Dr. Yuzhou Chen: Opening for fully funded Ph.D. positions in Department of Computer and Information Science at Temple University
[招生简介]
Several fully-funded Ph.D. positions are available inDepartment of Computer and Information Science at Temple University for Fall 2023. Current research topics include but not limited to:
Deep learning for graphs, including graph neural networks, graph mining, etc;
Time-series analysis, including spatio-temporal forecasting, time-series anomaly detection, etc;
Topological and geometric methods in statistics, including topological data analysis, higher-order structures analysis in networks, etc;
Machine learning, statistical methods, and applications in energy systems, blockchain, health, and satellite data, etc.
[招生要求]
Ideal candidates at the PhD level are highly self-motivated and have backgrounds specializing in computer science, statistics, mathematics, electrical engineering, or physics, in Bachelor’s or Master’s degree. Note that a Master’s degree is not required but considered as a plus.
[具体申请]
Email Dr. Yuzhou Chen (yuzhou.chen@temple.edu) using the subject “Application for Ph.D. position in CIS at Temple University – [Name]”. Include your CV, current academic status, and brief highlights of AI/ML/Statistics/Mathematics-related projects. Candidates will be considered until the positions are filled.
[导师简介]
Dr. Yuzhou Chen (https://yuzhouguangc.github.io/yuzhou/) is an Assistant Professor in Department of Computer and Information Sciences at Temple University. Before joining Temple University, he worked as a postdoctoral scholar in Department of Electrical and Computer Engineering at Princeton University (2021-2022). Dr. Chen was an NSF Research Fellow at Lawrence Berkeley National Laboratory (2020-2022). Dr. Chen received the Ph.D. degree in Statistics from Southern Methodist University (2017-2021). His research has appeared in the top machine learning and data mining top conferences, including ICML, ICLR, NeurIPS, KDD, AAAI, ICDM, etc. Dr. Chen was the recipient of 2022 and 2021 Best Paper Award of the Section for Statistics in Defense and National Security (SDNS) of the American Statistical Association (ASA) and 2021 Chateaubriand Fellowship from the Embassy of France in the United States.
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