I earned my Ph.D. in Quantum Computation and Information at the Department of Computer Science, Thapar Institute of Engineering & Technology, Patiala, India in 2020. After my Ph.D., during the pandemic, I worked as a Postdoctoral fellow in Prof Daniel Braun Group at the University of Tubingen, Germany. I’m currently working as a Postdoctoral Research Associate in the School of Electrical and Computer Engineering at Purdue University under Prof. Alam’s group and the Department of Chemistry under Prof. Kais group.

I am dedicated to the field of quantum technologies, focusing on education, public awareness, and contributing to cutting-edge research. My previous work has involved quantum computational models and their applications in Biology, Chemistry, and Tensor Network Theory. Currently, I am concentrating on quantum optimization using resilient algorithms within the financial sector. My research is centered on near-term quantum computing techniques, specifically variational quantum algorithms and quantum/classical machine learning. I am exploring their applications across various engineering disciplines, and more recently, in healthcare, manufacturing, and finance. Currently, I am working on privacy-preserving quantum federated learning algorithms for heterogeneous data, further advancing the intersection of quantum computing and data privacy in the healthcare sector.

My research interests lie in the fields of Quantum Computation, Quantum Algorithms, Privacy-preserving Federated Learning, Quantum/classical Machine Learning, Medical imaging, Cheminformatics, Tensor network theory, Theory of Computation, and Formal Languages. Skilled in programming languages with experience using quantum computing frameworks such as Qiskit, Cirq, Pennylane, and CUDA Quantum.