I am a PhD student in Electrical Engineering at KAIST, advised by Professor Chang Dong Yoo. My research focuses on reinforcement learning (RL), generative modeling, and robotics. I aim to develop principled learning algorithms that enhance the decision-making accuracy, controllability, and robustness of autonomous agents.
My recent work centers on diffusion and flow-matching models for policy learning. Broadly, I seek to integrate generative models with robot learning to enable agents to understand complex environments and interact with them safely, reliably, and adaptively.
📌 Research Interests
- Reinforcement Learning
- Deep Generative Modeling
- Robotic Control Algorithms
🏫 Educations
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2020 - Present: PhD in Electrical Engineering (KAIST, Korea) GPA: 3.79/4.3
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2018 - 2020: MS in Electrical Engineering (KAIST, Korea) GPA: 3.66/4.3
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2010 - 2015: BE in Electrical Engineering (HCMUT, Vietnam) GPA: 8.34/10
🔥 News
- 2026.01: 🎉🎉 One paper accepted to ICLR 2026
- 2024.06: 🎉🎉 One paper accepted to IROS 2024
- 2024.02: 🎉🎉 One paper accepted to IEEE Access 2024
📝 Publications
Thanh Nguyen , Chang D. Yoo.
The International Conference on Learning Representations (ICLR), 2026
[J4] Uncertainty-Aware Rank-One MIMO Q Network Framework for Accelerated Offline Reinforcement Learning
Thanh Nguyen , Tung M. Luu, Tri Ton, Sungwoong Kim, Chang D. Yoo
IEEE Access, 2024
[C10] Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization
Tung M. Luu, Thanh Nguyen , Tee Joshua Tian Jin, Sungwoong Kim, Chang D. Yoo.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
[C9] Scalable SoftGroup for 3D Instance Segmentation on Point Clouds
Thang Vu, Kookhoi Kim, Thanh Nguyen , Tung M. Luu, Junyeong Kim, Chang D. Yoo
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
[J3] DimCL: Dimensional Contrastive Learning for Improving Self-Supervised Learning
Thanh Nguyen*, Trung X. Pham*, Chaoning Zhang, Tung M. Luu, Thang Vu, Chang D. Yoo
IEEE Access, 2023
[J2] Lad: A hybrid deep learning system for benign paroxysmal positional vertigo disorders diagnostic
Trung X. Pham, Jin Woong Choi, Rusty John Lloyd Mina, Thanh Nguyen, Sultan Rizky Madjid, Chang D Yoo
IEEE Access, 2022
[C8] SoftGroup for 3D Instance Segmentation on Point Clouds
Thang Vu, Kookhoi Kim, Tung M. Luu, Thanh Nguyen , Chang D. Yoo
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
[C7] Visual Pretraining via Contrastive Predictive Model for Pixel-Based Reinforcement Learning
Tung M. Luu, Thang Vu, Thanh Nguyen , Chang D. Yoo
MDPI Sensors, 2022
[J1] Utilizing Skipped Frames in Action Repeats for Improving Sample Efficiency in Reinforcement Learning
Tung M. Luu, Thanh Nguyen , Thang Vu, Chang D. Yoo
IEEE Access, 2022
Thanh Nguyen , Tung M. Luu, Trung X. Pham, Sanzhar Rakhimkul, Chang D. Yoo
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Thanh Nguyen*, Tung M. Luu*, Thang Vu, Chang D. Yoo
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
[C4] SphereRPN: Learning Spheres for High-Quality Region Proposals on 3D Point Clouds Object Detection
Thang Vu, Kookhoi Kim, Haeyong Kang, Thanh Nguyen, Tung M. Luu, Chang D. Yoo
IEEE International Conference on Image Processing (ICIP), 2021
Thanh Nguyen, Tung M. Luu, Thang Vu, Chang D. Yoo
The Institute of Electronics and Information Engineers Conference (Theieie), 2021
[C2] A survey on meta-learning
Thanh Nguyen, Chang D. Yoo
The Korean Artificial Intelligence Society 2020 Summer and Autumn Conference (KAIA), 2020
[C1] GDCA: GAN-based single image super resolution with Dual discriminators and Channel Attention
Thanh Nguyen, Hieu Hoang, Chang D. Yoo
The Korean Artificial Intelligence Society 2019 Summer and Autumn Conference (KAIA), 2019
🎏 Patent
- Computing apparatus and method for implementing end-to-end deep learning framework for sample-efficient image-based reinforcement learning, KR-10-2022-0173811 (2022.12.13)
🎖 Honors and Awards
- 2010 - 2015 HCMUT Excellent Student Scholarship for five consecutive years.
- 2018 - 2026 Full Kaist Scholarship for Master-PhD program.
💬 Academic Service
Teaching assistant
- 2024 Fall EE331: Introduction to Machine Learning
- 2021 Fall EE531: Statistical Learning Theory
- 2020 Spring EE331: Introduction to Machine Learning
Lab Leader
- 2/2022-2/2024 UAIM Laboratory Leader
Others
- 2024 - 2025 Member of the Korea Information Science Society
- 2022 - Now Member of the Institute of Electrical and Electronics Engineers (IEEE)
- 2020 - Now Reviewer of ICLR, ICML, AAAI, IROS, ICASSP …