Zheyi Chen | Best Researcher Award - Biography

Prof Dr Zheyi Chen : Machine Learning Applications

Early Academic Pursuits:

Prof Dr. Zheyi Chen embarked on his academic journey with a Bachelor's degree in Computer Science and Technology from Shanxi University, China, where he laid the foundation for his future endeavors. He continued his education with a Master's degree in Computer Science and Technology from Tsinghua University, China, under the guidance of Prof. Yongwei Wu.

For his doctoral studies, Prof. Chen pursued a Ph.D. in Computer Science at the University of Exeter, U.K., from September 2017 to October 2021. During this period, he worked under the supervision of Prof. Geyong Min and Dr. Jia Hu, contributing to the field of computer science and further honing his research skills.

Professional Endeavors:

Following his academic pursuits, Prof Dr. Zheyi Chen transitioned into the role of an Associate Professor and Ph.D. Supervisor at the College of Computer and Data Science, Fuzhou University, China, from December 2021 to January 2023. Subsequently, he assumed the position of a Professor and Ph.D. Supervisor in the same department from February 2023 onwards, signifying a progression in his academic career.

Contributions and Research Focus:

Prof Dr. Chen's research interests encompass Cloud/Edge Computing, Resource Optimization, Deep Learning, and Deep Reinforcement Learning. His notable contributions include leading research projects such as "Research on Efficient and Adaptive Resource Optimization in Cloud-Edge Environments" and "Research and Application of Key Technologies for Resource Optimization and Data Processing in Cloud-Edge Collaborative Environment."

He has significantly advanced the understanding of resource allocation in mobile edge computing and the development of key technologies for big data intelligence. His expertise extends to the exploration and practice of training postgraduate students aligned with the "Digital Fujian" strategy.

Accolades and Recognition:

Prof Dr. Zheyi Chen's contributions to the field have been acknowledged through prestigious awards, including the "World’s Top 2% Scientists" in 2023, the "First Prize of Fujian Science and Technology Progress" in 2021, and multiple "First Prizes for Outstanding Papers" at the Annual Academic Conference of Fujian Computer Society in 2021 and 2023.

Impact and Influence:

As an active member of IEEE, ACM, and CCF, Prof. Chen has played a pivotal role in the academic community. His involvement in conference organization, as seen in his roles as Web and System Management Chair for IEEE SustainCom-2020 and IEEE SmartCity-2018, highlights his commitment to fostering scholarly exchange.

He has also served as a reviewer for reputable journals and conferences, including IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, and IEEE/CAA Journal of Automatica Sinica, contributing to the rigorous evaluation and dissemination of research in his field.

Legacy and Future Contributions:

Prof Dr. Zheyi Chen's legacy is marked by his leadership in influential research projects, academic recognition, and service to the community. His commitment to advancing knowledge in Cloud/Edge Computing and related fields positions him as a key figure in shaping the future of computer science. As he continues to lead research projects, mentor students, and contribute to scholarly activities, Prof. Chen is poised to leave a lasting impact on the field and inspire future generations of researchers.

Notable Publications:

Citations:

A total of  921 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

 Zhi Liu | Best Researcher Award  Winner 2023  🏆

Dr Zhi Liu : Machine Learning Applications

🏆 Congratulations to Dr. Zhi Liu!

 International Research Data Analysis Excellence Awards Best Researcher Award Winner Recognizing Dr. Liu's outstanding contributions in Machine Learning Applications. Your dedication to research excellence has set a benchmark for the global scientific community. Well-deserved honor!

Early Academic Pursuits

Liu Z started his academic journey with a focus on computer software and theory at Northeast Normal University, where he pursued a master's degree in Computer Software and Theory from September 2014 to January 2017. During this period, his research interests included recommendation systems, artificial intelligence, machine learning, and natural language processing.

Professional Endeavors

Subsequently, he advanced his academic pursuits by obtaining a Ph.D. in Mechanical Manufacturing and Automation from the University of the Chinese Academy of Sciences (2017-2022). His doctoral research concentrated on artificial intelligence, machine teaching, knowledge graphs, natural language processing (NLP), natural language understanding (NLU), machine reading comprehension (MRC), and knowledge modeling.

Research Focus

The core of Liu Z's doctoral research was the development of machine teaching methods for human-machine collaboration. His dissertation focused on leveraging natural language processing (NLP) techniques in the medical domain to explore how AI models could be taught through interactive human-machine methods. The goal was to enhance learning efficiency by incorporating existing knowledge systems and incorporating correction mechanisms into the learning process.

Contributions and Research Output

Liu Z has made significant contributions to the field, as evidenced by his research outcomes and publications. Notably, he co-authored a paper titled "AttentiveHerb: A Novel Method for Traditional Medicine Prescription Generation" and secured a patent for a method analyzing symptom-drug relationships using new artificial intelligence technology.

His work extended to Chinese traditional medicine, with a paper on "TCMNER and PubMed: A Novel Chinese Character-Level-Based Model and a Dataset for TCM Named Entity Recognition." In addition, Liu Z contributed to the field of event extraction with a paper on structural dependency self-attention-based hierarchical event models.

Recognition and Impact

Liu Z's contributions have not gone unnoticed, as he received funding from the 71st batch of the China Postdoctoral Science Foundation. His work in the medical domain, specifically on the generation of traditional herbal medicine prescriptions, was acknowledged in a transfer learning model published in the journal "Artificial Intelligence in Medicine."

Future Contributions and Legacy

Transitioning to a postdoctoral role at Zhejiang Lab, Liu Z continued his research in natural language processing, understanding, and knowledge graphs. His accomplishments include the development of large models tailored to specific vertical domains, such as finance and traditional Chinese medicine. His work in numerical reasoning and a transfer learning-based dual-augmentation strategy for rare disease syndrome differentiation in traditional Chinese medicine showcases his commitment to advancing the field.

Liu Z's legacy extends beyond academic achievements, with patents, conference papers, and impactful research contributing to the broader landscape of artificial intelligence, natural language processing, and medical applications. His efforts are likely to leave a lasting mark on the integration of AI into medical practices and knowledge systems.

Notable publication :