Ruochen Li | Artificial Intelligence | Best Researcher Award

Dr. Ruochen Li, BOHUA UHD Co., Ltd. , China.

Ruochen Li, PhD candidate at Macau University of Science and Technology, specializes in Artificial Intelligence with a focus on no-reference video quality assessment, cross-modal audio-visual retrieval, and image-based sound source localization. With expertise in cutting-edge AI technologies like PyTorch, TensorFlow, and MindSpore, Li has achieved groundbreaking research in video quality evaluation and audio-visual content correlation, earning recognition in top-tier journals. He has also received a prize in the National Artificial Intelligence Competition for his contributions to ultra-high-definition video processing.

Publication Profile

Scopus

Education and Experience

PhD in Artificial Intelligence (2021-2024), Macau University of Science and Technology.
Master’s in Control Engineering (2016-2019), Jiangsu University of Science and Technology.
- Supervisor: Associate Prof. Shuxia Ye.
Bachelor’s in Control Engineering (2012-2016), Jiangsu University of Science and Technology.
Research Participant: National Ultra-High Definition Video Innovation Center.
Research Contributor: China Science and Technology Information Research Institute.

Suitability For The Award

Dr. Ruochen Li is an accomplished researcher specializing in artificial intelligence, video quality assessment, and audio-visual event retrieval. With a Ph.D. in Artificial Intelligence from Mauca University of Science and Technology and extensive expertise in PyTorch, TensorFlow, and MindSpore, Li has contributed significantly to advancing multimedia technologies. Their innovations include state-of-the-art datasets, algorithms like Reformer, and multimodal fusion techniques with applications in accessibility, entertainment, and surveillance. Recognized through high-impact publications and awards, including third prize in the National Artificial Intelligence Competition, Ruochen Li exemplifies excellence in research and innovation, making them a strong candidate for prestigious honors such as the Best Researcher Award.

Professional Development

Ruochen Li’s professional journey is defined by innovations in AI and deep learning. He developed the UHD-VQ5k dataset and proposed novel algorithms for ultra-high-definition video quality assessment, utilizing advanced models like Resformer. His work in audio-visual content analysis, featured in his doctoral dissertation, emphasizes the integration of audio-visual features using deep neural networks. As a key participant in national projects, he has contributed to cloud-based UHD video platforms and AI policy analysis. His collaborations and publications underscore his commitment to advancing AI research and applications.

Research Focus

Ruochen Li’s research revolves around Artificial Intelligence applications in multimedia. His expertise spans no-reference video quality assessment, where he develops datasets and benchmarks for UHD video, to cross-modal audio-visual retrieval, enhancing machine understanding of multimodal content. His work also extends to image-based sound source localization, integrating audio-visual data for precise event detection. Through pioneering algorithms, Li bridges gaps between modalities, advancing the interplay of audio and video content in deep learning applications. His contributions drive progress in multimedia AI.

Awards and Honors

Prize Winner: National Artificial Intelligence Competition.
CET-6 Certificate: Scored 490.
CET-4 Certificate: Scored 552.

Publication Top Notes

SgLFT: Semantic-guided Late Fusion Transformer for Video Corpus Moment Retrieval – Neurocomputing, 2024.
Ultrahigh-definition Video Quality Assessment: A New Dataset and Benchmark – Neurocomputing, 2024,
TA2V: Text-Audio Guided Video Generation – IEEE Transactions on Multimedia, 2024,
Cross-Modality Knowledge Calibration Network for Video Corpus Moment Retrieval – IEEE Transactions on Multimedia, 2024,
Maximizing Mutual Information Inside Intra- and Inter-Modality for Audio-Visual Event Retrieval – International Journal of Multimedia Information Retrieval, 2023,

Assoc Prof Dr. Izabela Rojek, Kazimierz Wielki University, Poland

Dr. Izabela Rojek is a prominent academic and researcher serving as the Head of the Department of Data Processing Methods and Tools and the Dean of the Faculty of Computer Science at Kazimierz Wielki University in Bydgoszcz, Poland. She holds the qualifications of Ph.D., D.Sc.Eng., and Associate Professor. Dr. Rojek’s research is centered on engineering sciences, specifically in Technical Informatics, Telecommunications, and Mechanical Engineering. Her extensive scientific output includes five books, 190 articles and chapters in monographs, and over 6000 points in the Ministry of Science and Higher Education (MNiSW) ranking, with a Hirsch index of 18 (Web of Science and Scopus) and 20 (Google Scholar). She has been recognized with 15 national and international awards, including four UKW Rector’s Awards and three foreign medals for outstanding inventions. Dr. Rojek’s contributions extend to 20 grants and innovation projects, and she actively participates in the Manufacturing Engineering Committee of the Polish Academy of Sciences, where she chairs the Manufacturing Digitisation Section.

Suitability for Best Researcher Award:

Izabela Rojek is an exemplary candidate for the Best Researcher Award due to her outstanding contributions to the field of engineering sciences, particularly in Technical Informatics and Telecommunications. Her extensive publication record, high citation metrics, and significant involvement in national and international research projects highlight her impact on the field. Her leadership roles and innovative research further demonstrate her exceptional qualifications for this award.

Work Experience:

Kazimierz Wielki University, Bydgoszcz

Head of the Department of Data Processing Methods and Tools
Dean of the Faculty of Computer Science

Additional Roles and Experience:

Member of the Manufacturing Engineering Committee of the Polish Academy of Sciences

Chair of the Manufacturing Digitisation Section of this Committee

Participation in the implementation of the IFS Applications IT system, including solution design, data migration, and training material preparation

Research and Contributions:

Authored 5 books and over 190 articles and chapters in monographs

Achieved over 6000 points in MNiSW (Polish Ministry of Science and Higher Education) evaluation

Total Impact Factor (IF) above 120

Hirsch index: h=18 (573 citations, Web of Science), h=18 (717 citations, Scopus), h=20 (1097 citations, Google Scholar)

Involved in 20 grants and innovation projects and 10 research topics

Recipient of 15 national and international awards, including 4 UKW Rector’s Awards and 3 foreign medals for outstanding inventions

Publication top Notes: