Combining split and federated architectures for efficiency and privacy in deep learning. - Valeria Turina; Zongshun Zhang; Flavio Esposito; Ibrahim Matta (CoNEXT, 2020)

Anomaly detection for NILM task with Apache Flink. - Zongshun Zhang; Ethan Timoteo Go (DEBS, 2020)

Federated or Split? A Performance and Privacy Analysis of Hybrid Split and Federated Learning Architectures. - Valeria Turina; Zongshun Zhang; Flavio Esposito; Ibrahim Matta (CLOUD, 2021)

LIBRA: An Economical Hybrid Approach for Cloud Applications with Strict SLAs. - Ali Raza 003; Zongshun Zhang; Nabeel Akhtar; Vatche Isahagian; Ibrahim Matta (IC2E, 2021)

Privacy and Efficiency of Communications in Federated Split Learning. - Zongshun Zhang; Andrea Pinto; Valeria Turina; Flavio Esposito; Ibrahim Matta (IEEE Trans. Big Data, 2023)

PraxiPaaS: A Decomposable Machine Learning System for Efficient Container Package Discovery. - Zongshun Zhang; Rohan Kumar; Jason Li; Lisa Korver; Anthony Byrne; Gianluca Stringhini; Ibrahim Matta; Ayse K. Coskun (IC2E, 2024)

DRKF: Decoupled Representations with Knowledge Fusion for Multimodal Emotion Recognition. - Peiyuan Jiang; Yao Liu; Qiao Liu; Zongshun Zhang; Jiaye Yang; Lu Liu; Daibing Yao (CoRR, 2025)