University of Michigan - Shanghai Jiao Tong University Joint Institute

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Paul Weng

Paul Weng

助理教授

办公室
  406
电话
  +86-21-34206765 转 4061
传真
  +86-21-34206525
邮件
  nc.ud1544678173e.utj1544678173s@gne1544678173w.lua1544678173p1544678173
网站
  http://weng.fr/

教育背景

Ph.D. Artificial Intelligence, Pierre and Marie Curie University (UPMC), Paris (2006)
M.Sc. Artificial Intelligence, Pierre and Marie Curie University (UPMC), Paris (2003)
M.Sc. Statistics, French School of Statistics and Information Analysis (ENSAI), Bruz (2000)
B.Sc. Computer Science, University of Rennes I, Rennes (1998)

工作经历

2018 – pres. Assistant Professor, UM-SJTU Joint Institute, Shanghai Jiao Tong University
2015 – 2017. Assistant Professor, CMU-SYSU Joint Institute of Engineering, Sun Yat-sen University
2015 Visiting Faculty, Electrical and Computer Engineering Department, Carnegie Mellon University
2008 – 2014 Associate Professor, Department of Computer Science, Pierre and Marie Curie University
2006 – 2007 Assistant Professor, Department of Computer Science, Pierre and Marie Curie University
2000 – 2002 Junior Quantitative Analyst, SG Securities, Société Générale

荣誉奖励

  • Best Paper Award, Multidisciplinary International Workshop on Artificial Intelligence (2016)
  • Best Paper Award, Multidisciplinary International Workshop on Artificial Intelligence (2013)

发表论文

  • M. Hadi Amini, Paul McNamara, Paul Weng, Orkun Karabasoglu, Yinliang Xu, “Hierarchical Electric Vehicle Charging Aggregator Strategy Using Dantzig-Wolfe Decomposition,” IEEE Design & Test, DOI: 10.1109/MDAT.2017.2759505 (October 2017).
  • Róbert Busa-Fekete, Balázs Szörenyi, Paul Weng, Shie Mannor, “Multi-objective Bandits: Optimizing the Generalized Gini Index”, International Conference on Machine Learning (ICML), 2017.
  • Hugo Gilbert, Paul Weng, Yan Xu, “Optimizing Quantiles in Preference-based Markov Decision Processes,” AAAI Conference on Artificial Intelligence, 2017.
  • Viet Hung Nguyen, Paul Weng, “An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems”, International Conference on Combinatorial Optimization and Applications (COCOA), Lecture Notes in Computer Science, 2017.
  • Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng, “Solving MDPs with Skew Symmetric Bilinear Utility Functions,” International Joint Conference in Artificial Intelligence (IJCAI), 2015.
  • Emmanuel Hadoux, Aurélie Beynier, Nicolas Maudet, Paul Weng, Anthony Hunter, “Optimization of probabilistic argumentation with Markov Decision Models,” International Joint Conference on Artificial Intelligence (IJCAI), 2015.
  • Balázs Szörenyi, Róbert Busa-Fekete, Paul Weng, Eyke Hüllermeier, “Qualitative Multi-Armed Bandits: A Quantile-Based Approach,” International Conference on Machine Learning (ICML), 2015.
  • Róbert Busa-Fekete, Balázs Szörenyi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier, “Preference-based Reinforcement Learning: Evolutionary Direct Policy Search using a Preference-based Racing Algorithm,” Machine Learning, DOI: 10.1007/s10994-014-5458-8 (December 2014).
  • Róbert Busa-Fekete, Balázs Szörenyi, Paul Weng, Weiwei Cheng, Eyke Hüllermeier, “Top-k Selection based on Adaptive Sampling of Noisy Preferences,”  International Conference on Machine Learning (ICML), 2013.
  • Wlodzimierz Ogryczak, Patrice Perny, Paul Weng, “A Compromise Programming Approach to Multiobjective Markov Decision Processes,” International Journal of Information Technology & Decision Making, DOI 10.1142/S0219622013400075 (September 2013).

专业贡献

  • Editor of AI Resources
  • Chair of the demonstration track at IJCAI-ECAI 2018
  • Co-chair of Asian Workshop on Reinforcement Learning 2016-2017
  • Co-chair of Multidisciplinary Workshop on Advances in Preference Handling 2014-2015
  • Program co-chair of Multidisciplinary International Workshop on Artificial Intelligence 2014

所授课程

  • CMU-SYSU Joint Institute: 18-660 Numerical Methods for Engineering Design and Optimization (with Prof. Xin Li)
  • Pierre and Marie Curie University: DJ Decision and games; IREC Pattern recognition and introduction to decision; MAPSI Probabilistic and statistical models and algorithms for computer science; AN Numerical Analysis; LI 317 General algorithmics ; LI214 Discrete Structure; 1i002 Introduction to programming in C