Professor at Tsinghua University, China
This researcher has built a stellar academic and professional record that positions them as a leading figure in artificial intelligence and related domains. Their publication portfolio includes highly cited, groundbreaking research in artificial intelligence, computer vision, and natural language processing, with consistent appearances in top-tier conferences and journals such as IEEE TPAMI, CVPR, ICLR, NeurIPS, and EMNLP. Such contributions have advanced both the theoretical foundations and practical applications of AI, significantly shaping how the field evolves. In addition to research productivity, the individual has received prestigious awards and best paper honors, reinforcing their global recognition and scientific impact. Beyond personal achievements, they are also a dedicated mentor, fostering the growth of emerging researchers and cultivating innovation in collaborative projects. This rare combination of academic excellence, innovation, and leadership ensures that their work not only influences current scholarship but also sets the stage for future breakthroughs in intelligent systems.
Professional Profile
Google Scholar | Scopus
Education
Prof. Yujiu Yang built a strong academic foundation through rigorous study and training at two leading Chinese institutions. He earned his B.Sc. degree from the China University of Mining and Technology (CUMT). under the guidance of Prof. Shouhua Dong. His undergraduate training gave him exposure to core principles of computer science, mathematics, and engineering, which later shaped his curiosity toward artificial intelligence. With a passion for advanced research, he pursued a Ph.D. in Artificial Intelligence at the Institute of Automation, Chinese Academy of Sciences (CASIA), completing it in under the supervision of Prof. Baogang Hu. His doctoral work focused on foundational AI techniques, setting the stage for his future contributions in machine learning, visual content analysis, and natural language processing. This strong academic background enabled him to combine theoretical depth with applied innovation, positioning him to emerge as a leading researcher in artificial intelligence.
Experience
Prof. Yujiu Yang is currently a Professor at Tsinghua University, one of China’s most prestigious institutions. Over the course of his career, he has demonstrated expertise in machine learning, computer vision, and natural language processing, contributing to both theoretical advances and practical applications. At Tsinghua, he leads research teams, mentors graduate students, and fosters collaborations between academia and industry. He has served as an advisor in Tencent’s Rhino-Bird Elite Talent Program, guiding young innovators in advancing applied AI projects. His professional journey reflects a balance between research excellence and academic service, with a strong emphasis on leadership, mentorship, and innovation. Through international collaborations, industry projects, and contributions to top AI conferences, Prof. Yang has established himself as a thought leader who bridges the gap between academic research and real-world impact, thereby strengthening China’s role in global AI development.
Skills and Expertise
Prof. Yang possesses a comprehensive set of technical and academic skills that define his role as both a researcher and educator. His expertise lies in deep learning architectures, generative models, adversarial learning, computer vision, and natural language processing, enabling him to contribute across diverse AI subfields. He is adept at designing and optimizing advanced algorithms, developing large-scale models for image and video analysis, and applying AI for content generation and understanding. Beyond technical proficiency, his skills extend to academic leadership, curriculum design, research supervision, and interdisciplinary project management. He is highly experienced in mentoring students and early-career researchers, equipping them with both theoretical knowledge and practical problem-solving capabilities. His ability to integrate AI methodologies into real-world challenges—ranging from visual content creation to interactive systems—demonstrates his versatile skill set. Combined with effective communication, leadership, and collaboration skills, Prof. Yang continues to advance AI research while nurturing future leaders in the field.
Research Focus
Prof. Yang’s research focuses on advancing the fundamental theories and applications of artificial intelligence. His work spans machine learning, natural language processing, and visual content understanding, where he aims to bridge human cognition with intelligent machine behavior. One of his primary goals is to develop systems capable of perceiving, interpreting, and interacting with complex real-world environments, thus moving AI closer to human-like intelligence. His studies in deep learning, video object segmentation, and multimodal understanding have gained international recognition through publications in top-tier journals and conferences. By combining theoretical development with applied innovation, he contributes to both the academic community and industry-driven AI solutions. His long-term vision emphasizes the role of AI in creative content generation, interactive technologies, and robust learning frameworks. Through his research, Prof. Yang continues to shape the field, creating intelligent systems with broad applications in science, education, and technology.
Awards and Honors
Prof. Yang’s achievements have been recognized with numerous national and international honors, underscoring his influence in artificial intelligence. He received the Best Paper Runner-up Award at NeurIPS, one of the most prestigious global AI conferences, as well as the First Prize of the Natural Science Award (Grade 1) from the Xinjiang Uygur Autonomous Region. He was also honored with Tencent’s Outstanding Mentor Award and Excellent Mentor Award for his dedication to student mentorship. His other accolades include the First Prize of the Scientific and Technological Progress Award from Guangdong Province, the Second Prize of the Scientific and Technological Progress Award from Shenzhen City, and the Teaching Achievement Award from Tsinghua University. Additionally, he won the Wu Wenjun AI Science and Technology Award and the Scientific and Technological Progress Award from Guangdong Province. These distinctions highlight his research excellence, teaching impact, and leadership in AI.
Publication
Title: GAN Inversion: A Survey
Authors: W. Xia, Y. Zhang, Y. Yang, J.H. Xue, B. Zhou, M.H. Yang
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(3)
Citations: 739
Title: Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
Authors: T. Liang, Z. He, W. Jiao, X. Wang, Y. Wang, R. Wang, Y. Yang, S. Shi, Z. Tu
Journal: Empirical Methods in Natural Language Processing
Citations: 600
Title: MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
Authors: S. Yang, T. Wu, S. Shi, S. Lao, Y. Gong, M. Cao, J. Wang, Y. Yang
Journal: IEEE/CVF Conference on Computer Vision and Pattern Recognition
Citations: 529
Title: CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Authors: Z. Gou, Z. Shao, Y. Gong, … , Y. Yang
Journal: International Conference on Learning Representations
Citations: 525
Title: Tedigan: Text-Guided Diverse Face Image Generation and Manipulation
Authors: W. Xia, Y. Yang, J.H. Xue, B. Wu
Journal: IEEE/CVF Conference on Computer Vision and Pattern Recognition
Citations: 510
Conclusion
In conclusion, the researcher emerges as an exceptionally strong candidate for the Best Researcher Award, given their remarkable academic and scientific contributions in artificial intelligence, computer vision, and natural language processing. With an impressive publication record in world-leading venues such as IEEE TPAMI, CVPR, ICLR, NeurIPS, and EMNLP, alongside consistently high citation counts, their research clearly demonstrates both impact and global recognition. The individual has not only advanced theoretical foundations but has also provided practical frameworks and tools that shape the future of intelligent systems. Their recognition through prestigious awards, combined with active involvement in mentoring young researchers, further highlights their leadership and influence. Looking ahead, the researcher shows strong potential to expand into interdisciplinary collaborations, industrial applications, and global AI leadership roles, ensuring their work continues to benefit both science and society. Such achievements establish them as a world-class researcher fully deserving of this award.