معرفی
Matey Neykov is an Assistant Professor of Statistics and Data Science at Northwestern University, serving as Director of Graduate Studies. He holds a Ph.D. in Biostatistics from Harvard University (2015), with postdoctoral research at Princeton University and prior faculty positions at Carnegie Mellon University. His research focuses on high-dimensional statistics, nonparametric estimation, variable selection, and statistical applications in medical contexts such as electronic health records and personalized medicine.
Education:
- Ph.D. in Biostatistics, Harvard University (2015)
- B.S. in Applied Mathematics, Sofia University
- Postdoctoral Research: Princeton University (Department of Operations Research and Financial Engineering)
Research Interests:
- High-dimensional inference and dimension reduction
- Nonparametric methods under shape constraints
- Statistical machine learning applications in healthcare
- Graph property testing and conditional independence testing
Publications Trends: Recent work emphasizes theoretical advancements in nonparametric regression, robust estimation under constraints, and optimal transport-based hypothesis testing. Key themes include minimax rate characterizations, adversarial noise resilience, and applications in biomedical data analysis.
Labs/Teams: Engages with interdisciplinary teams in statistics, machine learning, and biomedical informatics, focusing on translating theoretical insights into practical methodologies for healthcare analytics.
