Topological Data Analysis
Statistical Inference on Topology and Geometry
Machine Learning Theory
Computational Topology
Clustering
2013 – 2018
Ph.D. in Statistics & Machine Learning, Carnegie Mellon University
2013 – 2014
M.S. in Statistics, Carnegie Mellon University
2006 – 2013
B.S. in Mathematics, Computer Science, Statistics, Seoul National University
2023 – Present
Assistant Professor, Department of Statistics, Seoul National University
2020 – 2023
Non Permanent Researcher, DataShape, Inria Saclay
2021 – 2023
Non Permanent Researcher, Laboratoire de Mathématiques d’Orsay, Université Paris-Saclay
2018 – 2020
PostDoc, DataShape, Inria Saclay
Kwangho Kim, Jisu Kim, Manzil Zaheer, Joon Sik Kim, Frédéric Chazal, Larry Wasserman, PLLay: Efficient Topological Layer based on Persistence Landscapes (2021)
Jisu Kim, Jaehyeok Shin, Frédéric Chazal, Alessandro Rinaldo, Larry Wasserman, Homotopy Reconstruction via the Cech Complex and the Vietoris-Rips Complex (2020)
Jisu Kim, Jaehyeok Shin, Alessandro Rinaldo, Larry Wasserman, Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension (2019)
Eddie Aamari, Jisu Kim, Frédéric Chazal, Bertrand Michel, Alessandro Rinaldo, Larry Wasserman, Estimating the Reach of a Manifold (2019)
Jisu Kim, Alessandro Rinaldo, Larry Wasserman, Minimax Rates for Estimating the Dimension of a Manifold (2019)
Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman, Statistical Inference for Cluster Trees (2017)
2019
Umesh Gavasakar Memorial Thesis Award, by Department of Statistics, Carnegie Mellon University
2013 – 2018
Samsung Scholarship (for Doctoral degree)
2017
TA of the Year Award, by Department of Statistics, Carnegie Mellon University
2017
Student of the year for 2017, by the American Statistical Association Pittsburgh Chapter
2016
α TA Award, by Machine Learning Department, Carnegie Mellon University
