PARS: A Uniform and Open-source Password Analysis and Research System. - Shouling Ji; Shukun Yang; Ting Wang 006; Changchang Liu; Wei-Han Lee; Raheem A. Beyah (ACSAC, 2015)

Using GIDL mechanism for low-power consumption and data retention time improvement in a double-gate nanowire TFT 1T-DRAM with Fin-Gate and Pillar-Body structure. - Wei-Han Lee; Jyi-Tsong Lin; Yu-Chun Wang; Po-Hsieh Lin; Chien-Chia Lai; Yong-Huang Lin; Tin-Chun Chang (ASICON, 2015)

Multi-sensor Authentication to Improve Smartphone Security. - Wei-Han Lee; Ruby B. Lee (ICISSP, 2015)

Implicit Authentication for Smartphone Security. - Wei-Han Lee; Ruby B. Lee (ICISSP (Revised Selected Papers), 2015)

Implicit Sensor-based Authentication of Smartphone Users with Smartwatch. - Wei-Han Lee; Ruby B. Lee (HASP@ISCA, 2016)

Implicit Smartphone User Authentication with Sensors and Contextual Machine Learning. - Wei-Han Lee; Ruby B. Lee (DSN, 2017)

Sensor-Based Implicit Authentication of Smartphone Users. - Wei-Han Lee; Ruby B. Lee (DSN, 2017)

Quantification of De-anonymization Risks in Social Networks. - Wei-Han Lee; Changchang Liu; Shouling Ji; Prateek Mittal; Ruby B. Lee (ICISSP, 2017)

How to Quantify Graph De-anonymization Risks. - Wei-Han Lee; Changchang Liu; Shouling Ji; Prateek Mittal; Ruby B. Lee (ICISSP (Revised Selected Papers), 2017)

Secure Pick Up: Implicit Authentication When You Start Using the Smartphone. - Wei-Han Lee; Xiaochen Liu; Yilin Shen; Hongxia Jin; Ruby B. Lee (SACMAT, 2017)

Blind De-anonymization Attacks using Social Networks. - Wei-Han Lee; Changchang Liu; Shouling Ji; Prateek Mittal; Ruby B. Lee (WPES@CCS, 2017)

Inferring Smartphone Users' Handwritten Patterns by using Motion Sensors. - Wei-Han Lee; Jorge Ortiz 001; Bongjun Ko; Ruby B. Lee (ICISSP, 2018)

Time Series Segmentation through Automatic Feature Learning. - Wei-Han Lee; Jorge Ortiz 001; Bongjun Ko; Ruby B. Lee (CoRR, 2018)

Exact Incremental and Decremental Learning for LS-SVM. - Wei-Han Lee; Bong Jun Ko; Shiqiang Wang 001; Changchang Liu; Kin K. Leung (ICIP, 2019)

Acoustic anomaly detection system: demo abstract. - Jae-wook Ahn; Keith Grueneberg; Bong Jun Ko; Wei-Han Lee; Eduardo Morales; Shiqiang Wang 001; Xiping Wang; David Wood (SenSys, 2019)

MOPT: Optimized Mutation Scheduling for Fuzzers. - Chenyang Lyu; Shouling Ji; Chao Zhang 008; Yuwei Li; Wei-Han Lee; Yu Song; Raheem Beyah (USENIX Security Symposium, 2019)

Model Pruning Enables Efficient Federated Learning on Edge Devices. - Yuang Jiang; Shiqiang Wang 001; Bong Jun Ko; Wei-Han Lee; Leandros Tassiulas (CoRR, 2019)

User Authentication and Security Vulnerabilities Using Smartphone Sensors and Machine Learning - Wei-Han Lee (2019)

Neuraltran: Optimal Data Transformation for Privacy-Preserving Machine Learning by Leveraging Neural Networks. - Changchang Liu; Wei-Han Lee; Seraphin B. Calo (DSN (Supplements), 2020)

Understanding the Security Risks of Docker Hub. - Peiyu Liu 003; Shouling Ji; Lirong Fu; Kangjie Lu; Xuhong Zhang 002; Wei-Han Lee; Tao Lu; Wenzhi Chen; Raheem Beyah (ESORICS (1), 2020)

NeuralFP: Out-of-distribution Detection using Fingerprints of Neural Networks. - Wei-Han Lee; Steve Millman; Nirmit Desai; Mudhakar Srivatsa; Changchang Liu (ICPR, 2020)

Rim: Offloading Inference to the Edge. - Yitao Hu; Weiwu Pang; Xiaochen Liu; Rajrup Ghosh; Bongjun Ko; Wei-Han Lee; Ramesh Govindan (IoTDI, 2021)

UNIFUZZ: A Holistic and Pragmatic Metrics-Driven Platform for Evaluating Fuzzers. - Yuwei Li; Shouling Ji; Yuan Chen; Sizhuang Liang; Wei-Han Lee; Yueyao Chen; Chenyang Lyu; Chunming Wu 001; Raheem Beyah; Peng Cheng 001; Kangjie Lu; Ting Wang 006 (USENIX Security Symposium, 2021)

Enhancing Robustness in Federated Learning by Supervised Anomaly Detection. - Pengrui Quan; Wei-Han Lee; Mudhakar Srivatsa; Mani B. Srivastava (ICPR, 2022)

A Large-Scale Empirical Study on the Vulnerability of Deployed IoT Devices. - Binbin Zhao; Shouling Ji; Wei-Han Lee; Changting Lin; Haiqin Weng; Jingzheng Wu; Pan Zhou 001; Liming Fang 001; Raheem Beyah (IEEE Trans. Dependable Secur. Comput., 2022)

Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms. - Tianshu Zhang 001; Changchang Liu; Wei-Han Lee; Yu Su 001; Huan Sun 001 (ACL (1), 2023)

Model Pruning Enables Efficient Federated Learning on Edge Devices. - Yuang Jiang; Shiqiang Wang 001; Víctor Valls; Bong Jun Ko; Wei-Han Lee; Kin K. Leung; Leandros Tassiulas (IEEE Trans. Neural Networks Learn. Syst., 2023)

GneissWeb: Preparing High Quality Data for LLMs at Scale. - Hajar Emami-Gohari; Swanand Ravindra Kadhe; Syed Yousaf Shah; Constantin Adam; Abdulhamid Adebayo; Praneet Adusumilli; Farhan Ahmed; Nathalie Baracaldo Angel; Santosh Borse; Yuan Chi Chang; Xuan-Hong Dang; Nirmit Desai; et al. (CoRR, 2025)