PopCorns: Power Optimization Using a Cooperative Network-Server Approach for Data Centers. - Bingqian Lu; Sai Santosh Dayapule; Fan Yao; Jingxin Wu; Guru Venkataramani; Suresh Subramaniam 001 (ICCCN, 2018)

Automating Deep Neural Network Model Selection for Edge Inference. - Bingqian Lu; Jianyi Yang 001; Lydia Y. Chen; Shaolei Ren (CogMI, 2019)

HolDCSim: A Holistic Simulator for Data Centers. - Fan Yao; Kathy Ngyugen; Sai Santosh Dayapule; Jingxin Wu; Bingqian Lu; Suresh Subramaniam 001; Guru Venkataramani (IISWC, 2019)

Poster: Scaling Up Deep Neural Network optimization for Edge Inference†. - Bingqian Lu; Jianyi Yang 001; Shaolei Ren (SEC, 2020)

A Note on Latency Variability of Deep Neural Networks for Mobile Inference. - Luting Yang; Bingqian Lu; Shaolei Ren (CoRR, 2020)

Scaling Up Deep Neural Network Optimization for Edge Inference. - Bingqian Lu; Jianyi Yang 001; Shaolei Ren (CoRR, 2020)

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search. - Bingqian Lu; Jianyi Yang 001; Weiwen Jiang; Yiyu Shi 001; Shaolei Ren (Proc. ACM Meas. Anal. Comput. Syst., 2021)

A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural Accelerators. - Bingqian Lu; Zheyu Yan; Yiyu Shi 001; Shaolei Ren (CoRR, 2022)

Improving QoE of Deep Neural Network Inference on Edge Devices: A Bandit Approach. - Bingqian Lu; Jianyi Yang 001; Jie Xu 001; Shaolei Ren (IEEE Internet Things J., 2022)

Towards Ultra-Efficient Machine Learning for Edge Inference - Bingqian Lu (2022)

CMDRL: A Markovian Distributed Rate Limiting Algorithm in Cloud Networks. - Lilong Chen; Xiaochong Jiang; Xiang Hu; Tianyu Xu; Ye Yang; Xing Li; Bingqian Lu; Chengkun Wei; Wenzhi Chen (APNet, 2024)

Hardware-Sensitive Fairness in Heterogeneous Federated Learning. - Zahidur Talukder; Bingqian Lu; Shaolei Ren; Mohammad Atiqul Islam (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2025)