Haesun Park

 Haesun Park

Haesun Park

Regents' Professor and Chair, School of Computational Science and Engineering

Dr. Haesun Park is a Regents' Professor and Chair in the School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A. She was elected as a SIAM Fellow in 2013 and IEEE Fellow in 2016 for her outstanding contributions in numerical computing, data analysis, and visual analytics. She was the Executive Director of Center for Data Analytics 2013-2015 and was the director of the NSF/DHS FODAVA-Lead (Foundations of Data and Visual Analytics) Center 2008-2014. She has published extensively in the areas of numerical computing, large-scale data analysis, visual analytics, text mining, and parallel computing. She was the conference co-chair for SIAM International Conference on Data Mining in 2008 and 2009 and an editorial board member of the leading journals in computational science and engineering such as IEEE Transactions on Pattern Analysis and Machine Intelligence, SIAM Journal on Matrix Analysis and Applications, and SIAM Journal on Scientific Computing. She was the plenary keynote speaker at major international conferences including SIAM Conference on Applied Linear Algebra in 1997 and 2015, and SIAM International Conference on Data Mining in 2011. Before joining Georgia Tech, she was a professor in Department of Computer Science and Engineering, University of Minnesota, Twin Cities 1987- 2005 and a program director in the Computing and Communication Foundations Division at the National Science Foundation, Arlington, VA, U.S.A., 2003 - 2005. She received a Ph.D. and an M.S. in Computer Science from Cornell University, Ithaca, NY in 1987 and 1985, respectively, and a B.S. in Mathematics from Seoul National University, Seoul, Korea in 1981 with the Presidential Medal for the top graduate.

hpark@cc.gatech.edu

Website

Research Focus Areas:
  • Big Data
  • High Performance Computing
  • Infrastructure Ecology
Additional Research:

Bioinformatics; Computer Vision


IRI Connections:

Peng Chen

Peng Chen

Peng Chen

Assistant Professor

Dr. Chen is an Assistant Professor in the School of Computational Science and Engineering. Previously he was a Research Scientist at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. Dr. Chen’s research is in the multidisciplinary fields of computational mathematics, data science, scientific machine learning, and parallel computing with various applications in materials, energy, health, and natural hazard. Specifically, his research focuses on developing fast, scalable, and parallel computational methods for integrating data and models under high-dimensional uncertainty to make (1) statistical model learning via Bayesian inference, (2) reliable system prediction with uncertainty quantification, (3) efficient data acquisition through optimal experimental design, and (4) robust control and design by stochastic optimization.

pchen402@gatech.edu

Office Location:
CODA | E1350B

Scientific Machine Learning (SciML) and Uncertainty Quantification (UQ)

Google Scholar

Research Focus Areas:
  • Advanced Materials
  • Geosystems
  • Machine Learning
Additional Research:

Bayesian InferenceInfectious DiseasesOptimal Experimental DesignPlasma FusionStochastic OptimizationUncertainty Quantification


IRI Connections:

Victor Fung

Victor Fung

Victor Fung

Assistant Professor of Computational Science and Engineering

Victor Fung is an Assistant Professor in the School of Computational Science and Engineering. Prior to this position, he was a Wigner Fellow and a member of the Nanomaterials Theory Insitute in the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory. A physical chemist by training, Fung now works at the intersection of scientific artificial intelligence, computing, and materials science/chemistry.

victorfung@gatech.edu

Office Location:
E1354B | CODA Building, 756 W Peachtree St NW, Atlanta, GA 30308

Fung Group

Google Scholar

Research Focus Areas:
  • Advanced Materials
  • Big Data
  • Computational Materials Science
  • Machine Learning
Additional Research:

Quantum chemistrySurrogate models for quantum chemistryData-driven inverse designChemically-informed machine learningHigh-throughput computational simulations


IRI Connections:

Xiuwei Zhang

 Xiuwei Zhang

Xiuwei Zhang

Assistant Professor

Xiuwei Zhang is an Assistant Professor and J. Z. Liang Early Career Assistant Professor in the School of Computational Science and Engineering at the Georgia Institute of Technology. Her research group works on applying machine learning and optimization skills in method development and data analysis for single-cell RNA-Seq data and other types of data on single cell level. The goal is to study cellular mechanisms during differentiation, development of cells and disease progression. 

Zhang was a postdoc researcher in Prof. Nir Yosef‘s group at UC Berkeley. She obtained a Ph.D. in computer science under the supervision of Prof. Bernard Moret in the Laboratory for Computational Biology and Bioinformatics, EPFL (École Polytechnique Fédérale de Lausanne), Switzerland. 

Before moving to the United States, she was a postdoc researcher in Dr. Sarah Teichmann’s group at the European Bioinformatics Institute (EBI) and Wellcome Trust Sanger Institute in Cambridge, UK. Zhang was supported by a Fellowship for Prospective Researchers and an Advanced Postdoc Mobility Fellowship from Swiss National Science Foundation (SNSF) from Aug. 2012 to Jul. 2015. She was a research fellow in the 2016 Simons Institute program on Algorithmic Challenges in Genomics. Her Erdös number is 3.

xzhang954@gatech.edu

Website

Research Focus Areas:
  • Machine Learning

IRI Connections: