News briefs:
  • Openings for PhDs, postdocs, research associates or interns: If you're interested in my research, please send me your CV.
  • Prospective master students: here are for some previous projects I advised.
  • Oct. 2016: one paper accepted at DA2PL
  • Sept. 2016: two papers accepted at MIWAI
  • July 2016: our project was funded by PGMO
  • Co-organizing the first Asian Workshop on Reinforcement Learning
  • June 2016: Xiaoliang Fan gave a talk at JRI.
  • May 2016: Hugo Gilbert visited us at JIE and JRI.
  • May 2016: one paper accepted at UAI
  • April 2016: Robert Busa-Fekete visited us at JIE and JRI.
  • April 2016: new paper accepted at COMSOC
  • February 2016: Hugo Gilbert, a PhD student in our group, got a second prize as young researcher at ROADEF for his work with Olivier Spanjaard.
  • June 2015: new paper accepted at ADT
  • May 2015: two papers accepted at IJCAI
  • May 2015: new paper accepted at ICML

Paul Weng

Paul Weng   翁安林   (CV)


JIE and JRI are partnerships between Sun Yat-sen University (SYSU) and Carnegie Mellon University (CMU). Both are international research and teaching institutes.  JIE offers single-degree and double-degree PhD programs. The single-degree option is a PhD program at SYSU, Guangzhou, China. The double-degree option is a PhD program, which delivers two PhD diplomas, one from SYSU and one from CMU. A double-degree PhD student usually spends the first year at SYSU, China, the second at CMU, USA, the third and fourth at SYSU and the last year at CMU (with possibility of OPT).  It is a fantastic opportunity to experience two different international research environments. For more information, please have a look at here and here.

SYSU-CMU Joint Institute of Engineering
Office 217B
Guangzhou Higher Education Mega Center
132 East Waihuan Road
Guangzhou, 510006, P.R. China
SYSU-CMU Shunde International Joint Research Institute
Office N201E
9 Eastern Nanguo Road
Shunde, Guangdong, 528300, P.R. China
Tel: +86 (0)757 2989 8708
Artificial intelligence; Algorithmic Decision theory; Markov decision processes/reinforcement learning; Qualitative/ordinal decision-making; Multiobjective/multicriteria decision-making; Preference learning/elicitation.