Building the quantum analogue of OpenAI Gym — and making Mumbai a global hub for Quantum-Assisted Physical AI.

• 🧠 Senior Quantum ML Engineer @ BosonQ Psi (BQP) — Full-time research on LEO satellite trajectory propagation using Physics-Informed Neural Networks (PINNs), including Quantum-Assisted PINNs (QAPINNs), uncertainty quantification, and transfer learning across orbital regimes.
• 🏗️ Founder & Lead Developer @ QRL — Building the open-source qrl-qai SDK, a quantum analogue of OpenAI Gym, built on PennyLane and PyTorch. Long-term vision: making Mumbai a global hub for Quantum-Assisted Physical AI.
• 🎙️ Podcast Host of Quantum Podcast with Jay Shah — featuring researchers, founders, and recruiters across the quantum computing ecosystem.
• 🎤 Speaker at 15+ institutions including IIT Delhi, IIT Guwahati, IIT Jodhpur, BITS Pilani, Arizona State University (USA), NIT Agartala, K. J. Somaiya College of Engineering, Pillai College of Engineering, GIET University, and more.
• 🏅 IBM Certified Associate Developer – Quantum Computation
• ✍️ Published science fiction writer with an interest in humanoid robotics and the future of physical AI.

The quantum analogue of OpenAI Gym, built on PennyLane and PyTorch.

The SDK provides a standardized interface for training classical and quantum reinforcement learning agents on quantum computing environments. v1.0.0 ships with:

• Environments: BlochSphereV0, BlochSphereV1, CompilerV0, ErrorChannelV0, ExpressibilityV0, ProbabilityV0
• Algorithms: ValueIteration, QValueIteration, REINFORCE (+ DQN variants, PPO, A3C, SAC in v2.x roadmap)
• Full tutorial notebooks, test suites, a no-code Streamlit app, and Lightning Studio templates.

Multi-document Agentic RAG system for quantum computing, showcased in Indian Quantum Community programs.

If you find qrl-qai useful for your research or learning, consider supporting the project:

"The intersection of quantum mechanics and machine learning isn't just a research area — it's the next frontier of physical intelligence."