Demo: real-time breath monitoring using wireless signals. - Fadel Adib; Zachary Kabelac; Hongzi Mao; Dina Katabi; Robert C. Miller (MobiCom, 2014)

Smart Homes that Monitor Breathing and Heart Rate. - Fadel Adib; Hongzi Mao; Zachary Kabelac; Dina Katabi; Robert C. Miller (CHI, 2015)

Capturing the human figure through a wall. - Fadel Adib; Chen-Yu Hsu 001; Hongzi Mao; Dina Katabi; Frédo Durand (ACM Trans. Graph., 2015)

Resource Management with Deep Reinforcement Learning. - Hongzi Mao; Mohammad Alizadeh; Ishai Menache; Srikanth Kandula (HotNets, 2016)

NUMFabric: Fast and Flexible Bandwidth Allocation in Datacenters. - Kanthi Nagaraj; Dinesh Bharadia; Hongzi Mao; Sandeep Chinchali; Mohammad Alizadeh; Sachin Katti (SIGCOMM, 2016)

Neural Adaptive Video Streaming with Pensieve. - Hongzi Mao; Ravi Netravali; Mohammad Alizadeh (SIGCOMM, 2017)

SageDB: A Learned Database System. - Tim Kraska; Mohammad Alizadeh; Alex Beutel; Ed H. Chi; Ani Kristo; Guillaume Leclerc; Samuel Madden 001; Hongzi Mao; Vikram Nathan (CIDR, 2019)

Variance Reduction for Reinforcement Learning in Input-Driven Environments. - Hongzi Mao; Shaileshh Bojja Venkatakrishnan; Malte Schwarzkopf; Mohammad Alizadeh (ICLR (Poster), 2019)

Learning Generalizable Device Placement Algorithms for Distributed Machine Learning. - Ravichandra Addanki; Shaileshh Bojja Venkatakrishnan; Shreyan Gupta; Hongzi Mao; Mohammad Alizadeh (NeurIPS, 2019)

Park: An Open Platform for Learning-Augmented Computer Systems. - Hongzi Mao; Parimarjan Negi; Akshay Narayan 001; Hanrui Wang 002; Jiacheng Yang; Haonan Wang; Ryan Marcus; Ravichandra Addanki; Mehrdad Khani Shirkoohi; Songtao He; Vikram Nathan; Frank Cangialosi; et al. (NeurIPS, 2019)

Learning scheduling algorithms for data processing clusters. - Hongzi Mao; Malte Schwarzkopf; Shaileshh Bojja Venkatakrishnan; Zili Meng; Mohammad Alizadeh (SIGCOMM, 2019)

Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning. - Ravichandra Addanki; Shaileshh Bojja Venkatakrishnan; Shreyan Gupta; Hongzi Mao; Mohammad Alizadeh (CoRR, 2019)

Explaining Deep Learning-Based Networked Systems. - Zili Meng; Minhu Wang; Mingwei Xu; Hongzi Mao; Jiasong Bai; Hongxin Hu (CoRR, 2019)

Neo: A Learned Query Optimizer. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Chi Zhang 068; Mohammad Alizadeh; Tim Kraska; Olga Papaemmanouil; Nesime Tatbul (Proc. VLDB Endow., 2019)

Cost-Guided Cardinality Estimation: Focus Where it Matters. - Parimarjan Negi; Ryan Marcus; Hongzi Mao; Nesime Tatbul; Tim Kraska; Mohammad Alizadeh (ICDE Workshops, 2020)

High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization. - Qing Feng; Benjamin Letham; Hongzi Mao; Eytan Bakshy (NeurIPS, 2020)

Learned garbage collection. - Lujing Cen; Ryan Marcus; Hongzi Mao; Justin Gottschlich; Mohammad Alizadeh; Tim Kraska (MAPL@PLDI, 2020)

Interpreting Deep Learning-Based Networking Systems. - Zili Meng; Minhu Wang; Jiasong Bai; Mingwei Xu; Hongzi Mao; Hongxin Hu (SIGCOMM, 2020)

Bao: Learning to Steer Query Optimizers. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Nesime Tatbul; Mohammad Alizadeh; Tim Kraska (CoRR, 2020)

Real-world Video Adaptation with Reinforcement Learning. - Hongzi Mao; Shannon Chen; Drew Dimmery; Shaun Singh; Drew Blaisdell; Yuandong Tian; Mohammad Alizadeh; Eytan Bakshy (CoRR, 2020)

Neural Rate Control for Video Encoding using Imitation Learning. - Hongzi Mao; Chenjie Gu; Miaosen Wang; Angie Chen; Nevena Lazic; Nir Levine; Derek Pang; Rene Claus; Marisabel Hechtman; Ching-Han Chiang; Cheng Chen; Jingning Han (CoRR, 2020)

Flow-Loss: Learning Cardinality Estimates That Matter. - Parimarjan Negi; Ryan Marcus; Andreas Kipf; Hongzi Mao; Nesime Tatbul; Tim Kraska; Mohammad Alizadeh (Proc. VLDB Endow., 2021)

Bao: Making Learned Query Optimization Practical. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Nesime Tatbul; Mohammad Alizadeh; Tim Kraska (SIGMOD Rec., 2022)