Kok-Seng Wong, PhD
College of Engineering and Computer Science
Associate Professor, Computer Science program
Email:
wong.ks@vinuni.edu.vn
Biography
Dr. Kok-Seng Wong is an Associate Professor at the College of Engineering and Computer Science (CECS), VinUniversity. He earned his Bachelor’s degree in Computer Science (Software Engineering) from the University of Malaya, Malaysia, followed by an M.Sc. in Information Technology from the Malaysia University of Science and Technology (in collaboration with MIT). He completed his Ph.D. at Soongsil University, South Korea.
He has over 20 years of teaching experience in Computer Science across universities in Malaysia, South Korea, Kazakhstan, and Vietnam. Dr. Wong’s research interests encompass information security, data privacy, and trustworthy AI. His current focus is on Federated Learning (FL), particularly addressing critical issues such as data privacy protection, backdoor attacks, and communication efficiency. He has published high-quality research papers on FL topics in top-tier conferences and journals, including CVPR, ECCV, ICLR, NeurIPS, ACL, WWW, IEEE TETC, IEEE TNSM, etc.
- Information Security
- Data Privacy Protection
- Trustworthy AI
- Backdoor Attacks and Defenses
- Federated Learning
- Introduction to Programming
- Object-Oriented Programming
- Algorithms Design
- Computational and Algorithmic Thinking
- Quang H. Nguyen, Nguyen Ngoc-Hieu, The-Anh Ta, Thanh Nguyen-Tang, Kok-Seng Wong, Hoang Thanh-Tung, Khoa D. Doan, “Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks,” the 13th International Conference on Learning Representations (ICLR’25), 2025.
- Toan D. Gian, Tien Dac Lai, Thien Van Luong, Kok-Seng Wong, and Van-Dinh Nguyen. HPE-Li: WiFi-enabled Lightweight Dual Selective Kernel Convolution for Human Pose Estimation. European Conference on Computer Vision (ECCV 2024), Milan, Italy.
- Le Huy Khiem, Long Tuan Ho, Cuong Do, Danh Le-Phuoc, and Kok-Seng Wong, “Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization,” the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR’24), Seattle, 2024, pp. 6027-6036.
- Duy Hoang, Nguyen Hung-Quang, Saurav Manchanda, Minlong Peng, Kok-Seng Wong, and Khoa Doan. Fooling the textual fooler via randomizing latent representations. In Lun-Wei Ku, Andre Martins, and Vivek Srikumar, editors, Findings of the Association for Computational Linguistics (ACL 2024), pages 14403–14421, Bangkok, Thailand.
- Tran Van Tuan, Pham Huy Hieu, and Kok-Seng Wong, “Personalized privacy-preserving framework for cross-silo federated learning,” IEEE Transactions on Emerging Topics in Computing (ISSN: 2168-6750), 2024.
- Thuy Dung Nguyen, Tuan Nguyen, Phi Le Nguyen, Hieu H. Pham, Khoa D. Doan, and Kok-Seng Wong, “Backdoor Attacks and Defences in Federated Learning: Survey, Challenges and Future Research Directions,” Engineering Applications of Artificial Intelligence (ISSN: 1873-6769), Vol. 127, Part A, 2024. 01.
- Nguyen, N. H., Nguyen, T. A., Nguyen, T., Hoang, V. T., Le, D. D., & Wong, K. S, “Towards Efficient Communication Federated Recommendation System via Low-rank Training,” the ACM Web Conference (TheWebConf’24), Singapore, 2024, pp.3940-3951.
- Quang H. Nguyen, Yingjie Lao, Tung Pham, Kok-Seng Wong, and Khoa D. Doan, “Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks,” the 12th International Conference on Learning Representations (ICLR’24), 2024.
- Nguyen Anh Tu, Assanali Abu, Nartay Aikyn, Nursultan Makhanov, Min-Ho Lee, Khiem Le-Huy, and Kok-Seng Wong, “FedFSLAR: A Federated Learning Framework for Few-Shot Action Recognition,” Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 2024, pp. 270-279.
- Thuy Dung Nguyen, Tuan Nguyen, Anh Tran, Khoa D. Doan, and Kok-Seng Wong, “IBA: Towards Irreversible Backdoor Attacks in Federated Learning,” the 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, USA.
- Quan Nguyen, Hieu H Pham, Kok-Seng Wong, Phi Le Nguyen, Truong Thao Nguyen, Minh N Do, “FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Co-Training”, IEEE Transactions on Network and Service Management (ISSN: 1932-4537), 2023. 9.
Selected Awards
- Year 2022 Faculty of the Year Award, VinUniversity.
- Year 2021 Teaching Excellent Awards, VinUniversity.
- Visiting scholar at State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications (2015, 2016, and 2018).
- Best Portfolio (CQI) Award, Soongsil University (2014 and 2016).
- Visiting professor at CRISES Research Group at the University of Rovira i Virgil (2012).
- Best Teaching Award, Soongsil University (2009).
- Letter of Merit (Teaching Evaluation), Multimedia University (2004 – 2008).
Selected Funded Projects
- Green Serverless Computing for Resource-Efficient AI Training, Role: PI, Center for Environment Intelligence, 2024, VinUniversity, Hanoi, Vietnam.
- Farm2Vet: Combatting AMR on the Farm Frontier, Role: Co-PI, The Trinity Challenge on Antimicrobial Resistance, Grand Prize Winner, 2024. Budget: £1M for a solution to reduce the impact of antimicrobial resistance and bacterial infections in low- and middle-income communities.
- Improving NLP Applications in Low-resource Languages: One Country and One Use Case At A Time, Role: Co-PI, A Cross-College Project, 2024, VinUniversity, Hanoi, Vietnam.
- Privacy-Preserving, Robust, and Explainable Federated Learning Framework, Role: PI, VinUni-Illinois Smart Health Center, 2022. Budget: $1M for funding co-advised VinUniversity and UIUC PhD Students.
