Guofeng Cui

Guofeng Cui

PhD student CS@Rutgers

About me

  • I am a fifth-year PhD student in Computer Science department at Rutgers University, advised by Prof. He Zhu. My research interests involve reinforcement learning, computer vision, programming language and machine learning. I investigate to increase efficiency of neural program synthesis and apply programs of neural module to enhance robustness and interpretability of reinforcement learning policy. I also investigate to apply reinforcement learning methods for performance enhancing of deep learning models, including large language model finetuning, active learning, etc..

  • I obtained my Master’s degree from University of Rochester CS, advised by Prof. Chenliang Xu.

Publication

  • Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning [pdf]; ; Yuanlin Duan, Guofeng Cui, He Zhu; Neural Information Processing Systems 2021 (NeurIPS 2024)

  • Reward-Guided Synthesis of Intelligent Agents with Control Structures [pdf]; Guofeng Cui, Yuning Wang, Wenjie Qiu, He Zhu; ACM SIGPLAN Conference on Programming Language Design and Implementation, 2024 (PLDI 2024)

  • Differentiable Synthesis of Program Architecture [pdf]; Guofeng Cui, He Zhu; Neural Information Processing Systems 2021 (NeurIPS 2021)

  • Improve CAM with Auto-adapted Sementation and Co-supervised Augmentation [pdf]; Ziyi kou, Guofeng Cui, Shaojie Wang, Wentian Zhao, Chenliang Xu; Proceedings of the IEEE/CVF Winter Conference on Application of Computer Vision 2021 (WACV 2021)

  • Talking-head Generation with Rhythmic Head Motion [pdf]; Lele Chen, Guofeng Cui, Celong Liu, Zhong Li, Ziyi Kou, Yi Xu, Chenliang Xu; European Conference on Computer Vision 2020 (ECCV 2020)

  • What Comprises a Good Talking-head Video Generation? [pdf]; Lele Chen, Guofeng Cui, Ziyi Kou, Haitian Zheng, Chenliang Xu; IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops 2020 (CVPR Workshops 2020)

  • Improving the efficiency of thermal covert channels in multi-/many-core systems [pdf]; Zijun Long, Xiaohang Wang, Yingtao Jiang, Guofeng Cui, Li Zhang, Terrence S. T. Mak 2018 Design, Automation Test in Europe Conference Exhibition (DATE 2018)

Experience

  • Reviewer for CVPR 2025. (2024.12)
  • Reviewer for ICLR 2025. (2024.10)
  • Applied Scientist Intern in Amazon Prime Video (Mentor: Pichao Wang) (2024.06 - 2024.09)
  • Reviewer for AAAI 2024. (2023.11 )
  • Applied Scientist Intern in Amazon Prime Video (Mentor: Pichao Wang) (2023.06 - 2023.09)