Dr. Jun-Liu-Action Recognition-Best Researcher Award
Singapore University of Technology and Design-Singapore
Early Academic Pursuits
Dr. Jun Liu's academic journey began with a Bachelor of Engineering in Software Engineering from Central South University, China, followed by a Master of Science in Computer Science from Fudan University, China. His passion for research led him to pursue a Ph.D. in the School of Electrical and Electronic Engineering at Nanyang Technological University (NTU), Singapore, which he completed in 2019. During his early academic pursuits, Liu demonstrated a keen interest in artificial intelligence (AI), machine learning (ML), and computer vision, laying the foundation for his future contributions to these fields.
Professional Endeavors
Dr. Jun Liu's professional career spans both academia and industry, reflecting his multidisciplinary expertise. He commenced his academic journey as an Assistant Professor at the Singapore University of Technology and Design (SUTD) in 2019, where he actively engaged in teaching and research activities. His role expanded beyond SUTD as he assumed adjunct positions at prestigious institutions such as the University of Western Australia and Nanyang Technological University, solidifying his presence in the academic community across different continents.
Prior to his academic appointments, Liu gained valuable industry experience as a Software Engineer at Tencent Inc., China, where he honed his skills in software development. This industry exposure equipped him with practical insights that he seamlessly integrates into his academic endeavors, bridging the gap between theory and application.
Contributions and Research Focus
Dr. Jun Liu's research interests encompass AI, computer vision, and ML, with a focus on solving real-world challenges through innovative approaches. His notable contributions include advancements in egocentric vision-based activity analysis, 3D human digitization, and fine-grained event analysis in videos. By securing substantial grants from prestigious funding bodies like the Ministry of Education (MOE) and the National Research Foundation (NRF), Liu has demonstrated his ability to spearhead impactful research initiatives addressing critical societal needs.
Dr. Jun Liu's research output is not limited to theoretical advancements but also extends to practical applications with tangible benefits. His collaborations with industry partners, including AI Singapore, animalEYEQ, and Tencent, underscore his commitment to translating research findings into actionable solutions that drive technological innovation and societal progress.
Accolades and Recognition
Dr. Jun Liu's contributions to the field have been widely recognized through numerous accolades and awards. Notable among these are the Best Student Paper Awards from the Pattern Recognition and Machine Intelligence Association and the prestigious recognition as one of the top 2% scientists worldwide by Stanford University. These accolades not only affirm Liu's scholarly excellence but also serve as a testament to the impact of his research on the global academic community.
Impact and Influence
Dr. Jun Liu's research has left a profound impact on various domains, ranging from healthcare and education to computer vision and AI. His work in intelligent human behavior understanding, robust behavior analysis, and age-related disease risk assessment reflects a deep understanding of societal needs and a commitment to leveraging technology for social good. Through his mentorship of graduate students and researchers, Liu is cultivating the next generation of scholars and innovators who will continue to push the boundaries of AI and ML.
Legacy and Future Contributions
As Dr. Jun Liu's continues to advance his research agenda and mentor future leaders in the field, his legacy as a visionary researcher and educator is sure to endure. His relentless pursuit of excellence, coupled with his interdisciplinary approach to problem-solving, positions him as a driving force in shaping the future of AI, computer vision, and machine learning. With a steadfast commitment to innovation and societal impact, Liu's future contributions hold the promise of transformative change, further solidifying his status as a trailblazer in the field of computational sciences.
Citations
- Citations 12464
- h-index 42
- i10-index 80
Notable Publication
- Modifying the one-hot encoding technique can enhance the adversarial robustness of the visual model for symbol recognition
- Correlation Matching Transformation Transformers for UHD Image Restoration
- Cross-domain transfer learning algorithm for few-shot ship recognition in remote-sensing image
- UDT: U-shaped deformable transformer for subarachnoid haemorrhage image segmentation
- Trusted semi-supervised multi-view classification with contrastive learning