[ICPR '26] Dhivya Dharshini Kannan, Wei Li, Wei Zhang (corresponding author), et al. "When Smaller Wins: Dual-Stage Distillation and Pareto-Guided Compression of Liquid Neural Networks for Edge Battery Prognostics." International Conference on Pattern Recognition (ICPR). IAPR. Lyon, France. August 17-22, 2026. [arXiv PDF]
[ICPR '26] Yunyi Zhao, Wei Zhang (corresponding author), Cheng Xiang, et al. "Diffusion-Modeled Reinforcement Learning for Carbon and Risk-Aware Microgrid Optimization." International Conference on Pattern Recognition (ICPR). IAPR. Lyon, France. August 17-22, 2026. [arXiv PDF]
[ICPR '26] Jasraj Singh, Fang Liu, Hong Xu, Bee Chin Ng, and Wei Zhang. "LingML: Linguistic-Informed Machine Learning for Enhanced Fake News Detection." International Conference on Pattern Recognition (ICPR). IAPR. Lyon, France. August 17-22, 2026. [arXiv PDF]
[IJCNN '26] Yuan Qiu, Wei Li, Wei Zhang (corresponding author), et al. "Interpretable Battery Aging without Extra Tests via Neural-Assisted Physics-based Modelling." International Joint Conference on Neural Networks (IJCNN). IEEE/INNS. Maastricht, Netherlands. June 21-26, 2026. [arXiv PDF]
[IJCNN '26] Alexander Matyasko, Xin Lou, Indriyati Atmosukarto, Wei Zhang. "TsallisPGD: Adaptive Gradient Weighting for Adversarial Attacks on Semantic Segmentation." International Joint Conference on Neural Networks (IJCNN). IEEE/INNS. Maastricht, Netherlands. June 21-26, 2026.
[SAC '26] Sara Sameer, Wei Zhang (corresponding author), Kannan Dhivya Dharshini, et al. “Pace: Physics-Aware Attentive Temporal Convolutional Network for Battery Health Estimation.” ACM/SIGAPP Symposium On Applied Computing (SAC), pp. 1140-1147. ACM. Thessaloniki, Greece. March 23–27, 2026. (acceptance rate: 23.4%) [arXiv PDF][GitHub Code][Google Drive PDF]
[SAC '26] Wei Li, Wei Zhang (corresponding author), and Qingyu Yan. “EntroLnn: Entropy-Guided Liquid Neural Networks for Operando Refinement of Battery Capacity Fade Trajectories.” ACM/SIGAPP Symposium On Applied Computing (SAC), pp. 1447-1454. ACM. Thessaloniki, Greece. March 23–27, 2026. (acceptance rate: 23.4%) [arXiv PDF][Google Drive PDF]
[SAC '26] Zhiying Yang, Fang Liu, Wei Zhang (corresponding author), et al. “LLM-Upgraded Graph Reinforcement Learning for Carbon-Aware Flexible Job Shop Scheduling in Smart Manufacturing.” ACM/SIGAPP Symposium On Applied Computing (SAC), pp. 831-838. ACM. Thessaloniki, Greece. March 23–27, 2026. (acceptance rate: 23.4%) [arXiv PDF][Google Drive PDF]
[SAC '26] Vijay Babu Pamshetti, Hiew Teng Kan, Wei Zhang (corresponding author), et al. “Shift: Sodium-battery Health Prediction with Integrated Frequency-aware Transfer Learning.” ACM/SIGAPP Symposium On Applied Computing (SAC), pp. 1942-1949. ACM. Thessaloniki, Greece. March 23–27, 2026. (acceptance rate: 23.4%). [Google Drive PDF]
[GLOBECOM '25] Wei Li, Wei Shen Jackson Ng, Wei Zhang (corresponding author), et al. “Driving Behavior-Aware Transformer for Practical Battery Capacity Estimation.” IEEE Global Communications Conference (GLOBECOM). IEEE. Taipei, China. December 8–12, 2025. [SIT PDF][Google Drive PDF][Slides]
[IV '25] Vijay Babu Pamshetti, Wei Zhang (corresponding author), King Jet Tseng, et al. "Optimal Signal Decomposition-based Multi-Stage Learning for Battery Health Estimation." IEEE Intelligent Vehicles Symposium (IV), pp. 2409-2414. IEEE. Cluj-Napoca, Romania. June 22-25, 2025. [PDF][Poster][DOI]
[VTC '25] Sara Sameer, Wei Zhang (corresponding author), Xin Lou, et al. "GiNet: Integrating Sequential and Context-Aware Learning for Battery Capacity Prediction." IEEE Vehicular Technology Conference (VTC), pp. 1-6. IEEE. Oslo, Norway. June 17-20, 2025. [PDF][Code][Sara's Slides][Sara's Video][DOI]
[CAI '25] Yanghui Mo, Xin Lou, Mageshwaran Muthusamy, Wei Zhang, et al. “Adversarially Trained Dynamic Ensemble: A Moving Target Defense Strategy for Robust Semantic Segmentation in Autonomous Vehicles.” IEEE Conference on Artificial Intelligence (CAI), pp. 1036-1043. IEEE. Santa Clara, California, USA. May 5-7, 2025. (Best Paper Award) [DOI]
