个人简介   　　

孔树锋，副教授，硕士生导师，565net必赢客户端百人计划青年学术骨干。2018年10月毕业于澳大利亚悉尼科技大学工程与信息技术学院，获博士学位。分别于美国加州大学尔湾分校 (2017.11—2018.05) 、美国康奈尔大学 (2018.10—2020.09) 和新加坡南洋理工大学 (2020.10—2022.08) 从事科研工作, 并于2022年9月加盟565net必赢客户端。

本人的研究内容主要包括多智能体系统、深度学习、强化学习、自动推理与规划、约束优化、Computational Sustainability、AI for Scientific Discovery（particularly in materials science, biology, and agriculture)、多标签分类、多目标回归、大语言模型等。

本人目前已在Nature Communications、NeurIPS、ICML、AAAI、IJCAI、CP和AAMAS等国际顶尖期刊和会议上发表学术论文20余篇，并参与国内外重大科研项目多项。本人长期担任多个期刊和会议（NeurIPS、ICML、ICLR、AAAI、IJCAI和TNNLS等）的审稿人。

本人亦长期与康奈尔大学Carla Gomes教授团队(https://www.cs.cornell.edu/gomes/) 、南洋理工大学安波教授团队(https://personal.ntu.edu.sg/boan/) 和悉尼科技大学李三江教授团队（https://profiles.uts.edu.au/Sanjiang.Li） 保持良好合作关系。 另外个人主页请参见 (https://sk2299.github.io)。欢迎有意向合作的单位或个人来信联系，也欢迎有意攻读必赢官网研究生的同学或有意来565net必赢客户端从事博士后工作的同仁与我联系。

　　

研究团队

565net必赢客户端区块链与智能金融研究中心

  • 大语言模型的高效适配、可控生成、生成内容的质量评估方法研究等

康奈尔大学可持续发展计算研究所

  • 大规模组合优化（应用于渔业管理优化、作业调度等）、大规模种群分布预测（应用于鱼群、鸟群分布预测等）、复杂决策过程（应用于亚马逊大坝选址，新能源材料开发等）、AI for drug design等

　　

招生简介

欢迎有意保送或报考565net必赢客户端研究生的同学与我联系，来信请附上个人简历、本科阶段成绩单等材料以供参考。同时也欢迎本校学有余力、动手能力强并对科研有浓厚兴趣的本科生加入课题组。

 

电子邮箱

kongshf@mail.sysu.edu.cn

 

工作经历

  •  2022年9月至今               565net必赢客户端，副教授
  •  2020年9月-2022年8月    新加坡南洋理工大学计算机科学与工程学院，研究员
  •  2018年10月-2020年9月  美国康奈尔大学计算机科学系，博士后研究员

　　

学术论文（*即通讯作者）

  • Shufeng Kong, Caihua Liu, and Carla Gomes (2024): IPGPT: Solving Integer Programming Problems with Sequence to Contrastive Multi-Label Learning. In the 40th Conference on Uncertainty in Artificial Intelligence, accepted. (CCF-B)

  • Yingheng Wang, Shufeng Kong*, John Gregoire, Carla Gomes (2024): Conformal Crystal Graph Transformer with Robust Encoding of Periodic Invariance. AAAI 2024, accepted. (CCF-A)

  • Yimeng Min, Ming-Chiang Chang, Shufeng Kong*, John M. Gregoire, R. Bruce van Dover, Michael O. Tompson, and Carla P. Gomes (2023): Physically Informed Graph-based Deep Reasoning Net for Efficient Combinatorial Phase Mapping. In: the 22nd International Conference on Machine Learning and Applications (ICMLA), accepted. (EI)

