I am an Associate Research Scholar at the Computer Science Department of Princeton University. In the past few years, I have been working on problems in broad areas of Computer Architecture Design and Memory Verification, and more recently on utilization of NISQ era Quantum Computer Architectures. At Princeton, I enjoy doing both hands-on research and advising graduate and undergraduate students.
Computer Architecture: I have been working on Computer Architecture Design for energy efficient and fast execution of memory bound applications such as Graph and Sparse Linear Algebra workloads together with graduate students Aninda Manocha and Marcelo Orenes Vera. I worked on developing automated compiler techniques that implements memory level parallelization for Graph Applications, developing efficient cycle accurate simulators for architecture design, designing hardware and programming model for data-local program execution for energy efficient Sparse workload execution. More recently I have been working on: (i) designing OS related software and hardware solutions to address memory latency bottlenecks in Graph and Sparse applications and (ii) designing wafer scale systems to process graph and sparse workloads.
Verification: Together with my collaborator Tyler Sorensen, I developed methodologies for statistical characterization of relaxed memory behavior observed through empirical memory testing, as well as efficient tuning of stress testing parameters for a given system. More recently I have been working on application of computer architectural verification techiques to Deep Neural Networks.
Quantum Computing: I am currently working on projects related to Variational Quantum Algorithms, Calibration of Quantum Systems and Statistical Properties of Measurement of Quantum Systems through various collaborations.
Data Science and Statistical Modeling: I am currently collaborating with Britt Hadar on studying the impact of risk appetite on biased representation of population subgroups in higher education and STEM.
I have a broad background spanning Computer Science, Data Science, Quantitative Finance (Statistical Arbitrage using Algorithmic Trading), Computational Biophysics (Ph.D) and Molecular Biology and Genetics (B.S.).
Finally, I am an avid follower of research on Privacy, Security and Verification of Machine Learning tools and the corresponding Information Technology Policy and am open to collaborations on these topics.