Liu Jiacheng will join Shanghai Jiao Tong University Global Institute of Future Technology in September 2026 as a tenure-track associate professor. Selected into the National High-Level Young Talents Program and the Shanghai Overseas High-Level Young Talents Program. His main research directions include large models, agents, and cross-applications of artificial intelligence. He has published more than 30 CCF-A papers in top conferences and journals in related fields, and won 3 international conference best paper (nomination) awards. Guiding students to obtain top talent programs from many companies including Bytedance Cloud, Tencent Qingyun, JD.com's Top Young Technical Genius Program (TGT), and Xiaomi Future Star. Undergraduate students with sufficient ability in related engineering majors are welcome to join the research group. Long-term recruitment of masters, PhDs, postdoctoral fellows, research assistants.
2011-2015，Dalian University of Technology，School of Software，B.S
2015-2017，Shanghai Jiao Tong University，School of Software，M.S
2017-2022，Shanghai Jiao Tong University，School of Electronic Information and Electrical Engineering，Ph.D
2026 - Pres.，Global Institute of Future Technology, Shanghai Jiao Tong University，Tenure-track Associate Professor
2025 - 2026, Hong Kong University of Science and Technology，Postdoctoral Researcher
2022 - 2025, The Chinese University of Hong Kong，Postdoctoral Researcher
Large Language Models, Agents
AI for Engineering/Science
2026，National High-Level Young Talent Program
2026，Shanghai High-Level Young Talent Program
Reviewer for top-tier conferences and journals such as ICML, ICLR, TC, and TNNLS.
1. Jiacheng Liu, et al. “Causal Dependency-Aware Unsupervised Routing for Large Reasoning Model.” The Forty-third International Conference on Machine Learning, July. 2026.
2. Jiacheng Liu, et al. “A Survey on Inference Optimization Techniques for Mixture of Experts Models”. ACM Computing Surveys, Mar. 2026.
3. Jiacheng Liu, et al. “scHeteroNet: A Heterophily-Aware Graph Neural Network for Accurate Cell Type Annotation and Novel Cell Detection”. Advanced Science, Mar. 2025
4. Jiacheng Liu, et al. “Space-Exit: Enabling Efficient Adaptive Computing in Space with Early Exits”. Proc. the USENIX Annual Technical Conference, Jul. 2025.
5. Jiacheng Liu, et al. “Noisy Multi-Label Aggregation with Self-Supervised Graph Transformer in Mobile Crowdsourcing”. IEEE Transactions on Mobile Computing, Dec, 2025.
6. Jiacheng Liu, et al. “BAT: A Versatile Bipartite Attention-based Approach for Comprehensive Truth Inference in Mobile Crowdsourcing”. IEEE Transactions on Mobile Computing, Apr. 2025.
7. Jiacheng Liu, et al. “An Adaptive and Interpretable Congestion Control Service Based on Multi-Objective Reinforcement Learning”. IEEE Transactions on Service Computing, Dec. 2024.
8. Jiacheng Liu, et al. “Practical Network Modeling Using Weak Supervision Signals for Human-Centric Networking in Metaverse”. IEEE Journal on Selected Areas in Communications, Dec. 2023.
9. Tianle Chen, Pengyu Cheng, Qiyuan Zhu, Jiacheng Wang, Bei Liu, Hao Gu, Ruijie Shen, Xiaofeng Hou, Sirui Han, Jiacheng Liu*. “Adaptive Spatial and Temporal Redundancy Optimization for Efficient Reasoning in Large Language Models”. The 64th Annual Meeting of the Association for Computational Linguistics (ACL, CCF A), 2026.
10. Hao Liu, Jiacheng Liu*, et al. “Towards a Foundation Model for Crowdsourced Label Aggregation”. The Fourteenth International Conference on Learning Representations (ICLR, CCF A), 2026.