  • Hao Cheng, Shufeng Kong*, Yanchen Deng, Caihua Liu, Xiaohu Wu, Bo An, Chongjun Wang. Exploring leximin principle for fair core-selecting combinatorial auctions: Payment rule design and implementation. Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), accepted. (CCF A) 
  • Shufeng Kong, Francesco Ricci, Dan Guevarra, Jeffrey B. Neaton, Carla P. Gomes, and John M. Gregoire (2022): Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings. Nature Communications (Impact Factor: 14.92), 13(1), 1-12. (JCR Q1)
  • Junwen Bai, Yuanqi Du, Yingheng Wang, Shufeng Kong, John Gregoire, Carla Gomes (2022): Xtal2DoS: Attention-based crystal to sequence learning for density of states prediction. NeurIPS Workshop on AI for Science.
  • Yanchen Deng, Shufeng Kong*, Caihua Liu, and Bo An (2022): Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems. In: the 36th Annual Conference on Neural Information Processing Systems (NeurIPS'22), accepted. (CCF A)
  • Junwen Bai, Shufeng Kong*, and Carla P. Gomes (2022): Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification. In: the 39th International Conference on Machine Learning (ICML'22), accepted. (CCF A)
  • Yanchen Deng, Shufeng Kong*, and Bo An (2022): Pretrained cost model for distributed constraint optimization problems. In: the 36th AAAI Conference on Artificial Intelligence (AAAI'22). pp. 9331-9340. (CCF A)
  • Shufeng Kong, Dan Guevarra, Carla Gomes, and John Gregoire (2021): Materials representation and transfer learning for multi-property prediction. Applied Physics Reviews (Impact Factor: 19.162), 8(2). (JCR Q1)
  • Wenting Zhao, Shufeng Kong, Junwen Bai, Daniel Fink, and Carla Gomes (2021): HOTVAE: Learning high-order label correlation for multi-label classification via attention-based variational autoencoders. In: the 35th AAAI Conference on Artificial Intelligence (AAAI'21), pp. 15016-15024. (CCF A)
  • Shufeng Kong, Junwen Bai, Jae Hee Lee, Di Chen, Andrew Allyn, Michelle Stuart, Malin Pinsky, Kathy Mills and Carla Gomes (2020): Deep hurdle networks for zero-inflated multi-target regression: application to multiple species abundance estimation. In: the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), pp. 4375-4381. (CCF A)
  • Junwen Bai, Shufeng Kong and Carla Gomes (2020): Disentangled variational autoencoder based multi-label classification with covariance-aware multivariate probit model. In: the 29th International Joint Conference on Artificial Intelligence (IJCAI'20), pp. 4313-4321. (CCF A)
  • Shufeng Kong, Jae Hee Lee and Sanjiang Li (2018): A new distributed algorithm for efficient generalized arc-consistency propagation. Autonomous agent and multi-agent systems (Impact Factor: 1.419), 32(5):569-601. (JCR Q3)
  • Shufeng Kong, Jae Hee Lee and Sanjiang Li (2018): Multiagent simple temporal problem: the arc-consistency approach. In: the 32th AAAI Conference on Artificial Intelligence (AAAI’18), New Orleans, Louisiana, USA, February 2-7, 2018. (CCF A)
  • Shufeng Kong, Jae Hee Lee and Sanjiang Li (2017): A deterministic distributed algorithm for reasoning with connected row-convex constraints. In: the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'17), pp. 203-211. (CCF B)
  • Shufeng Kong, Sanjiang Li and Michael Sioutis (2018): Exploring directional path-consistency for solving constraint networks. The Computer Journal (Impact Factor: 0.98), 61(9): 1138-1350. (JCR Q4)
  • Shufeng Kong, Sanjiang Li, Yongming Li and Zhiguo Long (2015): On tree-preserving constraints. In: the 21st International Conference on Principles and Practice of Constraint Programming (CP'15), pp. 244-261. (CCF B)
  • Shufeng Kong, Sanjiang Li, Yongming Li and Zhiguo Long (2017): On tree-preserving constraints. Annals of Mathematics and Artificial Intelligence (Impact Factor: 1.011), 81(3-4): 241-271. (JCR Q3)
  • Carla P. Gomes, Junwen Bai, Yexiang Xue, Johan Bjorck, Brendan Rappazzo, Sebastian Ament, Richard Bernstein, Shufeng Kong, Santosh K. Suram, R. Bruce van Dover, John M. Gregoire (2019): CRYSTAL: a multi-agent AI system for automated mapping of materials’ crystal structures. MRS Communications (Impact Factor: 1.935), 9(2):600-608. (JCR Q4)
  • Qiong Liu, Jiajun Zhuang and Shufeng Kong (2013): Detection of pedestrians for far-infrared automotive night vision systems using learning-based method and head validation. Measurement Science and Technology, 24(7):074022.
  • Qiong Liu, Jiajun Zhuang and Shufeng Kong (2012): Detection of pedestrians at night time using learning-based method and head validation. IEEE International Conference on Imaging Systems and Techniques (IST), pp. 398-402.

 

科研项目

  • Accelerated Learning Lab: Capturing Deep Structure to Accelerate Materials Discovery，丰田汽车研究院，参与，2017-2021
  • Collaborative Research: CompSustNet: Expanding the Horizons of Computational Sustainability，美国自然科学基金，参与，2015-2021
  • Convergence Research to Meet Ocean Decision Challenges，美国自然科学基金，参与，2020-2022
  • 多无人机系统的多对多指派算法与协同优化，国家自然科学基金面上项目, 参与，2021-2024

 

学术服务（学术兼职）

  • IEEE TNNLS, IEEE TCDS, IEEE Cybernetics, Science Advances 等期刊审稿人
  • AAAI, IJCAI, ICLR, NeurIPS, ICML, AAMAS等国际学术会议审稿人