About
Whether I shall turn out to be the hero of my own life, or whether that station will be held by anybody else, these pages must show.
Charles Dickens, David Copperfield
I’m Dhruv Rawat. I am currently working as a quant developer working on financial pricing systems. Most of my time goes into writing C++ and making sure large-scale code runs fast, predictable, and correct under constraints.
I studied Computer Science and Economics at BITS Pilani, where I gravitated toward systems: compilers, parallel computing, and network programming. Along the way I also picked up a taste for research, publishing work on ML-inspired streaming algorithms and spending time in Advanced Data Analytics and Parallel Technologies research group, mentored by Dr. Jagat Sesh Challa.
These days I’m interested in the overlap between systems and machine learning: especially how compiler and runtime ideas can make ML workloads more efficient and reliable. Long term, I hope to keep building systems that matter, whether in research or industry.
To be precise, I am motivated by these two research questions:
How can we design systems that adapt automatically to heterogeneous hardware and dynamic workloads while guaranteeing correctness?
What architectural principles and cross-layer optimizations can bridge the gap between an algorithm’s theoretical efficiency and its deployed performance in a distributed environment?
Outside of work, I enjoy reading books, watching films, and following technology and history.
Visit coursework for more detailed information about the courses I did.
Visit coursework for more detailed information about the courses I did.
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Jagat Sesh Challa, Dhruv Rawat, Navneet Goyal, & Poonam Goyal AnyStreamKM: Anytime k-medoids Clustering for Streaming Data. 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan.
