Pongsak Lasang, Ph.D.
Strategy & Planning Office
Pongsak heads the Strategy & Planning Office of Panasonic R&D Center Singapore. He focuses on defining and formulating the company’s strategy and direction for future growth and sustainability, as well as creating customer and lifestyle-centric innovative business solutions for regional and worldwide partners.
He is also actively researching cutting-edge technologies in the areas of AI, Robotics, Autonomous Vehicles, Lightweight Deep Learning, 3D Scene Understanding, and New Sensors. He places emphasis on innovation-driven solutions to resolve customers’ problems. Leveraging the advancement of Singapore and its strategic location in ASEAN, he is working closely with regional/local partners and Singapore’s government to bring the technologies of Panasonic R&D Center Singapore into full play for practical use and thus contribute to the betterment of people’s lives.
He earned his Bachelor’s Degree in Electronics and Telecommunication Engineering in 2005, Master’s Degree in Electrical Engineering in 2006, and Ph.D. in Electrical and Computer Engineering in 2016, all of which were from King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand. In November 2006, he joined Panasonic R&D Center Singapore as an intern. Since then, he has been developing competitive image processing AI & 3D technologies and continually contributing to businesses. His co-work on Motion Blur Removal and Image Denoising with Deep Learning received the 1st Place Winner Best Paper Award from the IEEE International Conference on Consumer Electronics (ICCE), 2010, and the Best Paper Award from the 18th International Symposium on Communications and Information Technologies (ISCIT 2018), 2018, respectively. Pongsak has contributed to more than 60 patents and is a member of the IEEE and the ACM.
Optimal Depth Recovery using Image Guided TGV with Depth Confidence for High-Quality View Synthesis
P. Lasang, W. Kumwilaisak, Y. Liu and S. M. Shen Journal of Visual Communication and Image Representation, Vol. 39, pp. 24-39. (Available online 12 May 2016).
Multi-sparse Descriptor: A Scale Invariant Feature for Pedestrian Detection
Y. Liu, P. Lasang, M. Siegel and Q. Sun Neurocomputing, Vol. 184, pp. 55-65. (Available online 25 December 2015)
Geodesic Invariant Feature: A Local Descriptor in Depth
Y. Liu, P. Lasang, M. Siegel and Q. Sun IEEE Transactions on Image Processing, vol. 24, no. 1, pp. 236 – 248, January 2015
CFA-based Motion Blur Removal using Long/Short Exposure Pairs
P. Lasang, C. P. Ong, and S. M. Shen IEEE Transaction on Consumer Electronics, vol. 56, no. 2, May 2010, pp. 332-338
Rate Distortion Analysis and Bit Allocation Scheme for Wavelet Lifting-Based Multiview Image Coding
P. Lasang and W. Kumwilaisak EURASIP Journal on Advances in Signal Processing, Volume 2009 (2009), pp. 1-13, January 2009
Rate-Complexity Scalable Multi-view Image Coding with Adaptive Disparity-Compensated Wavelet Lifting
P. Lasang, C.S. Kim, and W. Kumwilaisak Journal of Information and Computing Science, vol. 4, no. 3, August 2009, pp. 211-223
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