黄婷，西安电子科技大学广州研究院的华山准聘副教授、硕士生导师，是刘静教授带领的工业人工智能团队核心成员之一。2021年于华南理工大学取得博士学位（导师：龚月姣教授）。目前主要研究方向包括智能计算、机器学习、深度学习、运筹规划、智能物流、智能交通等，累计发表论文10余篇。主持国家自然科学基金青年项目一项、市级项目一项，参与国家自然科学基金面上项目。共同指导研一学生获得2022年WSC国际仿真竞赛第一名（多智能体路径规划方向）。

招生信息

可招收4名硕士研究生（2026年）。欢迎对智能计算、机器学习、深度学习、路径规划、多智能体系统等研究方向感兴趣的研究生和优秀本科生加入我们的研究团队。有意向的同学请邮件联系 huangting (AT) xidian.edu.cn 。

欢迎勤勉刻苦、踏实上进、对学术充满热情的同学报考。我会提供科学性、系统性和方向性的培养方案，提供结合学生兴趣的学术发展路径，手把手带教，提供必要的资源和支持。。

发表期刊

[12] F. Zhuang, T. Huang*, Q. Xu, Y.-J. Gong, J. Liu, “A robust lifelong multi-agent path finding with active conflict resolution and decentralized execution”, IEEE Robotics and Automation Letters, 2025.

[11] T. Huang, B.-B. Niu, Y.-J. Gong, J. Liu, An Efficient History-Guided Surrogate Models-Assisted Niching Evolutionary Algorithm for Expensive Multimodal Optimization, Swarm and Evolutionary Computation, 2025. 

[10]  X. -C. Wang, Y. -J. Gong, T. Huang, H. Xu and J. Zhang, “Long-Distance Charge-Route Planning for Electric Vehicles: A Multi-Solution Approach,” IEEE Transactions on Transportation Electrification. 2025.

[9] L.-S. Xu, T. Huang*, B.-W. Zhao, Y.-J. Gong and J. Liu, “Continuous berth allocation and time-variant quay crane assignment: Memetic algorithm with a heuristic decoding method,” IEEE Transactions on Intelligent Transportation Systems, , vol. 26, no. 3, pp. 3387-3401, Mar. 2025.

[8] T. Huang, Z.-Q. Zhang, Y.-J. Gong and J. Liu, “nLKH-ACS: A Niching Lin-Kernighan-Helsgaun Based Ant Colony System for Multi-Solution Traveling Salesman Problems,” IEEE Transactions on Evolutionary Computation, 2025. 

[7]  Y.-H. Sun, T. Huang*, J.-H. Zhong, J. Zhang and Y.-J. Gong, “Symbolic Regression-Assisted Offline Data-Driven Evolutionary Computation,” IEEE Transactions on Evolutionary Computation. 2024.

[6] Y.-J. Gong, T. Huang*, Y. -N. Ma, S. -W. Jeon and J. Zhang, “MTrajPlanner: A Multiple-Trajectory Planning Algorithm for Autonomous Underwater Vehicles,”  IEEE Transactions on Intelligent Transportation Systems. vol. 24, no. 4, pp. 3714-3727, April 2023.

[5] Z.-H. Zhan, J. Zhang, Y. Lin, J.-Y. Li, T. Huang, X.-Q. Guo, F.-F. Wei, S. Kwong, X.-Y. Zhang, R. You, “Matrix-Based Evolutionary Computation,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 2, pp. 315-328, Apr. 2022. 

[4] T. Huang, Y.-J. Gong, W.-N. Chen, H. Wang and J. Zhang, “A Probabilistic  Niching Evolutionary Computation Framework Based on Binary Space Partitioning,” IEEE  Transactions on Cybernetics, vol. 52, no. 1, pp. 51-64, Jan. 2022. （中科院SCI一区TOP期刊， IF=11.448/2021）

[3] T. Huang, Y.-J. Gong, S. Kwong, H. Wang and J. Zhang, “A Niching Memetic  Algorithm for Multi-Solution Traveling Salesman Problem,” IEEE Transactions on  Evolutionary Computation, vol. 24, no. 3, pp. 508-522, Jun. 2020. （中科院SCI一区TOP期刊, IF =11.554/2021）

[2] T. Huang, D.-T. Duan, Y.-J. Gong, L. Ye, W.-W.Y. Ng, J. Zhang, “Concurrent Optimization of Multiple Base Learners in Neural Network Ensembles: An Adaptive Niching Differential Evolution Approach,” Neurocomputing, vol. 396, pp. 24-38, Jul. 2020.

[1] T. Huang, Y.-J. Gong, Y.-H. Zhang, Z.-H. Zhan and J. Zhang, “Automatic  Planning of Multiple Itineraries: A Niching Genetic Evolution Approach,” IEEE  Transactions on Intelligent Transportation Systems, vol. 21, no. 10, pp. 4225-4240,  Oct. 2020. （中科院SCI一区TOP期刊，IF=6.492/2021）

会议

[4] J.-J. Li, Z.-Y. Ma, T. Huang*, Y.-J. Gong, “Learn to refine: Synergistic multiagent path optimization for lifelong conflict-free navigation of autonomous vehicles,” in Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025. (CCF-A)

[3]  F. Zhuang, T. Huang, H. Yu, and J. Liu, "An empirical study of constrained evolutionary algorithms for isomorphic connected graph segmentation problems," in Proc. Genetic and Evolutionary Computation Conference Companion, Jul. 2024, pp. 459–462. (CCF-C)

[2]  H.-Q. Lian, Z.-Y. Ma, H.-S. Guo, T. Huang, and Y.-J. Gong, "RLEMMO: Evolutionary multimodal optimization assisted by deep reinforcement learning," in Proc. Genetic and Evolutionary Computation Conference, Jul. 2024, pp. 683–693. (CCF-C)

[1] X.-W. Ma, T. Huang, W.-L. Liu, and Y.-J. Gong, "Collision-aware evolutionary algorithm for multi-agent coverage path planning," in Proc. 11th Int. Conf. Machine Intelligence Theory and Applications, Jul. 2024, pp. 1–8.

google scholar: https://scholar.google.com/citations?hl=zh-CN&user=6QPNGSYAAAAJ

基本要求

1. 掌握主流编程语言C/C++, Python, Matlab等其中一项

2. 具有一定的英文读写能力