Thanh-Dat Truong Selected for CVPR 2024 Doctoral Consortium

Thanh-Dat Truong, a Ph.D. candidate in the Department of Electrical Engineering and Computer Science, will participate in the Computer Vision and Pattern Recognition Conference Doctoral Consortium. The conference takes place on June 17 in Seattle, Washington, and is one of the top publishing AI conferences.

The Computer Vision and Pattern Recognition Conference is very selective in choosing participants for the conference. In general, the conference accepts less than 30% of papers submitted, and less than 5% of those are accepted for oral presentations. The conference uses a multi-tier double-blind peer review process to select papers and participants. 

Khoa Luu said, "Thanh-Dat Truong is an outstanding student in my research lab. His research topics focus on video scene understanding, unsupervised domain adaptation, continual learning and robust vision learning. During his Ph.D. program, he has contributed to the Computer Vision Research Society with five published CVPR/ICCV papers (four as the first author and one as the co-first author) and one published NeurIPS paper (the first author). He has been a CVPR reviewer since 2022 and an IEEE TPAMI reviewer since 2020. He also received the NeurIPS Travel Award 2023." 

"It is an honor to participate in the CVPR 2024 Doctoral Consortium. It affirms the recognition and value of my Ph.D. research," Truong said. "It gives me motivation for my research and future academic career. In addition, through this event, I have the opportunity to engage and discuss with senior researchers and experts in my field. This enables discussions on my ongoing research and career plans." 

Truong said, "The CVPR 2024 Doctoral Consortium selected me for my Ph.D. dissertation, titled 'Towards Robust and Fair Vision Learning in Open-World Environments.' Today, AI and deep learning have adopted various visual applications. However, these could produce biased predictions due to an imbalance in training of the data. My Ph.D. dissertation aims to develop vision learning toward two goals: fairness with continual learning and robust representation learning. By being selected, I will have an opportunity to present my research to experts in the field at the CVPR conference." 

Truong will graduate within the next six months. Participating in the Doctoral Consortium in CVPR 2024 will benefit his academic and professional development. This will allow him to secure his future job in computer vision and computer science. In addition, the CVPR 2024 Doctoral Consortium will fund Truong's trip to Seattle to attend CVPR, including conference registration, hotel accommodations, meals and airfare.