Dr Jianya Lu
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Email
jianya.lu@essex.ac.uk -
Telephone
+44 (0) 1206 872851
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Location
3A.524, Colchester Campus
Profile
Biography
Jianya Lu is a lecturer at the Department of Mathematical Sciences of the ºÚÁÏÍø. He received his BS.s in Applied Mathematics from Henan Normal University, China, and then went on to do his MS.c in Probability Theory at Central South University, China. He obtained PhD in Mathematics from the University of Macau, Macau, China under the supervision of Dr Lihu Xu. Jianya has a wide range of interests in stochastic processes, the limit theory, stochastic algorithms, Stein’s method and other topics in probability theory and statistical learning. Recently, Jianya has focused on the methodology of stochastic algorithms, such as reinforcement learning and deep neural networks, using stochastic dynamics to provide insights into algorithm interpretation and optimization.
Qualifications
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Ph.D. in Mathematics University of Macau, (2022)
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MS.c in Probability Theory Central South University, (2018)
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BS.s in Applied Mathematics Henan Normal University, (2015)
Appointments
ºÚÁÏÍø
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Lecturer in Statistics, Department of Mathematical Sciences, ºÚÁÏÍø (17/10/2022 - present)
Research and professional activities
Research interests
Stochastic Processes
Probability Limit Theorems and Moderate Deviations
Time Series
Stochastic Algorithms
Conferences and presentations
Statistical inference for operation control
Workshop on Statistical Learning, Macao, China, 28/7/2025
Approximation to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations
Maths Seminars, Tianjin, China, 14/7/2025
Self-Normalized Cramér-Type Moderate Deviation of Stochastic Gradient Langevin Dynamics
2025 Statistical Society of Canada (SSC) Annual Meeting, Saskatoon, Canada, 8/5/2025
Self-normalized Cramér-type moderate deviation of stochastic gradient Langevin dynamics
Statistics and Data Science Seminar, Birmingham, United Kingdom, 3/2/2025
Distribution estimation for time series via DNN-based GANs with an application to change-point estimation
Invited presentation, Maths and Stats Research Seminars, London, United Kingdom, 21/8/2023
Approximation to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations
Invited presentation, Swansea 2023 Probability summer workshop, Swansea, United Kingdom, 6/6/2023
Teaching and supervision
Current teaching responsibilities
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Financial Mathematics (MA226)
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Mathematics of Portfolios (MA311)
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Dissertation (MA981)
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Linear Regression Analysis (MA317)
Publications
Publications (1)
Dai, H., Fan, X. and Lu, J., Self-normalized Cramer-type Moderate Deviation of Stochastic Gradient Langevin Dynamics
Journal articles (4)
Lu, J., Mo, Y., Xiao, Z., Xu, L. and Yao, Q., (2025). . Machine Learning. 114 (9)
Chen, P., Lu, J. and Xu, L., (2022). . Applied Mathematics and Optimization. 85 (2)
Lu, J., Tan, Y. and Xu, L., (2022). . Bernoulli. 28 (2), 937-964
Jin, X., Li, X. and Lu, J., (2020). . Journal of Mathematical Analysis and Applications. 488 (2), 124063-124063
Conferences (1)
Wang, Y., Pan, B., Li, M., Lu, J., Kong, L., Jiang, B. and Kong, L., (2024).
Grants and funding
2025
LMS Scheme 4 Research in Pairs - Applicant Research Visit (Alberta, Canada)
London Mathematical Society