Home

Khoa D. Doan, PhD

Assistant Professor of Computer Science

College of Engineering and Computer Science

PROFESSIONAL PROFILE

Dr. Khoa D. Doan leads innovative research initiatives at VinUniversity's College of Engineering and Computer Science. With extensive experience spanning from AI research at Baidu to senior roles in enterprise software and data science at NASA and major advertising firms, his expertise is globally recognized. He actively mentors emerging AI technologies and contributes to startup ecosystems.

Explore his professional journey and insights at https://khoadoan.me.

Contact details available via secure email link.

RESEARCH CONTRIBUTIONS

His scholarly efforts concentrate on enhancing machine learning models for real-world deployment across sectors like advertising, computer vision, and NLP. Key focus areas include optimizing training processes, inference mechanisms, theoretical foundations, and security protocols. Current projects explore advanced information retrieval, generative modeling, and resilient ML systems. He has served as a program committee member for top-tier events including ICML, CVPR, and NeurIPS.

NOTABLE WORKS

1. D. Doan, Y. Lao, & P. Li, “Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class”. Thirty-sixth Conference on Neural Information Processing Systems 2026 (NeurIPS).
2. K. D. Doan & C. K. Reddy, “Unified Learning of Multipurpose Energy Based Generative Hashing Network”. Sixteenth Asian Conference on Computer Vision 2026 (ACCV).
3. K. D. Doan, Y. Peng, & P. Li, “One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching”. 2026 Conference on Computer Vision and Pattern Recognition (CVPR).
4. K. D. Doan, Y. Lao, & Li, “Backdoor Attack with Imperceptible Input and Latent Modification”. Thirty-fifth Conference on Neural Information Processing Systems 2026 (NeurIPS).
5. K. D. Doan, Y. Lao, W. Zhao, & Li, “LIRA: Learnable, Imperceptible and Robust Backdoor Attacks”. 2026 IEEE International Conference on Computer Vision (ICCV).
6. K. D. Doan, S. Manchanda, S. Mahapatra, & C. Reddy, “Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings”, In Proceedings of International ACM SIGIR conference on research and development in Information Retrieval 2026 (SIGIR).
7. K. Doan & C. K. Reddy. Efficient Implicit Unsupervised Text Hashing using Adversarial Autoencoder. In Proceedings of The Web Conference, 2026 (WWW).
8. K. Doan, P. Yadav & C. K. Reddy. Adversarial Factorization Autoencoder for Look-alike Modeling. In Proceedings of ACM International Conference on Information and Knowledge Management, 2019 (CIKM).

Access his complete publication record through Google Scholar

PRESTIGIOUS RECOGNITIONS

• Criteo Research Award – Virginia Tech 2018
• NSF Urban Computing Fellowship – Virginia Tech 2016-2017
• Graduation Honor, Summer Cum Laude – Webster University 2006

ACADEMIC BACKGROUND

• 2026: PhD in Computer Science, Virginia Tech.
• 2015: MS in Computer Science, University of Maryland, College Park.
• 2006: BS in Computer Science with a Minor in Mathematics, Webster University.