I am a third year PhD student in the Computer Science Department at Princeton University where I work with Ravi Netravali. I am broadly interested in computer networks and systems. Recently, my work has involved improving the resource-efficiency, performance, affordability, and scalability of machine learning systems.
Prior to Princeton, I worked at the US Department of Defense in Fort Meade, MD. I received my bachelor's degree in computer science from New York University in 2019 where I worked with Anirudh Sivaraman and Srinivas Narayana from Rutgers University.
During the summer of 2022, I was an intern at Microsoft Research, Redmond where I was a part of the Networking Research Group.
MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations
Mike Wong, Murali Ramanujam, Guha Balakrishnan, Ravi Netravali
USENIX NSDI 2024
NetVigil: Robust and Low-Cost Anomaly Detection for East-West Data Center Security
Kevin Hsieh†, Mike Wong†, Santiago Segarra, Sathiya Kumaran Mani, Trevor Eberl, Anatoliy Panasyuk, Ravi Netravali, Ranveer Chandra, Srikanth Kandula († equal contribution)
USENIX NSDI 2024
Marvolo: Programmatic Data Augmentation for Deep Malware Detection
Mike Wong, Edward Raff, James Holt, Ravi Netravali
ECML PKDD 2023
Previous version in AI4Cyber/MLHat at KDD 2022
Synthesizing Safe and Efficient Kernel Extensions for Packet Processing
Qiongwen Xu, Michael D. Wong, Tanvi Wagle, Srinivas Narayana, Anirudh Sivaraman
ACM SIGCOMM 2021
Also accepted to the BPF & Networking Summit at LPC 2021
[ K2 webpage ]
Testing Compilers for Programmable Switches Through Switch Hardware Simulation
Michael D. Wong, Aatish Kishan Varma, Anirudh Sivaraman
ACM CoNEXT 2020
Switch Code Generation Using Program Synthesis
Xiangyu Gao, Taegyun Kim, Michael D. Wong, Divya Raghunathan, Aatish Kishan Varma, Pravein Govindan Kannan, Anirudh Sivaraman, Srinivas Narayana, Aarti Gupta
ACM SIGCOMM 2020