Photo

Shengcai LIU (刘晟材)

助理教授，博导
Tenure-Track Assistant Professor, Ph.D Supervisor
Department of Computer Science and Engineering
Southern University of Science and Technology

Office: Room 311, South Tower, College of Engineering
Address: No. 1088 Xueyuan Avenue, Shenzhen, China 518055
Email: liusc3 AT sustech DOT edu DOT cn

SUSTech logo Lab logo

Short Biography

个人简介

Research Interests

Grants & Awards

Selected Publications

(First/corresponding-authored works listed; * indicates corresponding author; See Google Scholar for the complete list.)

Preprints

  1. Tianhang Lu, Runtian Ren, Shengcai Liu*. Learning-Augmented Algorithms for Online Vertex Cover. arXiv preprint arXiv:2606.22831. [Arxiv] L2O
  2. Rui Xu, Yufan Liao, Haoze Lv, Shengcai Liu*, Yi Mei, Ke Tang. Large Language Model-Driven Cooperative Operator Ensemble Evolution for Permutation Flow Shop Scheduling. arXiv preprint arXiv:2606.15334. [Arxiv] L2O LLM/Agent Applications
  3. Ning Lu, Baijiong Lin, Shengcai Liu*, Jiahao Wu, Haoze Lv, Yanbin Wei, Lingting Zhu, Shengju Qian, Xin Wang, Ying-Cong Chen, Qi Wang, Ke Tang. Policy and World Modeling Co-Training for Language Agents. arXiv preprint arXiv:2606.02388. [Arxiv] LLM/Agent
  4. Haoze Lv, Ning Lu, Ziang Zhou, Shengcai Liu*. AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design. arXiv preprint arXiv:2605.08756. [Arxiv] L2O LLM/Agent
  5. Jiahao Wu, Ning Lu, Shengcai Liu*, Kun Wang, Yanting Yang, Bailong Lin, Chen Jason Zhang, Li Qing, Ke Tang. Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Models. arXiv preprint arXiv:2603.25184. [Arxiv] LLM/Agent

