Chongyuan Wang | Deep learning | Best Researcher Award

Dr. Chongyuan Wang | Deep learning | Best Researcher Award

Dr. Chongyuan Wang, a Ph.D. researcher at Hohai University, specializes in artificial intelligence ๐Ÿค– and neural computation ๐Ÿง . He completed his B.S. at Jiangsu University ๐Ÿ‡จ๐Ÿ‡ณ and M.S. in Energy and Power from Warwick University ๐Ÿ‡ฌ๐Ÿ‡ง. His research journey is centered around biologically inspired learning algorithms, with notable contributions to dendritic neuron modeling and evolutionary optimization. Through innovative algorithms like Reinforced Dynamic-grouping Differential Evolution (RDE), Dr. Wang advances the understanding of synaptic plasticity in AI systems. His patent filings and international publications reflect a strong commitment to academic innovation and impact ๐ŸŒ.

Profile

Education ๐ŸŽ“

๐ŸŽ“ B.S. in Engineering โ€“ Jiangsu University, China ๐Ÿ‡จ๐Ÿ‡ณ
๐ŸŽ“ M.S. in Energy and Power โ€“ University of Warwick, UK ๐Ÿ‡ฌ๐Ÿ‡ง (2018)
๐ŸŽ“ Ph.D. Candidate โ€“ Hohai University, majoring in Artificial Intelligence ๐Ÿค–
Dr. Wang’s educational path bridges engineering and intelligent systems. His strong technical foundation and global exposure foster advanced thinking in machine learning and neuroscience. His current doctoral research integrates deep learning, dendritic neuron models, and biologically plausible architectures for improved learning accuracy and model efficiency. ๐Ÿ“˜๐Ÿง 

Experience ๐Ÿ‘จโ€๐Ÿซ

Dr. Wang is currently pursuing his Ph.D. at Hohai University, where he investigates dendritic learning algorithms and synaptic modeling. ๐Ÿงฌ He proposed the RDE algorithm, enhancing dynamic learning in artificial neurons. His hands-on experience includes research design, algorithm optimization, patent writing, and international publication. He has contributed to projects such as “Toward Next-Generation Biologically Plausible Single Neuron Modeling” and “RADE for Lightweight Dendritic Learning.” ๐Ÿ“Š His work balances theoretical depth and applied research, particularly in neural computation, classification systems, and resource-efficient AI. ๐Ÿ”ฌ๐Ÿ’ก

Awards & Recognitions ๐Ÿ…

๐Ÿ… Patent Holder (CN202410790312.0, CN202410646306.8, CN201510661212.9)
๐Ÿ“„ Published in SCI-indexed journal Mathematics (MDPI)
๐ŸŒ Recognized on ORCID (0009-0002-6844-1446)
๐Ÿง  Nominee for Best Researcher Award 2025
His inventive research has earned him national patents and global visibility. His SCI publications in computational modeling reflect both novelty and academic rigor. His continued innovation in biologically inspired AI learning systems has established his position as an emerging researcher in intelligent systems. ๐Ÿš€๐Ÿ“˜

Research Interests ๐Ÿ”ฌ

Dr. Wangโ€™s research fuses deep learning ๐Ÿค– and dendritic modeling ๐Ÿง  to create biologically plausible AI. He developed the RDE algorithm to mimic synaptic plasticity, improving convergence and adaptability in neural networks. His research areas include evolutionary optimization, adaptive grouping, resource-efficient models, and dendritic learning. He explores how artificial neurons can reflect real-brain behavior, leading to faster, more accurate AI systems. Current projects like RADE aim to make AI lightweight and biologically relevant. ๐ŸŒฑ๐Ÿ“Š His vision is to bridge the gap between neuroscience and AI through interpretable, high-performance algorithms. ๐Ÿง ๐Ÿ’ก

Publications
  • Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model

    Mathematics
    2025-04-29 |ย Journal article
    CONTRIBUTORS:ย Chongyuan Wang;ย Huiyi Liu

Radhika Subramanian | Speech Processing | Women Researcher Award

Dr. Radhika Subramanian | Speech Processing | Women Researcher Award

 

Profile

Education

She is currently pursuing a PhD at Anna University, Chennai, with an expected completion in 2025. She obtained her Master of Engineering in Communication Systems from B.S. Abdur Rahman Crescent Engineering College, Chennai, achieving 82.3% in the academic years 2007-2009. Prior to that, she completed her Bachelor of Engineering in Electronics and Communication Engineering from Kanchi Pallavan Engineering College, Kanchipuram, affiliated with Anna University, securing 84% from 2003 to 2007. She completed her Higher Secondary education at S.S.K.V Higher Secondary School, Kanchipuram, with 88% marks from 2001 to 2003, and her Secondary School Leaving Certificate from the same institution, scoring 84% in the year 2000-2001.

Work experience

As of January 31, 2025, she has a total academic experience of 14 years, 7 months, and 15 days. She has been serving as an Assistant Professor Grade-II at Sri Venkateswara College of Engineering, Sriperumpudur, since June 11, 2010. Prior to this, she worked as a Lecturer at Arulmigu Meenakshi Amman College of Engineering, Kanchipuram, from July 1, 2009, to May 7, 2010, gaining 10 months of experience. Her cumulative teaching experience amounts to 14 years, 17 months, and 15 days.

AREA OF INTEREST

  • Data Communication and Networking
  • Satellite communication
  • Signal Processing
  • Machine Learning

Publication

  • Radhika, S & Prasanth, A 2024, โ€žAn Effective Speech Emotion Recognition Model for Multi-Regional Languages Using Threshold-based Feature Selection Algorithmโ€Ÿ, Circuits, Systems, and Signal Processing, vol. 43, pp. 2477โ€“2506, ISSN: 1531-5878,DOI: 10.1007/s00034-023-02571-4, Impact Factor: 2.3.
  • Radhika, S & Prasanth, A 2024, โ€žAn Effective Speech Emotion Recognition Model for Multi-Regional Languages Using Threshold-based Feature Selection Algorithmโ€Ÿ, Circuits, Systems, and Signal Processing, vol. 43, pp. 2477โ€“2506, ISSN: 1531-5878,DOI: 10.1007/s00034-023-02571-4, Impact Factor: 2.3.
  • A Survey of Human Emotion Recognition Using Speech Signals: Current Trends and Future Perspectives
    R Subramanian, P Aruchamy
    Micro-Electronics and Telecommunication Engineering: Proceedings of 6th