I am a Researcher at JPMorgan Chase, serving as the Executive Director - Applied Research Director within the Global Technology Applied Research center. At this position, I lead the Quantum-Inspired Algorithms group, which develops advanced classical methods for big-data analytics, machine learning (including LLMs), and constrained optimization problems. Previously, I have worked as the quantum algorithms developer at the French quantum startup Pasqal, and at PayPal.

My Journey

  1. Applied Research Director (Executive Director)

    2024 - PresentJPMorganChase

  2. Applied Research Lead (Vice President)

    2022 - 2023JPMorganChase

  3. Senior Quantum Algorithms Researcher

    2021 - 2022Pasqal

  4. Quantum Algorithms Researcher

    2021 - 2022PayPal

  5. Post-doctoral Researcher in Quantum Computing

    2019 - 2021University of Edinburgh

  6. Ph.D. Researcher in Quantum Computing

    2015 - 2018Telecom ParisTech

  7. Bachelor's & Master's in Physics

    2009 - 2014Indian Institute of Technology (IIT) Kanpur

Research Interests

Quantum-Inspired Algorithms

My recent research focuses on quantum-inspired classical algorithms that leverage ideas from quantum computation to design efficient classical methods for large-scale problems:

  • Randomized NLA techniques for big-data analytics: fast provable clustering [1], coreset selection and regression [2], [3].
  • Classical techniques for fast discrete optimization [4].
  • Tensor-based techniques for high-dimensional integration and LLM compression [5].
  • Machine Learning / LLM: classical algorithmic techniques for explainability, compression, and fine-tuning [6].

Quantum Research

I have a diverse research experience across both theoretical and experimental aspects of quantum computing:

  • Quantum Algorithms: algorithms for machine learning — both variational [7], [8] — and provable methods based on quantum linear-algebra subroutines [9], [10], [11]; as well as optimization via QAOA [12], [13].
  • Privacy in Machine Learning using Quantum: frameworks for privacy in distributed (federated) learning [14], [15], [16].
  • Quantum Information and Cryptography: quantum vs classical communication complexity [17]; quantum money [18]; authentication [19]; and quantum cloning [20].
  • Quantum Advantage Demonstrations: quantum photonic state systems used show advantage in communication complexity [21], and efficient verification of non-interactive zero-knowledge proofs [22]. More recently, I have contributed to quantum advantage demonstrations in optimization [23], certified randomness generation [24], and advantage in streaming settings [25].

Press Coverage of Research Works