Journal Papers

  1. Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong, Xin Yao, and Ke Tang. MEGO: Learning Mixture-of-Experts for General-Purpose Binary Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2026, To appear. [Arxiv] L2O
  2. Qingya Li, Shengcai Liu*, Juan Zou, and Ke Tang. A novel dual-stage algorithm for capacitated arc routing problems with time-dependent service costs. Memetic Computing, 2026, 18(3): 33. [Paper][Arxiv] Applications
  3. Rui Xu, Xing Fan, Shengcai Liu*, Wenjie Chen, Ke Tang. Memetic Search for Green Vehicle Routing Problem with Private Capacitated Refueling Stations. IEEE Transactions on Evolutionary Computation, 2025, To appear. [Paper] [Arxiv] [Code] Applications
  4. Zhiyuan Wang, Shengcai Liu*, Peng Yang, and Ke Tang. Evolving Generalizable Parallel Algorithm Portfolios for Binary Optimization Problems via Domain-Agnostic Instance Generation. IEEE Transactions on Evolutionary Computation, 2025, To appear. [Paper] [Arxiv] [Code] L2O
  5. Wenjie Chen, Shengcai Liu*, Yew-Soon Ong, Li Zhuang, and Ke Tang. Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization. IEEE Transactions on Computational Social Systems, 2025, 12(6): 5155-5167. [Paper] [Arxiv] L2O Applications
  6. Zubin Zheng, Shengcai Liu*, and Yew-Soon Ong. Hybrid Memetic Search for Electric Vehicle Routing with Time Windows, Simultaneous Pickup-Delivery, and Partial Recharges. IEEE Transactions on Emerging Topics in Computational Intelligence, 2025, 9(6): 3773-3787. [Paper] [Arxiv] [Code] Applications
  7. Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu*, Qijiong Liu, Rui He, Qing Li, and Ke Tang. Condensing Pre-augmented Recommendation Data via Lightweight Policy Gradient Estimation. IEEE Transactions on Knowledge and Data Engineering, 2025, 37(1): 162 - 173. [Paper] [Arxiv] [Code] L2O Applications
  8. Xuanfeng Li, Shengcai Liu*, and Ke Tang. Novel Genetic Algorithm for Solving Chance-Constrained Multiple-Choice Knapsack Problems. Journal of Computer Applications, 2024, 44(5): 1378-1385. [Paper] Applications
  9. Xuanfeng Li, Shengcai Liu*, Jin Wang, Xiao Chen, Yew-Soon Ong, and Ke Tang. Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. IEEE Transactions on Cybernetics, 2024, 54(12): 7969 - 7980. [Paper] [Arxiv] [Code] L2O Applications
  10. Ning Lu, Shengcai Liu*, Rui He, Qi Wang, Yew-Soon Ong, and Ke Tang. Large Language Models can be Guided to Evade AI-Generated Text Detection. Transactions on Machine Learning Research, 2024. [Paper] [Arxiv] [Code] LLM/Agent
  11. Shengcai Liu, Ning Lu, Wenjing Hong, Chao Qian, and Ke Tang. Effective and Imperceptible Adversarial Textual Attack via Multi-objectivization. ACM Transactions on Evolutionary Learning and Optimization, 2024, 4(3): 16:1-16:23. [Paper] [Arxiv] [Code] Applications
  12. Shengcai Liu, Yu Zhang, Ke Tang, and Xin Yao. How Good Is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem. IEEE Computational Intelligence Magazine, 2023, 18(3): 14-28. [Paper] [Arxiv] [Code] L2O
  13. Zeyu Dai, Shengcai Liu*, Qing Li, and Ke Tang. Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. ACM Transactions on Intelligent Systems and Technology, 2023, 14(3): 1-20. [Paper] [Arxiv] [Code] Applications
  14. Rui He, Shengcai Liu*, Shan He, and Ke Tang. Multi-Domain Active Learning: Literature Review and Comparative Study. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023, 7(3): 791-804. [Paper] [Arxiv] Applications
  15. Shengcai Liu, Ning Lu, Cheng Chen, and Ke Tang. Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack. IEEE/ACM Transactions on Audio, Speech and Language Processing, 2022, 30: 98-111. [Paper] [Arxiv] [Code] Applications
  16. Shengcai Liu, Peng Yang, and Ke Tang. Approximately Optimal Construction of Parallel Algorithm Portfolios by Evolutionary Intelligence (in Chinese). SCIENTIA SINICA Technologica, 2023, 53(2): 280-290. [Paper] L2O
  17. Shengcai Liu, Ke Tang, and Xin Yao. Generative Adversarial Construction of Parallel Portfolios. IEEE Transactions on Cybernetics, 2022, 52(2): 784-795. [Paper] L2O
  18. Shengcai Liu, Ke Tang, and Xin Yao. Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows. Swarm and Evolutionary Computation, 66: 100927, 2021. [Paper] [Arxiv] [Code] Applications
  19. Shengcai Liu, Ke Tang, Peng Yang, and Xin Yao. Few-shots Parallel Algorithm Portfolio Construction via Co-evolution. IEEE Transactions on Evolutionary Computation, 2021, 25(3): 595-607. [Paper] [Arxiv] [Code] L2O

