Troubleshooting blackbox SDN control software with minimal causal sequences. - Colin Scott; Andreas Wundsam; Barath Raghavan; Aurojit Panda; Andrew Or; Jefferson Lai; Eugene Huang; Zhi Liu; Ahmed El-Hassany; Sam Whitlock; Hrishikesh B. Acharya; Kyriakos Zarifis; et al. (SIGCOMM, 2014)

Scaling Spark in the Real World: Performance and Usability. - Michael Armbrust; Tathagata Das; Aaron Davidson; Ali Ghodsi 002; Andrew Or; Josh Rosen; Ion Stoica; Patrick Wendell; Reynold Xin; Matei Zaharia (Proc. VLDB Endow., 2015)

SLAQ: quality-driven scheduling for distributed machine learning. - Haoyu Zhang; Logan Stafman; Andrew Or; Michael J. Freedman (SoCC, 2017)

ReLAQS: Reducing Latency for Multi-Tenant Approximate Queries via Scheduling. - Logan Stafman; Andrew Or; Michael J. Freedman (Middleware, 2019)

Resource Elasticity in Distributed Deep Learning. - Andrew Or; Haoyu Zhang; Michael J. Freedman (MLSys, 2020)

VirtualFlow: Decoupling Deep Learning Model Execution from Underlying Hardware. - Andrew Or; Haoyu Zhang; Michael J. Freedman (CoRR, 2020)

Abstracting Systems Challenges from Distributed Deep Learning - Andrew Or (2021)

VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware. - Andrew Or; Haoyu Zhang; Michael None Freedman (MLSys, 2022)

TorchAO: PyTorch-Native Training-to-Serving Model Optimization. - Andrew Or; Apurva Jain; Daniel Vega-Myhre; Jesse Cai; Charles David Hernandez; Zhenrui Zheng; Driss Guessous; Vasiliy Kuznetsov; Christian Puhrsch; Mark Saroufim; Supriya Rao; Thien Tran; et al. (CoRR, 2025)