I am an assistant professor in computer science at UC Santa Barbara. I co-direct the Systems and Networking Lab (SNL).
As a systems researcher, I design and build systems that solve the real-world problems at the intersection of networking, internet measurements, and machine learning.
Join us in shaping a more equitable digital world! If you are interested in building systems for network measurements and management for a more inclusive digital future, come work with us. Please find more details about my research here.
- 🆕 In Search of netUnicorn: A Data-Collection Platform to Develop Generalizable ML Models for Network Security Problems, ACM CCS, 2023.
- 🆕 Decoding the Divide: Analyzing Disparities in Broadband Plans Offered by Major US ISPs, ACM SIGCOMM, 2023.
- Panakos: Chasing the Tails for Multidimensional Data Streams, ACM VLDB, 2023.
- AI/ML for Network Security: The Emperor has no Clothes, ACM CCS, 2022.
🏆 Best Paper Honorable Mention
🏆 IETF/IRTF Applied Networking Prize (ANRP)
- The Importance of Contextualization of Crowdsourced Active Speed Test Measurements ACM IMC, 2022.
🏆 Distinguished Paper Award (Long)
- Detecting Ephemeral Optical Events with OpTel, USENIX NSDI, 2022.
Deployed at Tencent
- An Effort to Democratize Networking Research in the Era of AI/ML, ACM HotNets 2019.
- Flexible and Scalable Systems for Network Management, Dissertation, Princeton University, 2018.
🏆 ACM Doctoral Dissertation Award Honorable Mention
- Sonata: Query-Driven Streaming Network Telemetry, ACM SIGCOMM 2018.
- iSDX: An Industrial-Scale Software Defined Internet Exchange Point, USENIX NSDI 2016.
🏆 USENIX NSDI Community Contribution Award
🏆 USENIX Best of the Rest
- SDX: A Software Defined Internet Exchange, ACM SIGCOMM 2014.
🏆 Internet2 Innovation Award
Please check this page for an extended list of publications.
- Trustee: A framework that cracks open decision-making for black-box ML models (for networks) using high-fidelity, low-complexity, and stable decision trees.
- BQT: A tool that queries broadband plan offerings from major ISPs in the US at street-level granularity.
- PINOT: A programmable data-collection infrastructure at UCSB to collect fine-grained (labeled) network data at scale.
- netUnicorn: A data-collection platform that simplifies collecting network data for different learning problems from diverse network environments.
As a junior researcher, it has been an absolute honor and privilege to get the opportunities to organize different workshops (and tutorials) on topics related to digital equity and self-driving networks.
- ACM SIGCOMM 2023 Tutorial: Closed-Loop ML (for Networks) Pipelines, Sep 2023 (upcoming)
- Bridging the Divide: Answering Internet Policy Questions with Cutting-Edge Network Measurement Algorithms, Datasets, and Platforms, June 2023
- ACM SIGMETRICS Workshop on Measurements for Self-Driving Networks, 2023, June 2023
- NSF Workshop on Internet Frontiers & Opportunities, Nov 2021
- NSF Workshop on NextG Security, Oct 2020
- NSF Workshop on Measurements for Self-driving Networks, Apr 2019
Aug 2023: Our paper, In Search of netUnicorn: A Data-Collection Platform to Develop Generalizable ML Models for Network Security Problems, got accepted at ACM CCS’23. Kudos to Roman for developing such an impressive and useful system! Please find more information about the project here.
June 2023: Udit Paul received the Computer Science Outstanding Publication Award. 🏆
June 2023: Udit Paul received the Computer Science Outstanding Dissertation Award. 🏆
May 2023: Our paper, Decoding the Divide: Analyzing Disparities in Broadband Plans Offered by Major US ISPs, got accepted at SIGCOMM’23. Kudos to Udit Paul for such an impressive work! Please find more information about our BQT tool here.
Jan 2023: Our paper, Panakos: Chasing the Tails for Multidimensional Data Streams, got accepted at VLDB’23. Kudos to Fuheng Zhao and Punnal Ismail Khan for their hard work and perseverance!
Jan 2023: Our project, Trustee, received the Applied Networking Prize (ANRP) from IETF/IRTF. Kudos to Arthur Jacobs and Roman Beltiukov for yet another recognition for their awesome work! 🏆
Nov 2022: Our paper, AI/ML for Network Security: The Emperor has no Clothes, received the Best Paper Honorable Mention at ACM SIGSAC Conference on Computer and Communications Security (CCS), 2022. It was rated as the best paper in the
Machine Learning and Securitytrack. Special congratulations to Roman Beltiukov and Arthur Jacobs! 🏆
Nov 2022: I had the privilege to visit Lawrence Berkeley National Lab (LBNL). Special thanks to Inder Monga for hosting me.
Oct 2022: I had the privilege to present the Trustee work at ETH Zurich. Special thanks to Laurent Vanbever for hosting me.
Oct 2022: Our paper, The Importance of Contextualization of Crowdsourced Active Speed Test Measurements received the Distinguished Paper Award (Long) at ACM SIGCOMM Internet Measurements Conference (IMC), 2022. Special congratulations to my student, Udit Paul! 🏆
June 2022: Sanjay Chandrasekaran received the Computer Science Outstanding Graduate Research Award. 🏆
June 2022: Rohan Bhatia received the Computer Science Outstanding Teaching Assistant Award. 🏆
June 2022: Chaofan Shuo received the prestigious Computer Science Outstanding Undergraduate Research Award. 🏆
Apr 2022: Congcong Miao (Tencent) will present our work on detecting ephemeral network events in optical transport network at NSDI 2022.
Feb 2022: I talked about our efforts to democratize networking research at Google’s Networking Research Summit.
Jan 2022: Sanjay Chandrasekaran received M-Lab’s Research Fellowship 2022. Sanjay will be using the programmable research infrastructure at UCSB to study the relationship between the quality of experience (QoE) for applications and various QoS metrics from the network. 🏆