About

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

Background

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.

Publications

Google Scholar

1. Implementing a fast unbounded quantum fanout gate using power-law interactions. Guo, Andrew Y., Abhinav Deshpande, Su-Kuan Chu, Zachary Eldredge, Przemyslaw Bienias, Dhruv Devulapalli, Yuan Su, Andrew M. Childs, and Alexey V. Gorshkov. Physical Review Research 4, no. 4 (2022): L042016.
2. Quantum routing with Teleportation Accepted talk at QCTIP 2022 Devulapalli, Dhruv, Eddie Schoute, Aniruddha Bapat, Andrew M. Childs, and Alexey V. Gorshkov. arxiv:2204.04185 (2022) (with Eddie Schoute, Aniruddha Bapat, Andrew Childs, and Alexey Gorshkov)
3. Toward a 2D local implementation of quantum LDPC codes. Noah Berthusen, Dhruv Devulapalli, Eddie Schoute, Andrew M. Childs, Michael J. Gullans, Alexey V. Gorshkov, and Daniel Gottesman. arXiv:2404.17676 (2024).
4. Efficiently verifiable quantum advantage on near-term analog quantum simulators. Zhenning Liu, Dhruv Devulapalli, Dominik Hangleiter, Yi-Kai Liu, Alicia J. Kollár, Alexey V. Gorshkov, and Andrew M. Childs. arXiv:2403.08195 (2024).

Projects

Deep Learning for Music Genre Classification

Professional Experience

Quantum Computing

IBM Research (Summer 2024) - Quantum Research Intern. At IBM, I am working on quantum algorithms and circuit synthesis.

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.

QCB

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.

Software Engineering

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.