What we do?

We conduct research in two broad areas related to the Internet:

Intent-based and self-driving networks

We are designing computer networks of the future that are intent-based (i.e., network designs and configurations are automatically synthesized to provably meet higher level goals with respect to security, resilience and performance) and self-driving (i.e., networks driven by real-time analytics performed at line-rate leveraging programmable network hardware for security and performance). Our past work has made influential contributions in network verification (formally verifying network configurations), synthesizing network configurations (which has been deployed in production at AT&T), and new approaches to synthesizing enterprise networks from higher-level network-wide abstractions. Our research has involved collaborations with Meta, Microsoft and AT&T, and is of significant interest to industry.

ML-driven and multi-perspective Internet video delivery

We are optimizing Internet video delivery using ML techniques (such as causal reasoning), and are tackling challenges in delivering next generation video (such as 360 degree and volumetric video), which are not only bandwidth intensive but also latency sensitive, with high perceptual quality. Our past research has made important advances to the design of Adaptive Bit Rate (ABR) algorithms for Internet video streaming over variable Internet environments, developed systems that significantly reduce mobile Web latency, developed novel approaches to architect low-latency cloud applications, and has pioneered a peer-to-peer approach for live video broadcasting. We have extensively collaborated extensively with industry, including an active on going collaboration with Amazon Prime Video.

More about us?

The video below, and this slide deck present an overview of recent research in our group:

Background needed to work in Purdue ISL

Prospective students must ideally have a strong background in Computer Science or Computer Engineering with extensive programming (ideally systems programming) background. However, EE students with a willingness/ability to build strong systems programming skills are welcome. Since some of our research draws on cutting edge techniques in optimization, machine learning, and formal methods, students with an aptitude for math/theory with an interest in applications to real-world networking problems may also be a good fit. Students are not expected to have background in all areas at the start of their Ph.D, but successful students have an ability and willingness to develop the needed background for their research problem as their research evolves.

Our research has benefited by support from NSF, Cisco, Google, Meta, NetApp, AT&T, and Microsoft, and many of our projects have involved collaboration with these organizations. Many of the challenges we address are motivated by real-world experience, require insights into operations of networks at scale, and can have significant real-world impact. After completing a Ph.D, alumni of Purdue ISL are now working on cutting edge network infrastructure at places such as Meta, Google, AT&T, Bytedance, as well as in universities and Government Agencies. Purdue ISL has often involved undergraduate students, who have continued to pursue graduate studies in top universities, or gone on to good industry positions.

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