I am a Ph.D. candidate in the Department of Computer Science at North Carolina State University. My research interests span a broad range in artificial intelligence, machine learning and personalized learning technologies. Specifically, I have worked on the problem of interactive narrative adaptation in educational games, for which I’ve studied deep neural network-based simulated player modeling, reinforcement learning-based game content adaptation, and data-driven player goal recognition.
I’m also a game developer. I work closely with the IntelliMedia digital artists group in the development of the educational game INSPIRE using Unity3D.
In 2013, I received my M.S. degree in Computer Science from Beijing University of Technology where I conducted research on real-time water rendering for particle system-based fluid simulation. I also have multiple years of experience in 3D game development.
Ph.D., Computer Science (expected 2018)
North Carolina State University, Advisor: Dr. James Lester
M.S., Computer Science (2013)
Beijing University of Technology, Advisor: Dr. Baocai Yin
B.E., Software Engineering (2010)
Beijing University of Technology
Pengcheng Wang, Jonathan Rowe, Wookhee Min, Bradford Mott, and James Lester. High-Fidelity Simulated Players for Interactive Narrative Planning. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 3884-3890, Stockholm, Sweden. 2018.
Pengcheng Wang, Jonathan Rowe, Wookhee Min, Bradford Mott, and James Lester. Simulating Player Behavior for Data-Driven Interactive Narrative Personalization. Proceedings of the Thirteenth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2017), pp. 255-261, Snowbird, Utah. 2017.
Pengcheng Wang, Jonathan Rowe, Wookhee Min, Bradford Mott, and James Lester. Interactive Narrative Personalization with Deep Reinforcement Learning. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), pp. 3852-3858, Melbourne, Australia. 2017.
Pengcheng Wang, Jonathan Rowe, Bradford Mott, and James Lester. Decomposing Drama Management in Educational Interactive Narrative: A Modular Reinforcement Learning Approach. Proceedings of the Ninth International Conference on Interactive Digital Storytelling (ICIDS 2016), pp. 270-282, Los Angeles, California. 2016.
Pengcheng Wang, Dehui Kong, Yong Zhang, and Baocai Yin. Adaptive particle shape setting and normal calculation methods in fluid rendering. Multimedia Tools and Applications, 71(2), pp. 517–532, 2013.
Pengcheng Wang, Yong Zhang, Dehui Kong, and Baocai Yin. A Real-Time Fluid Rendering Method with Adaptive Surface Smoothing and Realistic Splash. Proceedings of the Nineteenth International Conference on Advances in Multimedia Modeling (MMM 2013), pp.468-478, Huangshan, China, 2013.
Publication list on Google Scholar
Co-organized the Deep Learning for Interactive Digital Entertainment tutorial at the Thirteenth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2017)
Member: Phi Kappa Phi (2015)
Outstanding Master’s Thesis Award in BJUT (2013)
Graduate Student Scholarship in BJUT (2011)
Outstanding Student Award to Receive a Bachelor’s Degree in BJUT (2010)
Third Prize in 2nd China College Students’ Software Development Innovation Competition (2009)
Third Prize in Microsoft Imagine Cup, Software Development Contest in China (2009)
Outstanding Undergraduate Student Award in BJUT (2009)
Student Technical Innovation Award in BJUT (2009)
Undergraduate Student Scholarship in BJUT (2007-2009)
■ Samsung Advanced Institute of Technology, Beijing, China (Jul 2012 – Oct 2012)
Intern in medical image analysis group
In charge of the development of medical data visualization module with multiplanar reformation and curved planar reformation
■ Baidu Inc., Beijing, China (Dec 2012 – Mar 2013)
Intern in the Baidu Map group
In charge of the development of the 3rd-party data integrity module and the web page response exception detection module
INSPIRE: A Self-Adaptive Personalized Behavior Change System for Adolescent Preventive Healthcare, 2014-2018.