معرفی
Per August Jarval Moen is a Doctoral Research Fellow in the Faculty of Mathematics and Natural Sciences at the University of Oslo, affiliated with the Statistics and Data Science group. His research focuses on changepoint and anomaly detection in high-dimensional data streams, with additional expertise in minimax theory, computational statistics, and high-dimensional statistics.
- Education:
- Master of Advanced Study in Mathematical Statistics, King's College, University of Cambridge (2020-2021)
- Bachelor's degrees in Mathematics with Informatics and Mathematics & Economics, University of Oslo (2016-2019)
Research Interests:
His work addresses challenging problems in real-time anomaly detection and theoretical bounds for statistical methods. He develops algorithms for sparsity-adaptive changepoint estimation and contributes to likelihood-free computational frameworks for binary data analysis.
Publications Trends:
Recent research spans theoretical advancements in minimax rates, practical methodologies for high-dimensional changepoint detection, and open-source software implementations (e.g., R integration with C).
Scientific Awards:
- Aker Scholarship (2020)
- Krafthack 2022 Winner (with Martin Tveten)
Teaching & Supervision:
He serves as a teaching assistant for STK4900 and STK3100/STK4100, and co-supervises Han Yu's master's project on hydropower sensor data modeling.
