Jing Liu - Image and Video Processing - Best Researcher Award

Tianjin University - China

AUTHOR PROFILE

GOOGLE SCHOLAR

Based on the provided information about Jing Liu, he appears to be a strong candidate for the Research for Community Impact Award for several reasons:

ACADEMIC ACHIEVEMENTS

Jing Liu has an impressive academic track record, including notable awards such as the Best Poster Award at the 20th International Forum of Digital Multimedia Communication in 2023, the Special Award of the Tianjin Science and Technology Progress Award in 2021, and the Prize Paper Award Runner-up of IEEE Transactions on Multimedia in 2021. These accolades highlight his significant contributions to the fields of information and communication engineering, particularly in multimedia and image processing.

EDUCATIONAL BACKGROUND

Jing Liu holds a Ph.D. in Information and Communication Engineering from Shanghai Jiao Tong University, one of China's top universities. His education was further enriched by his time as a visiting scholar at the Department of Computer Science and Engineering at SUNY Buffalo. This diverse educational background under the guidance of prominent advisors like Xiaokang Yang, Guangtao Zhai, and Chang Wen Chen has provided him with a solid foundation in his field.

PROFESSIONAL SERVICE AND LEADERSHIP

Jing Liu has demonstrated leadership and dedication to his field through various roles in academic service. He has served as an Associate Editor for Elsevier’s "Displays" journal since 2021 and as a Guest Editor for a Special Issue in Image and Vision Computing in 2024. His role as Chair of the 3rd Excellent Doctoral Forum of the China Society of Image and Graphics in 2023 and his involvement in organizing and chairing numerous workshops and conferences underscore his commitment to advancing research and fostering academic communities.

RESEARCH AND INNOVATION

Jing Liu's research focuses on cutting-edge topics in image and video processing, including facial micro-expression recognition, video salient object detection, and image bit-depth enhancement using neural networks. His publications, such as "Key Facial Components Guided Micro-Expression Recognition Based on First & Second-Order Motion" and "DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection," demonstrate his innovative approach to solving complex problems in digital multimedia communication and image processing.

COMMUNITY IMPACT

Jing Liu’s work has significant implications for the broader community, particularly in enhancing digital communication and imaging technologies. His research in micro-expression recognition can be applied in areas such as security, psychology, and human-computer interaction, potentially improving mental health assessments and surveillance systems. His contributions to video salient object detection and image enhancement also have practical applications in various industries, including entertainment, healthcare, and scientific research, thereby benefiting society at large.

RECOGNITION AND PEER REVIEW

Jing Liu is recognized as an advanced member of the China Computer Federation and has received numerous awards for his work. His role as a reviewer for prestigious journals like IEEE TPAMI, TNNLS, TIP, TMM, and TCSVT, as well as his involvement in program committees for top conferences, speaks to his expertise and the high regard in which he is held by his peers.

CONCLUSION

Jing Liu's extensive academic achievements, innovative research, professional service, and the broader impact of his work make him a highly suitable candidate for the Research for Community Impact Award. His contributions have not only advanced academic knowledge but also provided practical benefits to the community, aligning perfectly with the award's criteria.

NOTABLE PUBLICATION

Spatio-temporal mitosis detection in time-lapse phase-contrast microscopy image sequences: A benchmark 2021 (21)

Key Facial Components Guided Micro-Expression Recognition Based on First & Second-Order Motion 2021 (21)

BE-CALF: bit-depth enhancement by concatenating all level features of DNN 2019 (28)

DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection 2020 (20)

Recurrent conditional generative adversarial network for image deblurring 2018 (27)

EARLY ACADEMIC PURSUITS:

Khaled Mohamed Khedher pursued a robust academic journey, culminating in a Doctor of Philosophy in Civil and Mining Engineering from the University of Lorraine (INPL), France, in July 1996. His dissertation focused on the "Modeling of complex underground quarries in France." Prior to this, he obtained a Master of Science in Civil and Mining Engineering from the High School of Mining, University of Lorraine, and a Bachelor of Science in Mining Engineering from the University of Sfax, Tunisia.

PROFESSIONAL ENDEAVORS:

Khedher's professional experience spans various roles in geotechnical engineering, remote sensing, GIS, and civil and mining engineering. Noteworthy positions include his tenure as Head of Geotechnical Department at Tameer Co. Engineering Consultant, his role as a Remote Sensing, GIS, and Geotechnical Engineer Expert at consulting companies in Saudi Arabia, and his experience as a Civil and Mining Engineer Expert at consulting firms in Tunisia.

CONTRIBUTIONS AND RESEARCH FOCUS:

Khedher's research interests primarily revolve around the application of REMOTE SENSING and GIS in diverse disciplines such as water resources, geology, geotechnical engineering, and mining. His expertise includes Finite Element Modeling and Distinct Element Modeling in Civil and Mining Engineering. Additionally, he has contributed significantly to ecological engineering and the design of modern building materials, particularly in Saudi Arabia.

IMPACT AND INFLUENCE:

With a plethora of publications in prestigious ISI journals and numerous presentations at national and international conferences, Khedher's work has had a substantial impact on the fields of civil and mining engineering. His research on groundwater management, flood risk assessment, and urban planning using REMOTE SENSING and GIS technologies has provided valuable insights and practical solutions to pressing environmental challenges.

ACADEMIC CITES:

Khedher's contributions have been widely recognized and cited in the academic community. His research papers have appeared in esteemed journals, demonstrating the relevance and significance of his work in advancing scientific knowledge and informing practical applications in engineering and environmental management.

LEGACY AND FUTURE CONTRIBUTIONS:

Khedher's legacy lies in his multifaceted contributions to academia, industry, and research. His expertise in REMOTE SENSING, GIS, and geotechnical engineering has paved the way for innovative solutions to complex engineering problems. As he continues to delve into new research endeavors and mentor the next generation of engineers and scientists, his impact on the field is poised to endure and expand further.

Remote Sensing

Remote sensing serves as a cornerstone of Kheder's research endeavors, enabling him to analyze environmental phenomena, monitor land use changes, and assess natural resources. Through the application of remote sensing techniques, he has enhanced understanding and decision-making in diverse fields, ranging from geotechnical engineering to ecological management.