Zhizhou Ren is a postgraduate researcher specializing in smart agriculture and non-destructive detection of agricultural products. His work focuses on integrating hyperspectral imaging, electronic noses, and deep learning for efficient wheat disease detection. He has published two SCI papers in high-impact journals and developed the GFNN model, achieving 98.76% accuracy in disease identification. Ren has contributed to four major collaborative projects and holds one patent. As a member of the China Electronics Society, he actively engages in research that enhances precision agriculture and food security.

Profile:

• Google Scholar

🔬 Research Focus:

Zhizhou Ren specializes in smart agriculture and non-destructive detection of agricultural products. His research integrates hyperspectral imaging, electronic noses, and deep learning algorithms to detect wheat diseases efficiently.

📚 Key Contributions:

• Developed the GFNN model for detecting VOCs using an electronic nose, achieving 98.76% accuracy in wheat disease detection.
• Published two SCI papers in Q1 and Q2 journals, including Agriculture-Basel and International Journal of Agricultural and Biological Engineering.
• Holds one patent and has contributed to four major collaborative projects funded by Jiangsu Province.

🏆 Achievements & Collaborations:

• Active member of the China Electronics Society.
• Engaged in consultancy and industry projects, contributing to agricultural disease management and food security.
• Participated in prestigious research programs, including the Natural Science Foundation of Jiangsu Province.

Citations:

Citations: 948 (All), 947 (Since 2020)
h-index: 11 (All), 11 (Since 2020)
i10-index: 11 (All), 11 (Since 2020)

Publication Top Notes:

• QPLEX: Duplex Dueling Multi-Agent Q-Learning
  J. Wang, Z. Ren, T. Liu, Y. Yu, C. Zhang
  Ninth International Conference on Learning Representations (ICLR 2021) – 550 citations

• Exploration via Hindsight Goal Generation
  Z. Ren, K. Dong, Y. Zhou, Q. Liu, J. Peng
  Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) – 99 citations

• Towards Understanding Cooperative Multi-Agent Q-Learning with Value Factorization
  J. Wang, Z. Ren, B. Han, J. Ye, C. Zhang
  Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021) – 61 citations

• Proximal Exploration for Model-guided Protein Sequence Design
  Z. Ren, J. Li, F. Ding, Y. Zhou, J. Ma, J. Peng
  Thirty-ninth International Conference on Machine Learning (ICML 2022) – 47 citations

• Generalizable Episodic Memory for Deep Reinforcement Learning
  H. Hu, J. Ye, G. Zhu, Z. Ren, C. Zhang
  Thirty-eighth International Conference on Machine Learning (ICML 2021) – 43 citations

• Off-Policy Reinforcement Learning with Delayed Rewards
  B. Han, Z. Ren, Z. Wu, Y. Zhou, J. Peng
  Thirty-ninth International Conference on Machine Learning (ICML 2022) – 41 citations

• Learning Long-Term Reward Redistribution via Randomized Return Decomposition
  Z. Ren, R. Guo, Y. Zhou, J. Peng
  Tenth International Conference on Learning Representations (ICLR 2022 Spotlight) – 39 citations

• On the Estimation Bias in Double Q-Learning
  Z. Ren, G. Zhu, H. Hu, B. Han, J. Chen, C. Zhang
  Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021) – 24 citations

• Self-Organized Polynomial-Time Coordination Graphs
  Q. Yang, W. Dong, Z. Ren, J. Wang, T. Wang, C. Zhang
  Thirty-ninth International Conference on Machine Learning (ICML 2022) – 13 citations

• Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation
  Z. Ren, A. Liu, Y. Liang, J. Peng, J. Ma
  Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022) – 12 citations

• Object-Oriented Dynamics Learning through Multi-Level Abstraction
  G. Zhu, J. Wang, Z. Ren, Z. Lin, C. Zhang
  Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2020) – 11 citations

• Full-Atom Peptide Design based on Multi-modal Flow Matching
  J. Li, C. Cheng, Z. Wu, R. Guo, S. Luo, Z. Ren, J. Peng, J. Ma
  Forty-first International Conference on Machine Learning (ICML 2024) – 7 citations

• Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework
  R. Guo, R. Wang, R. Wu, Z. Ren, J. Li, S. Luo, Z. Wu, Q. Liu, J. Peng, J. Ma
  Thirty-eighth Conference on Neural Information Processing Systems (NeurIPS 2024) – 1 citation

• Bridging Distribution Gaps: Invariant Pattern Discovery for Dynamic Graph Learning
  Y. Jin, M. Wang, Y. Xiong, Z. Ren, C. Huo, F. Zhu, J. Zhang, G. Wang, H. Chen
  World Wide Web 27 (4), 44 (2024)