PhD Student at UMD
I’m a PhD student in Physics at the University of Maryland, College Park. My research interests are mainly in quantum algorithms and complexity theory. At UMD I have been working on quantum walk algorithms, unitary synthesis and state preparation, entanglement dynamics, and efficient classical verification of quantum computation. I’m also interested in both quantum and classical machine learning. I’m fortunate to be advised by Professor Alexey Gorshkov and Professor Andrew Childs.
My studies at UMD are supported by the NSF Graduate Research Fellowship.
Contact: here, ddhruv@umd.edu
I completed my undergrad at UC Berkeley in 2019 with a B.A. in Physics and Computer Science.
While at Berkeley, I worked with Professor Birgitta Whaley towards using tensor networks for Quantum Machine Learning, and implementing our tree tensor network models on Rigetti’s Quantum Computer. I also did research in experimental particle physics with the ATLAS collaboration under Professor Marjorie Shapiro, where I worked on projects involving new inner detector designs for the LHC as well as searches for Dark Matter candidate particles.
Deep Learning for Music Genre Classification
IBM Research (Summer 2024) - Quantum Research Intern. At IBM, I worked on fermionic encodings and fault-tolerant compilation.
Zapata Computing (Summer 2022) - Quantum AI Research Intern. At Zapata I worked on a project related to mitigation of Barren Plateaus in Quantum Neural Networks.
I am the founder and former president of Quantum Computing @ Berkeley, an undergraduate club aiming to spread quantum computing knowledge and connect industry, academia, and students. I also created and taught a DeCal (student run course) on quantum computing in Fall 2018.
In Summer 2017, I interned at Sonos on the Partner Integrations team, working on app development across Android, iOS, and Windows. In Summer 2018, I interned at Amazon on the AWS Rekognition team, where I worked on developing pipelines for different face detection and recognition models.