Dr. Li Li | 栗力

Assistant Professor

State Key Laboratory of Internet of Things for Smart City
Department of Computer and Information Science
Faculty of Science and Technology
University of Macau
Email: LLiLi@um.edu.mo

Short Bio

Dr. Li Li is currently an Assistant Professor in University of Macau. He received his  Ph.D. degree from the Ohio State University in 2018, the M.S. degree from the Ohio State University in 2014, and the B.S. degree from Tianjin University in 2011. He has research experience in different research institutions such as ShenZhen Institute of Technology, Chinese Academy of Science, Huawei Research and Microsoft Research. He has published in refereed journals and conference proceedings, such as MICRO, NIPS, ICML, INFOCOM, RTSS, CVPR, SENSYS, IJCAI, ICDCS, NDSS, MM, TMC, TDSC, TPDS, TNNLS, CIKM, ECAI. 

Openings

We have research positions for Postdoc, PhD student, Research Assistant and visiting student! Please feel free to contact me if interested!

Research Interests

Federated Learning, On-Device Learning, Mobile/Cloud Computing, Autonomous Driving, Distributed Learning. 

Selected Publications

2024

1. Chunlin Tian, Zhan Shi, Zhijiang Guo, Li Li*, ChengZhong Xu, “HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning”, Annual Conference on Neural Information Processing (NIPS, Oral) 2024. 

2. Kahou Tam; Chunlin Tian; Li Li*, Haikai Zhao, ChengZhong Xu, “FedHybrid: Breaking the Memory Wall of Federated Learning via Hybrid Tensor Management”, ACM Conference on Embedded Networked Sensor System (SENSYS) 2024. 

3. Chunlin Tian, Zhan Shi, Xinpeng Qin, Li Li*, ChengZhong Xu, ” Ranking-based Client Selection with Imitation Learning for Efficient Federated Learning”, International Conference on Machine Learning (ICML) 2024. 

4. Zhiyuan Ning, Chunlin Tian, Meng Xiao, Wei Fan, Pengyang Wang, Li Li*, Pengfei Wang, Yuanchun Zhou, “FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization”, International Joint Conference on Artificial Intelligence (IJCAI) 2024. 

5.Chunlin Tian, Li Li*, Kahou Tam, Yebo Wu, ChengZhong Xu, “Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting”, Transactions on Parallel and Distributed Systems (TPDS) 2024. 

6. Haicheng Liao, Yongkang Li, Chengyue Wang, Yanchen Guan, KaHou Tam, Chunlin Tian, Li Li, ChengZhong Xu, Zhenning Li, “When, Where and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models”, International Conference on Multimedia (MM) 2024. 

7. Haicheng Liao, Haoyu Sun, Huanming Shen, Chengyue Wang, KaHou Tam, Chunlin Tian, Li Li, Chengzhong Xu, Zhenning Li, “CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions”, International Conference on Multimedia (MM) 2024. 

8. Jialiang Ma, Chunlin Tian, Li Li*, ChengZhong Xu, “FedMG: A Federated Multi-Global Optimization Framework for Autonomous Driving”, International Symposium on Quality of Service (IWQoS) 2024. 

9. Yebo Wu, Li Li*, Chunlin Tian, Tao Chang, Chi lin, Cong Wang, Chengzhong Xu, “Heterogeneity-Aware Memory-Efficient Federated Learning via Progressive Layer Freezing”, International Symposium on Quality of Service (IWQoS) 2024. 

10. Shichen Zhan, Yebo Wu, Chunlin Tian, Yan Zhao, Li Li*, “Heterogeneity-Aware Coordination for Federated Learning via Stitching Pre-trained Blocks”, International Symposium on Quality of Service (IWQoS) 2024. 

11. Meihan Wu, Li Li*, Tao Chang, Jie Zhou, Cui Miao, Xiaodong Wang, ChengZhong Xu, “PFed-DBA: Distribution Bias Aware Personalized Federated Learning for Data Heterogeneity”, International Symposium on Quality of Service (IWQoS) 2024. 

12. Meihan Wu, Li Li*, Tao Chang, Peng Qiao, Cui Miao, Jie Zhou, Jingnan Wang, Xiaodong Zhang, “FedEKT: Ensemble Knowledge Transfer for Model-Heterogeneous Federated Learning”, International Symposium on Quality of Service (IWQoS) 2024. 

13. Chunlin Tian, Xinpeng Qin, Li Li, ” GreenLLM: Towards Efficient Large Language Model via Energy-Aware Pruning”, International Symposim on Quality of Service (IWQOS, poster) 2024. 

2023

1. Jialiang Ma, Li Li*, Zejiang Wang, Jun Wang, ChengZhong Xu, “HCPerf: Driving Performance-Directed Hierarchical Coordination for Autonomous Vehicles”, International Conference on Distributed Computing Systems (ICDCS) 2023. 

