Roles and responsibilities
Research Officer in Computer Vision and Graphics team of Digital Technologies Research Centre. Conducting research and development for research excellence and business innovation.
Current research and/or projects
Pengcheng is collaborating with government agencies and industry partners to work on data science projects and applications.
Research and/or project statements
- Invented a unified deep learning framework for multimodal multidimensional data.
- Developed 3-D data processing approaches for conducting statistical shape analysis of large data sets.
- Developed 3-D anthropometry design tools for the Department of National Defence (Canada) and the US Center of Disease Control (CDC).
- Ph.D. candidate Electrical and Computer Engineering, Carleton University
- M.S. Computer Science, University of Ottawa, 2007
- Advisor for undergraduate and graduate students on applied deep learning research.
- Reviewer for top conferences and journals.
- Assessor for Creative Destruction Lab, Toronto, on Computer Vision and AI startups.
- NRC Long Service Award for public service (2017)
- NRC-ICT Certificate of Excellence (2016)
- NRC-ICT Award for outstanding client services (2015)
- US NIOSH Alice Hamilton Award Honourable Mention - Engineering & Control Category (2014)
- NRC-ICT Award for achieving top results in international contest (2014)
- Recognition of contribution to innovative IT research, programs and projects - NRC Canada (2013)
- NRC-IIT Outstanding Achievers Award (2008)
- Active Volunteer award by Let’s Talk Science (2006)
- Outstanding Volunteer award by Let’s Talk Science (2005)
- Certificate of outstanding contribution in reviewing for Pattern Recognition (Elsevier, October 2018)
- Certificate of outstanding contribution in reviewing for Computer-Aided Design (Elsevier, August 2018)
- Certified Vision Professionals - Basic Level (AIA Global association for vision information, October 2015)
P. Xi, R. Goubran, C. Shu, "Cardiac Murmur Classification in Phonocardiograms using Deep Recurrent-Convolutional Neural Networks", Book chapter in “Frontiers in Pattern Recognition and Artificial Intelligence” by World Scientific, https://doi.org/10.1142/11362, November 2019.
P. Xi, C. Shu, R. Goubran, "Comparing 2D Image Features on Viewpoint Independence Using 3D Anthropometric Dataset", Int. J. of the Digital Human, 1(4) (2016), pp. 412-425.
Z. Zhuang, C. Shu, P. Xi, M. Bergman, M. Joseph, "Head-and-Face Shape Variations of U.S. Civilian Workers”, Applied Ergonomics, 44(5) (2013), pp. 775-784.
R. Ball, C. Shu, P. Xi, M. Rioux, J. Molenbroek, D.V. Eijk, “A Comparison of Chinese and Caucasian Head Shapes", Applied Ergonomics 41(6) (2010), pp. 832-839.
J. Boisvert, C. Shu, S. Wuhrer, P. Xi, “Three-Dimensional Human Shape Inference from Silhouettes: Reconstruction and Validation", Machine Vision and Applications, 24(1) (2013), pp. 145-157.
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