Haesun Park

Haesun Park is a Stephen Fleming Professor, Regents’ Professor, and Chair of the School of Computational Science and Engineering at the Georgia Institute of Technology. Her research areas include large-scale data analytics, numerical computing, visual analytics, text and social network analysis, high-performance computing, and bioinformatics. She was elected a SIAM Fellow in 2013, an IEEE Fellow in 2017, and an ACM Fellow in 2020; Georgia Tech sources associate these honors with contributions to numerical computing, data analysis, visual analytics, and leadership in computational science and engineering. She has also served as Executive Director of the Center for Data Analytics and Director of the NSF/DHS FODAVA-Lead Center.

• August 2020–Present·School of Computational Science and Engineering, Georgia Institute of Technology·Chair
• July 2019–Present·School of Computational Science and Engineering, Georgia Institute of Technology·Regents’ Professor
• July 2005–Present·School of Computational Science and Engineering, Georgia Institute of Technology·Professor
• 2008–2014·NSF/DHS FODAVA-Lead Center·Director
• 2013–2015·Center for Data Analytics (CDA)·Executive Director
• 2003–2005·National Science Foundation, Division of Computing and Communication Foundations·Program Director
• 1987–2005·Department of Computer Science and Engineering, University of Minnesota Twin Cities·Assistant Professor (1987–1993), Associate Professor (1993–1998), Professor (1998–2005)
• 2008–2018·Division of Computational Sciences, Korea Institute for Advanced Study (KIAS)·KIAS Scholar

• 1987·Cornell University·Ph.D. in Computer Science (minor in Mathematics)
• 1985·Cornell University·M.S. in Computer Science
• 1981·Seoul National University·B.S. in Mathematics (Summa Cum Laude)
  • Received the Presidential Medal for the top graduate.

• The Research page lists projects on nonnegative matrix and tensor factorization, hypergraph analysis and community detection, large-scale topic discovery, dimension reduction, and distributed data analytics.
• SmallK is a high-performance software package for nonnegative matrix factorization; its documentation describes distributed MPI-FAUN implementations and identifies Haesun Park as a Georgia Tech project lead/contributor.
• The Publications page provides a current publication list, including 2025 work on multi-type data co-embedding, active-set thresholding for nonnegative least squares, and randomized algorithms for symmetric nonnegative matrix factorization.

Sources checked on 2026-09-23. See persons/_review/63_Haesun Park/reference.md for the evidence log.