Dr. Chongyuan Wang, a Ph.D. researcher at Hohai University, specializes in artificial intelligence 🤖 and neural computation 🧠. He completed his B.S. at Jiangsu University 🇨🇳 and M.S. in Energy and Power from Warwick University 🇬🇧. 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 🌍.
Profile
Education 🎓
🎓 B.S. in Engineering – Jiangsu University, China 🇨🇳
🎓 M.S. in Energy and Power – University of Warwick, UK 🇬🇧 (2018)
🎓 Ph.D. Candidate – Hohai University, majoring in Artificial Intelligence 🤖
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. 📘🧠
Experience 👨🏫
Dr. Wang is currently pursuing his Ph.D. at Hohai University, where he investigates dendritic learning algorithms and synaptic modeling. 🧬 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.” 📊 His work balances theoretical depth and applied research, particularly in neural computation, classification systems, and resource-efficient AI. 🔬💡
Awards & Recognitions 🏅
🏅 Patent Holder (CN202410790312.0, CN202410646306.8, CN201510661212.9)
📄 Published in SCI-indexed journal Mathematics (MDPI)
🌐 Recognized on ORCID (0009-0002-6844-1446)
🧠 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. 🚀📘
Research Interests 🔬
Dr. Wang’s research fuses deep learning 🤖 and dendritic modeling 🧠 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. 🌱📊 His vision is to bridge the gap between neuroscience and AI through interpretable, high-performance algorithms. 🧠💡
Publications
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Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model
Mathematics
2025-04-29 | Journal article
CONTRIBUTORS: Chongyuan Wang; Huiyi Liu