Karan Kumar Gangadhar

I am a second-year Computer Science graduate student at New York University, Courant Institute of Mathematical Sciences. I am currently focused on my Master’s Thesis research on Programmable Computer Networks and Compiler Optimisation under Prof. Anirudh Sivaraman.

My primary research interests are parallelization, program and compiler optimization, and computer networks. I work extensively in the field of programmable network switches, focusing on building highly optimized compilers and transpilation tools for network programs. I am also interested in general language-agnostic task parallelization techniques using thread-level tools.

Previously, I worked as a software engineer at Goldman Sachs, where I focused on building low-latency Java-based backend microservices that served critical in-house financial software powering the asset management business. I also built a reliability monitoring service to ensure the active working of day-to-day services that financial analysts use. I also interned at Cisco Systems, being identified as the best Summer Intern, where I built a fully automated unit-testing framework integrated with the control plane software of the IOS-XR operating system, reducing the human effort and failure rates of essential software.

Even earlier, I worked as a Summer Research Intern at the Microsoft Innovation Lab during my undergraduate studies at PES University, where I worked on a Customer Feedback Model to analyze the customer review data of a company and help identify critical issues based on their severity, built using NLP and Sentiment Analysis models.

When not working, I love geeking out over Formula 1, Cricket, MMA, and other sports. And not to forget, I make a mean Masala Dose and a filter coffee to go along with it!

You can read about my current and published research on my projects and publications pages!