I am a fourth-year Ph.D. student in the Department of Statistics & Data Science at Carnegie Mellon University. I am fortunate to be advised by Professor Gonzalo Mena and Professor Sivaraman Balakrishnan. I hold a B.S. in Mathematical Sciences from Seoul National University.

My research focuses on statistical theory and methodology for dynamical systems and machine learning for scientific discovery, with applications in high-energy physics and growing interests in single-cell genomics.

Prior to CMU, I worked as a research scientist at Krafton AI and as a quantitative analyst in Hyperithm. At SNU, I was fortunate to be advised by Professor Ernest K. Ryu and Professor Sanghack Lee on research projects around theoretical aspects of machine learning, mainly optimization theory and graphical models.

You can find my CV here.

Contact

Email: soheuny [at] andrew [dot] cmu [dot] edu

News

• 2025.08. A paper entitled “Convergence Analyses of Davis–Yin Splitting via Scaled Relative Graphs II: Convex Optimization Problems” has been accepted to Optimization.
• 2024.12. I will be presenting our work entitled “Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions” at ML4PS Workshop at NeurIPS 2024.
• 2024.06. A paper entitled “Convergence Analyses of Davis-Yin Splitting via Scaled Relative Graphs” has been accepted to SIAM Journal on Optimization (SIOPT).
• 2024.01. A paper entitled “Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models” has been accepted in AISTATS 2024.