2. Jialing Ma, Li Li*, ChengZhong Xu, “AutoRS: Environment-dependent Real-Time Scheduling for End-to-End Autonomous Driving”, Transactions on Parallel and Distributed Systems (TPDS) 2023. 

3. Tam Ka Hou, Li Li*, Yan Zhao, ChengZhong Xu, “FedCoop: Cooperative Federated Learning for Noisy Labels”, European Conference on Artificial Intelligence (ECAI) 2023. 

4. Tam Ka Hou, Li Li*, Bo Han, ChengZhong Xu, Huazhu Fu, “Federated Noisy Client Learning”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 2023. 

5. Tao Chang, Li Li*, Meihan Wu, Wei Yu, Xiaodong Wang, “FedHybrid: Hierarchical Hybrid Training for High-Performance Federated Learning”, International Conference on Sensing, Communication, and Networking (SECON) 2023. 

6. Chunlin Tian, Zhan Shi, Li Li*, “Learn to Select: Efficient Cross-device Federated Learning via Reinforcement Learning”, International Conference on Learning Representations (ICLR Tiny) 2023. 

7. Tao Chang, Li Li*, Meihan Wu, Xiaodong Wang, ChengZhong Xu, “GraphCS: Graph-based Client Selection for Heterogeneity in Federated Learning”, Journal of Parallel and Distributed Computing (JPDC) 2023. 

8. Tao Chang, Li Li*, Meihan Wu, Xiaodong Wang, ChengZhong Xu, “PAGroup: Privacy-Aware Grouping Framework for High-Performance Federated Learning”, Journal of Parallel and Distributed Computing (JPDC) 2023. 

2022

1. Chunlin Tian, Li Li*, Zhan Shi, Jun Wang, ChengZhong Xu, “HARMONY: Heterogeneity-Aware Hierarchical Management for Federated Learning System”, IEEE/ACM International Symposium on Microarchitecture (MICRO) 2022. 

2. Liang Gao, Huazhu Fu, Li Li*, Yingwen Chen, Ming Xu, ChengZhong Xu, “FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction”, International Conference on Computer Vision and Pattern Recognition (CVPR) 2022. 

3. Meihan Wu, Li Li*, Tao Chang, Eric Rigall, Xiaodong Wang, ChengZhong Xu, “FedCDR: Federated Cross-Domain Recommendation for Privacy-Preserving Rating Prediction”, ACM International Conference on Information and Knowledge Management (CIKM) 2022. 

4. Liu HongZhou, Wenli Zheng, Li Li*, Minyi Guo, “LoADPart: Load-Aware Dynamic Partition of Deep Neural Network for Edge Offloading”, International Conference on Distributed Computing Systems (ICDCS) 2022. 

5. Liang Gao, Li Li*, Yingwen Chen, ChengZhong Xu, MingXu, “FGFL: A Blockchain-based Fair Incentive Governor for Federated Learning”, Journal of Parallel and Distributed Computing (JPDC) 2022. 

6. Yunhao Bai, Li Li, Zejiang Wang, Xiaorui Wang, Junmin Wang, “Performance Optimization of Autonomous Driving Control under End-to-End Deadlines”, Real-Time Systems (RTS) 2022. 

7. Jiang Bian, Abdullah AI Arafat, Haoyi Xiong, Jing Li, Li Li, Hongyang Chen, Dejing Dou, Jun Wang, Zhishan Guo, “Machine Learning in Real-Time Internet of Things Systems, IEEE Internet of Things Journal (IoT-J) 2022. 

2021

1. Li Li, Xiaorui Wang, Wenli Zheng, ChengZhong Xu, “SmartDistance: A Mobile-based Positioning System for Automatically Monitoring Social Distance”, International Conference on Computer Communications (INFOCOM) 2021. 

2. Liang Gao, Li Li*, Yingwen Chen, Wenli Zheng, ChengZhong Xu, Ming Xu, “FIFL: A Fairness Incentive Framework for Federated Learning”, International Conference on Parallel Processing (ICPP) 2021. 

3. Cong Wang, Yanru Xiao, Xing Gao, Li Li, Jun Wang, “A Framework for Behavioral Biometric Authentication using Deep Metric Learning on Mobile Devices”, Transactions on Mobile Computing (TMC), 2021. 

4. Xing Gao, Guannan Liu, Zhang Xu, Haining Wang, Li Li, Xiaorui Wang, “Investigating Security Vulnerabilities in a Hot Data Center with Reduced Cooling Redundancy”, Transactions on Dependable and Secure Computing (TDSC) 2021.

5.  Wenting Zou, Li Li, Zichen Xu, Dan Wu, ChengZhong Xu, “SmartDL: Energy-Aware Decremental Learning in a Mobile-based Federation for Geo-spatial Systems”, Neural Computing and Applications, 2021. 

 

2020

1. Li Li, Xiaorui Wang, Feng Qin, “EnergyDx: Diagnosing Energy Anomaly in Mobile Apps by Identifying the Manifestation Point”, International Conference on Distributed Computing Systems (ICDCS) 2020. 