Malcolm Yoke Hean Low, Chin Soon Chong, Changjun Yang, Sivakumar Nadarajan, Wei Zhang. “Development of a Multi-Objective Ship Operations Optimization Decision Support System.” International Conference on Industrial Engineering and Operations Management, pp. 1707-1716. Singapore, February 18-20, 2025. (Best Track Paper) [PDF][DOI]
[TENCON '24] Vijay Babu Pamshetti, Wei Zhang (corresponding author), Andy Man-Fai Ng, et al. "Enhanced Battery Degradation-Aware Scheduling for Distribution Network with Electric Vehicle Load." IEEE Region 10 Conference 2024 (TENCON), pp. 1044-1047. IEEE. Singapore. December 1–4, 2024. [PDF][DOI]
[VTC '24] Yunyi Zhao, Wei Zhang (corresponding author), Qingyu Yan, et al. "Practical Battery Health Monitoring using Uncertainty-Aware Bayesian Neural Network." IEEE Vehicular Technology Conference (VTC), pp. 1-6. IEEE. Washington DC, USA. October 7-10, 2024. [PDF][Slides][DOI]
[AIoT '24] Yunyi Zhao, Wei Zhang (corresponding author), Erhai Hu, et al. “BatSort: Enhanced Battery Classification with Transfer Learning for Battery Sorting and Recycling.” IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT), pp. 201-206. IEEE. Melbourne, Australia. July 24-26, 2024. [PDF][Data][Slides][DOI]
[AIoT '24] Fang Liu, Bosheng Ding, Chong Guan, Wei Zhang, et al. "Demystify Adult Learning: A Social Network and Large Language Model Assisted Approach.” IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT), pp. 207-212. IEEE. Melbourne, Australia. July 24-26, 2024. [PDF][DOI]
[SMC '23] Syabil Soedirman Salamat, Fang Liu, Zengyan Fan, Wei Zhang (corresponding author). “It Is About Weather: Explainable Machine Learning for Traffic Accident Understanding.” IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2689-2694. IEEE. Hawaii, USA. October 1–4, 2023. [PDF]
[ICC '22] Fang Liu, Teck Wei Low, Wei Zhang (corresponding author) et al. “TransLine: Transfer Learning for Accurate Power Line Anomaly Detection with Insufficient Data.” IEEE International Conference on Communications (ICC), pp. 5543-5548. IEEE. Seoul, South Korea. May 16–20, 2022. [PDF] [Data]
[GLOBECOM '21] Wei Zhang, Yonggang Wen, and Fang Liu. “Towards Cost-Optimal Energy Procurement for Cooling as a Service: A Data-Driven Approach.” IEEE Global Communications Conference (GLOBECOM). IEEE. Madrid, Spain. December 7 - 11, 2021. [PDF]
[ICME '19] Fang Liu, Wei Zhang, Yonggang Wen. “QoE-Driven Mobile Streaming: A Location-aware Approach.” IEEE International Conference on Multimedia & Expo (ICME), pp. 1708-1713. IEEE. Shanghai, China. July 8 - 12, 2019. [PDF]
[SPAWC '17] Wei Zhang, Yonggang Wen, Ying Jun (Angela) Zhang, et al. “Mobile Cloud Computing with Voltage Scaling and Data Compression.” IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE. Hokkaido, Japan. July 3 - 6, 2017. (invited paper) [PDF]
[IPDPS '16] Pan Lai, Rui Fan, Wei Zhang et al. “Utility Maximizing Thread Assignment and Resource Allocation.” IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 433-42. IEEE. Orlando, Florida USA. May 29 - June 2, 2016. (acceptance rate: 23%) [PDF]
[CLOUD '15] Fang Liu, Wee Keong Ng and Wei Zhang. “Encrypted SVM for Outsourced Data Mining.” IEEE International Conference on Cloud Computing (CLOUD), pp. 1085-92. IEEE. New York, USA. June 27 - July 2, 2015. (acceptance rate: 15%) [PDF]
[ICPADS '15] Wei Zhang, Rui Fan, Fang Liu et al. “Energy Aware Caching.” IEEE International Conference on Parallel and Distributed Systems (ICPADS), pp. 473-80. IEEE. Melbourne, Australia. December 14-17, 2015. (Student Travel Award) [PDF]
[IC2E '14] Fang Liu, Wee Keong Ng, Wei Zhang et al. “Encrypted Set Intersection Protocol for Outsourced Datasets.” IEEE International Conference on Cloud Engineering (IC2E), pp. 135-40. IEEE. Boston, Massachusetts, USA. March 10-14, 2014. (acceptance rate: 20%) [PDF]
[CLOUD '14] Fang Liu, Wee Keong Ng and Wei Zhang. “Encrypted Scalar Product Protocol for Outsourced Data Mining.” IEEE International Conference on Cloud Computing (CLOUD), pp. 336-43. IEEE. Alaska, USA. June 27 - July 2, 2014. (acceptance rate: 19%) [PDF]
[GECCO '11] Maoguo Gong, Fang Liu, Wei Zhang et al. “Interactive MOEA/D for Multi-objective Decision Making.” Annual Conference on Genetic and Evolutionary Computation Conference (GECCO), pp. 721-8. ACM. Dublin, Ireland. July 12-16, 2011. (citations: 100+) [PDF]