, Seyoun, and Hayong Shin. "Efficient generation of adaptive Cartesian mesh for computational fluid dynamics using GPU." International Journal for Numerical Methods in Fluids 70.11 (2012): 1393-1404.
- Kang, Wanmo, Kyoung-Kuk Kim, and Hayong Shin. "Denoising Monte Carlo sensitivity estimates." Operations Research Letters 40.3 (2012): 195-202. - Lee, Duckwoong, Hayong Shin, and Byoung K.
- Choi. "Mediator approach to direct workflow simulation." Simulation Modelling Practice and Theory 18.5 (2010): 650-662.
- Park, Seyoun, and Hayong Shin. "Machining Tool Path Generation for Point Set." International Journal of CAD/CAM 8.1 (2009). - Directional Offset of a Spatial Curve for Practical Engineering Design, Lecture Notes in Computer Science, V.2669, pp.711-720, 2003
- An integrated CAPP/CAM system for stamping die pattern machining, Computer Aided Design, 35(2), pp.203-213, 2003
- Parametric Surface Adaptive Tessellation Based on Degree Reduction, Computers & Graphics, 26(5), pp.709 ~ 719, 2002
- Polygonal Chain Intersection, Computers and Graphics, 26(2), pp.341-350, 2002
- The conversion of a dynamic B-spline curve into piecewise polynomials in power form, Computer Aided Design, 34(4), pp.337-345, 2002
- Rational Bezier form of hodographs of rational Bezier curves and surfaces, Computer Aided Design, 33(4), pp.321-330, 2001
Teaching
- IE362 Applied Data Structures and Algorithms (2011.1, 2012.1, 2013.1)
- IE471 Introduction to Financial Engineering (2011.1, 2012.1, 2013.1)
- IE575 Structuring and Pricing Financial Products (2011.3, 2012.3, 2013.3)