Hyoung Suk Shim is an assistant professor of finance at the School of Business of the College of Staten Island. Prior to joining CSI as an assistant professor, he was an economist at the ADP Research Institute of Automatic Data Processing, a substitute lecturer of the School of Business, and a senior econometrician of the CUNY High Performance Computing Center. He received a Ph.D. in Economics at The Graduate School of The City University of New York in 2015, and a B.A. in Economics and a B.S in Applied Statistics in 2009 from Yonsei University, Korea. He specializes in large-scale statistical computing that enhances statistical analysis of big data on a high performance computing system, and general econometric methods (time series and panel data analysis).

Contact Information

Hyoung Suk Shim, PhD
Assistant Professor
College of Staten Island
Phone : 718.982.3309
Contact Via Email

Department: School of Business / Accounting and Finance

Discipline: Large-scale statistical computing, Econometrics

Research Title

Developing Parallel Sparse Machine Learning Algorithms for Big Data

Description of Research

This project proposes development of distributed memory parallel machine learning algorithms for big data analytics that can be implemented on conventional HPC machines such as massively parallel processing (MPP) or symmetric multiprocessing (SMP). The PI focuses particularly on utilizing parallel sparse matrix computation algorithms such as in ScaLAPACK for a parallel distributed memory system, or cuSPARSE for a HPC machine with NVIDIA GPU accelerators. The PI also utilizes parallel I/O techniques in conjunction with the parallel sparse matrix computation algorithm for the big data analytics. The expected outcome of this project is to make a parallel sparse machine learning library for big data that can be implemented on MPP, SMP, and GPU accelerator machines.

Publications pertaining to the HPC over the past five years

"The Long-Run Effect of Environmental Issues on Stock Market Performance: Evidence from the U.S. Stock Market" (with Kyuhee Joo and Wonsik Sul), International Business Journal, 28(3), 101-133.


“Foreign Direct Investment in State Owned Enterprises”, (with Kyuhee Joo and Wonsik Sul), Advances in Economics and Business Vol. 5(5), pp. 265 - 279


“Disaggregate Multimodal Travel Demand Modeling Based on Road Pricing and Access to Transit” (with Jonathan Peters and Michael Kress), Transportation Research Record: Journal of the Transportation Research Board, 2263, 57-65, (2011).


“Electronic Toll Collection System and Travel Demand: A Field Experiment of Toll Facilities in New York City” (with Jonathan Peters), Journal of Regional Studies & Development, 20, 407-438, (2011).

Current Funding

2017 NSF CAREER Grant (CISE directorate): Pending
2017 NSF CRII (CISE Research Initiation Initiative, NSF 16-565): Pending 

Collaborators on the HPCC based Research Project

Developing Parallel Sparse Machine Learning Algorithms for Big Data 

“Taxi Fare Mechanism: New York City Yellow Cab Trips” (Title changed from “Principal versus Agent: Market Operation Mechanism of the New York City Taxicab Industry”), 2017

“New York City Taxis: Demand and Revenue in an Uber World” (with Kristin Mammen), 2017. 

Contribution of the HPC in your research

Since my research interest has been developing and applying large-scale statistical computing for Big Data analytics, utilizing HPC systems is essential. The Big Data analytics techniques that I have developed are mostly implemented on conventional HPC systems such as MPP, SMP, and  GPU like accelerators. CUNY HPC center has provided sufficient support hardware and software for my research. I hope I can continuously have the support for my future research project.