Feng Yu
Assistant ProfessorMathematical Sciences
Dr. Feng Yu joins UTEP from the University of Minnesota Twin Cities (UMN), where he was a postdoctoral associate in the School of Mathematics. His research focuses on high-dimensional and robust statistics, nonconvex optimization, machine learning, and data science. He has developed advanced robust estimators in matrix regression and subspace recovery with applications in computer vision and cybersecurity. Dr. Yu earned his Ph.D. in Mathematics from the University of Central Florida (UCF) and previously held postdoctoral positions at Old Dominion University and SUNY Albany. He is a member of IEEE and SIAM and enjoys movies and hiking.
No info available.
| Term | Course | Section | Syllabus |
|---|---|---|---|
| Fall 2025 | DS 6390 - DS Research Collaborative | 16266 | |
| Fall 2025 | DS 6390 - DS Research Collaborative | 16488 | |
| Fall 2025 | STAT 6428 - Intro to Statistical Analysis | 15687 | |
| Fall 2025 | MATH 1508 - Precalculus | 18452 | Syllabus |
| Fall 2025 | STAT 3325 - Prob & Applied Statistics | 11939 | Syllabus |
| Fall 2025 | STAT 6370 - Special Topics | 16525 |
| Term | Course | Section | Syllabus |
|---|---|---|---|
| Spring 2025 | DS 6390 - DS Research Collaborative | 28011 | |
| Spring 2025 | STAT 5388 - Multivariate Data Analysis | 20835 | Syllabus |
| Spring 2025 | STAT 6388 - Multivariate Data Analysis | 25071 | Syllabus |
| Fall 2024 | STAT 5195 - Graduate Seminar | 10684 | Syllabus |
| Fall 2024 | STAT 6195 - Graduate Seminar | 14567 | Syllabus |
| Term | Course | Section | Evaluation |
|---|---|---|---|
| Spring 2025 | STAT 5388 - Multivariate Data Analysis | 20835 | Evaluation |
| Spring 2025 | STAT 6388 - Multivariate Data Analysis | 25071 | Evaluation |
| Fall 2024 | STAT 5195 - Graduate Seminar | 10684 | Evaluation |
| Fall 2024 | STAT 6195 - Graduate Seminar | 14567 | Evaluation |
Dr. Feng Yu joins UTEP from the University of Minnesota Twin Cities (UMN), where he was a postdoctoral associate in the School of Mathematics. His research focuses on high-dimensional and robust statistics, nonconvex optimization, machine learning, and data science. He has developed advanced robust estimators in matrix regression and subspace recovery with applications in computer vision and cybersecurity. Dr. Yu earned his Ph.D. in Mathematics from the University of Central Florida (UCF) and previously held postdoctoral positions at Old Dominion University and SUNY Albany. He is a member of IEEE and SIAM and enjoys movies and hiking.
No info available.