Giulio Zhou, Martin Maas. Learning on Distributed Traces for Data Center Storage Systems. Conference on Machine Learning and Systems (MLSys), 2021.

Giulio Zhou, Jacob Devlin. Multi-Vector Attention Models for Deep Re-ranking. Empirical Methods in Natural Language Processing (EMNLP), 2021.

Giulio Zhou, Martin Maas. Multi-Task Learning for Storage Systems. Machine Learning for Systems Workshop, NeurIPS 2019.

Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai. Accelerating Deep Learning by Focusing on the Biggest Losers. arxiv preprint arXiv:1910.00762

Christopher Canel, Thomas Kim, Giulio Zhou, Conglong Li, Hyeontaek Lim, David G. Andersen, Michael Kaminsky, Subramanya R. Dulloor. Scaling Video Analytics on Constrained Edge Nodes. SysML, 2019.

Giulio Zhou, Subramanya Dulloor, David G. Andersen, Michael Kaminsky. EDF: Ensemble, Distill, and Fuse for Easy Video Labeling. arXiv preprint arXiv:1812.03626

Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica. Clipper: A Low-Latency Online Prediction Serving System. NSDI, 2017.


TA for 15-849: Machine Learning Systems Seminar, Spring 2022}
TA for 10-701: Introduction to Machine Learning (PhD), Spring 2020
TA for CS 189: Introduction to Machine Learning, Fall 2016
TA for CS 61BL: Data Structures and Programming Methodology, Summer 2016
TA for CS 61B: Data Structures and Algorithms, Spring 2016


10-702: Statistical Machine Learning
10-703: Deep Reinforcement Learning
10-705: Intermediate Statistics
10-725: Convex Optimization
15-712: Advanced and Distributed Operating Systems
15-740: Computer Architecture
15-750: Graduate Algorithms
15-780: Graduate Artificial Intelligence

CS 280: Computer Vision
CS 194-26: Image Manipulation and Computational Photography
CS 189: Introduction to Machine Learning
CS 188: Introduction to Artificial Intelligence
CS 186: Introduction to Database Systems
CS 170: Efficient Algorithms and Intractable Problems
CS 168: Computer Networking
CS 162: Operating Systems and Systems Programming
CS 70: Discrete Math and Probability Theory
CS 61C: Machine Structures
CS 61BL: Data Structures and Programming Methodology
CS 61A: Structure and Interpretation of Programs
EE 126: Probability and Random Processes