Conference Papers

  1. Jiyu Luo, Shaoyu Chen, Jingwei Sun, Shengcai Liu, Ke Tang, Guangzhong Sun. EMO: Energy Efficiency Modeling and Optimization for AI Workloads. In: Proceedings of The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'2026), Chicago, IL, Nov 15 - 20, 2026, To appear. L2O LLM/Agent
  2. Zubin Zheng, Jiahao Wu, Shengcai Liu*. Neural QAOA2: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization. In: Proceedings of the 43rd International Conference on Machine Learning (ICML'2026), Seoul, South Korea, Jul 6 - 11, 2026. L2O Quantum
  3. Zhangying Feng, Qianglong Chen, Ning Lu, Yongqian Li, Siqi Cheng, Shuangmu Peng, Duyu Tang, Shengcai Liu*, Zhirui Zhang*. Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs. In: Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS'2025), San Diego, CA, Nov 30 - Dec 7, 2025. [Paper] [Arxiv] LLM/Agent
  4. Haoze Lv, Zhiyuan Wang, Wenjie Chen, Shengcai Liu*. Cascaded Large-Scale TSP Solving with Unified Neural Guidance: Bridging Local and Population-based Search. In: Proceedings of the 28th European Conference on Artificial Intelligence (ECAI'2025), Bologna, Italy, Oct 25 - 30, 2025, 4961-4968. [Paper] [Arxiv] L2O Applications
  5. Ning Lu, Shengcai Liu*, Jiahao Wu, Weiyu Chen, Zhirui Zhang, Yew-Soon Ong, Qi Wang, Ke Tang. Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets. In: Proceedings of the 42nd International Conference on Machine Learning (ICML'2025), Vancouver, Canada, Jul 13 - 19, 2025. [Paper] [Arxiv] [Code] LLM/Agent
  6. Jiahao Wu, Ning Lu, Zeiyu Dai, Wenqi Fan, Shengcai Liu*, Qing Li, Ke Tang. Backdoor Graph Condensation. In: Proceedings of The 40th IEEE International Conference on Data Engineering (ICDE'2025), HongKong, China, May 19 - 23, 2025, 2267-2280. [Paper] [Arxiv] [Code] Applications
  7. Jiahao Wu, Qujiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu*, Qing Li, Xiao-Ming Wu, Ke Tang. Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content based Recommendation. In: Companion Proceedings of the ACM on Web Conference 2025 (WWW'2025), Sydney, Australia, Apr 28 - May 2, 2025, 1402-1406. [Paper] [Arxiv] [Code] LLM/Agent Applications
  8. Ning Lu, Shengcai Liu*, Zhirui Zhang, Qi Wang, Haifeng Liu, and Ke Tang. Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend. In: Proceedings of The 2024 IEEE Conference on Artificial Intelligence (CAI'2024), Singapore, Singapore, Jun 25 - 27, 2024, 823-830. [Paper] [Arxiv] Applications
  9. Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, and Yew-Soon Ong. Large Language Models as Evolutionary Optimizers. In: Proceedings of The 2024 IEEE Congress on Evolutionary Computation (CEC'2024), Yokohama, Japan, Jun 30 - Jul 5, 2024, 1-8. [Paper] [Arxiv] [Code] L2O LLM/Agent
  10. Rui He, Shengcai Liu*, Jiahao Wu, Shan He, and Ke Tang. Multi-Domain Learning From Insufficient Annotations. In: Proceedings of The 26th European Conference on Artificial Intelligence (ECAI'2023), Kraków, Poland, Sep 30 - Oct 4, 2023, 1028-1035. [Paper] [Arxiv] Applications
  11. Shengcai Liu, Fu Peng, and Ke Tang. Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. In: Proceedings of The 37th AAAI Conference on Artificial Intelligence (AAAI'2023), Washington, DC, Feb 7 - 14, 2023, 8852-8860. [Paper] [Arxiv] [Code] L2O Applications
  12. Fu Peng, Shengcai Liu*, and Ke Tang. Training Quantized Deep Neural Networks via Cooperative Coevolution. In: Proceedings of the 13th International Conference on Swarm Intelligence (ICSI'2022), Xi'an, China, Jul 15 - 19, 2022, 81-93. [Paper] Applications
  13. Kangfei Zhao, Shengcai Liu*, Yu Rong, and Jeffrey Xu Yu. Towards Feature-free TSP Solver Selection: A Deep Learning Approach. In: Proceedings of the 20th International Joint Conference on Neural Networks (IJCNN'2021), Virtual Event, Jul 18 - 22, 2021, 1-8. [Paper] [Arxiv] [Code] L2O
  14. Shengcai Liu, Ke Tang, and Xin Yao. On Performance Estimation in Automatic Algorithm Configuration. In: Proceedings of The 34th AAAI Conference on Artificial Intelligence (AAAI'2020), New York, NY, Feb 7 - 12, 2020, 2384-2391. [Paper] L2O
  15. Shengcai Liu, Ke Tang, and Xin Yao. Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. In: Proceedings of The 33rd AAAI Conference on Artificial Intelligence (AAAI'2019), Honululu, HI, Jan 27 - Feb 1, 2019, 1560-1567. [Paper] L2O

Professional Activities

People

Teaching



  |   © Shengcai LIU. Last updated: 2026-07-04.