2. Li Li, Jun Wang, Xu Chen, ChengZhong Xu, ” Multi-layer Coordination for High-Performance Energy-Efficient Federated Learning”, International Symposium on Quality of Service (IWQoS) 2020. 

3. Li Li, Jun Wang, ChengZhong Xu, “FLSim: An Extensible and Reusable Simulation Framework for Federated Learning”, International Conference on Simulation Tools and Techniques (SIMUtools) 2020. 

4. Guomei Shi, Li Li, Jun Wang, Weiyan Chen, ChengZhong Xu, Kejiang Ye, “HySync: Hybrid Federated Learning with Effective Synchronization” International Conference on High Performance Computing and Communications (HPCC) 2020. 

5. Zichen Xu, Li Li, Wenting Zou, “Exploring Federated Learning on Battery-powered devices”, ACM Turing Celebration Conference China (ACM TURC), 2020. 

6. Baoxin Zhao, ChengZhong Xu, Siyuan Liu, Juanjuan Zhao, Li Li, “Dynamic Traffic Bottlenecks Identification based on Congestion Diffusion Model by Influence Maximization in Metrocity Scales”, Concurrency and Computation: Practice and Experience 2020. 

 

2019

1. Li Li, Haoyi Xiong, Zhishan Guo, Jun Wang, ChengZhong Xu, “SmartPC: Hierarchical Pace Control in Real-Time Federated Learning System”, IEEE Real-Time Systems Symposium (RTSS) 2019. 

2. Cong Wang, Yanru Xiao, Xing Gao, Li Li, Jun Wang, “Close the Gap between Deep Learning and Mobile Intelligence by Incooperating Training in the Loop”, ACM Multimedia (MM) 2019. 

3. Wensi Yang, Yuhang Zhang, Kejiang Ye, Li Li, ChengZhong Xu, “FFD: A Federated Learning based Method for Credit Card Fraud Detection”, International Congress on Bigdata (BigData) 2019. 

4. Baoxin Zhao, Chengzhong Xu, Siyuan Liu, Juanjuan Zhao, Li Li, “A Congestion Diffusion Model with Influence Maximization for Traffic Bottleneck Identification in Metrocity Scales”, IEEE BigData (BigData) 2019. 

2018 and Before

1. Xing Gao, Xu Zhang, Haining Wang, Li Li, Xiaorui Wang, “Reduced Cooling Redundancy: A New Security Vulnerability in a Hot Data Center”, Network and Distributed Security Symposium (NDSS) 2018. 

2. Kuangyu Zheng, Wenli Zheng, Li Li, Xiaorui Wang, “PowerNetS: Coordinating Data Center Network with Servers and Cooling for Power Optimization”, IEEE Transactions on Network and Service Management (TNSM) 2017. 

3. Li Li, Yunhao Bai, Xiaorui Wang, Feng Qin, “Selective Checkpointing for Minimizing Recovery Energy and Efforts of Smartphone Apps”, International Green and Sustainable Computing Conference (IGSC) 2017. 

4. Li Li, Bruce Beitman, Mai Zheng, Xiaorui Wang, “eDelta: Pinpointing Energy Deviations in Smartphone Apps via Comparative Trace Analysis”, International Green and Sustainable Computing Conference (IGSC) 2017. 

5. Xing Gao, Zhang Xu, Haining Wang, Li Li, Xiaorui Wang, “Why Some Like It Hot Too: Thermal Attack on Data Centers”, ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) 2017. 

6.  Li Li, Yunhao Bai, Xiaorui Wang, Mai Zheng, Feng Qin, “Selective Checkpointing for Minimizing Recovery Efforts of Smartphone Apps”, International Conference on Autonomic Computing (ICAC) 2017. 

7. Li Li, Jun Wang, Xiaorui Wang, Handong Ye, Ziang Hu, “SceneMan: Bridging Mobile Apps with System Energy Manager via Scenario Notification”, ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED) 2017. 

8. Li Li, Wenli Zheng, Xiaorui Wang, Xiaodong Wang, “Data Center Power Minimization with Placement Optimization of Liquid-Cooled Servers and Free Air Cooling”, Sustainable Computing (Elsevier) 2016. 

9. Li Li, Wenli Zheng, Xiaodong Wang, Xiaorui Wang, “Coordinating Liquid and Free Air Cooling with Workload Allocation for Data Center Power Minimization”, International Conference on Autonomic Computing (ICAC) 2014. 

10. Li Li, Wenli Zheng, Xiaodong Wang, Xiaorui Wang, “Placement Optimization of Liquid-Cooled Servers for Power Minimization in Data Centers”, International Green Computing Conference (IGCC) 2014. 

11. Kuangyu Zheng, Xiaodong Wang, Li Li, Xiaorui Wang, “Joint Power Optimization of Data Center Network and Servers with Correlation Analysis”, International Conference on Computer Communications (INFOCOM) 2014.