Khoa Luu

Carnegie Mellon University, University of Arkansas at Fayetteville

Papers

Total Citations

266

H-Index

About

Dr. Khoa Luu is a leading researcher at the intersection of computer vision and artificial intelligence, with a primary focus on deep reinforcement learning and social group activity recognition. His most impactful work, the comprehensive survey on deep reinforcement learning in computer vision (2021), has garnered over 238 citations, establishing itself as a foundational reference in the field. This survey systematically explores how deep neural networks augment reinforcement learning frameworks, demonstrating remarkable successes across domains including finance, medicine, and video games. More recently, Dr. Luu has pioneered innovative approaches to social group activity recognition with his work on SoGAR (Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition), which addresses critical limitations in current methodologies. His research tackles the practical challenges of extensive manual annotations and reliance on pre-trained detectors, offering more efficient solutions for applications in surveillance, human-robot interaction, and behavioral analysis. Through his contributions, Dr. Luu continues to advance the capabilities of computer vision systems, making them more autonomous and applicable to real-world scenarios. His work represents a significant step toward more intelligent and adaptable visual recognition systems.