معرفی
Dr. Jianya Lu is a Lecturer in the Department of Mathematical Sciences at the University of Essex, affiliated with the School of Mathematics, Statistics and Actuarial Science (SMSAS). He holds a PhD in Mathematics from the University of Macau (2022), following an MS.c in Probability Theory (Central South University, 2018) and a BS.s in Applied Mathematics (Henan Normal University, 2015). His research focuses on stochastic processes, stochastic algorithms, Stein’s method, and their applications in statistical learning, particularly in reinforcement learning and deep neural networks. He has contributed to methodologies in stochastic dynamics for algorithm interpretation and optimization.
Education:
- PhD in Mathematics, University of Macau, 2022
- MS.c in Probability Theory, Central South University, 2018
- BS.s in Applied Mathematics, Henan Normal University, 2015
Research Interests: Dr. Lu’s work bridges theoretical probability and applied machine learning. Key areas include:
- Stochastic Algorithms: Analysis of reinforcement learning, deep neural networks, and stochastic gradient methods.
- Statistical Learning: Federated learning frameworks, distribution estimation via GANs, and change-point detection in time series.
- Limit Theorems: Invariance principles, moderate deviations, and convergence of stochastic processes.
Publications: Recent work emphasizes algorithmic approximation (e.g., DQNs via stochastic delay equations) and statistical methodologies (e.g., Euler-Maruyama scheme analysis). Themes include optimization, numerical analysis, and probabilistic modeling in high-dimensional spaces.
Labs/Teams: No specific lab affiliations mentioned, but his research aligns with computational statistics and stochastic modeling groups at the University of Essex.
