Unbounded Barrier-Synchronized Concurrent ASMs for Effective MapReduce Processing on Streams. - Zilinghan Li; Shilan He; Yiqing Du; Senén González; Klaus-Dieter Schewe (ABZ, 2021)

APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Trung-Hieu Hoang; Minseok Ryu; Eliu A. Huerta; Volodymyr V. Kindratenko; Jordan D. Fuhrman; Maryellen L. Giger; Ryan Chard; Kibaek Kim; Ravi K. Madduri (e-Science, 2023)

An Efficient Generative Data Imputation Toolbox with Adversarial Learning. - Yangyang Wu; Xiaoye Miao; Zilinghan Li; Shilan He; Xinkai Yuan; Jianwei Yin (ICDE, 2023)

FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler. - Zilinghan Li; Pranshu Chaturvedi; Shilan He; Han Chen; Gagandeep Singh; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (ICLR, 2024)

Obstacle-Aware UAV Swarm Deployment for User Coverage Using Deep Reinforcement Learning. - Shilan He; Kyo Hyun Kim; Matthew Caesar 001; Jae Kim; Josh D. Eckhardt; Greg Kimberly (MILCOM, 2024)

Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework. - Zilinghan Li; Shilan He; Ze Yang; Minseok Ryu; Kibaek Kim; Ravi K. Madduri (CoRR, 2024)

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2. - Zilinghan Li; Shilan He; Pranshu Chaturvedi; Volodymyr V. Kindratenko; Eliu A. Huerta; Kibaek Kim; Ravi K. Madduri (Comput. Sci. Eng., 2024)