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Research Engineer @ SMU-Quantum I build research software, educational resources, and computational experiments across quantum algorithms, applied AI, numerical methods, and high-performance scientific workflows.
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I work on the bridge between theory and implementation: quantum-classical algorithms, machine learning for scientific problems, optimization methods, and technical education. I care about clear explanations, reproducible notebooks, and code that makes advanced ideas easier to test and teach.
- Education: M.S. Physics and Data Science, IISER Mohali
- Current focus: AI-assisted scientific workflows, quantum optimization, and research tooling
- Website: monitsharma.github.io/portfolio
| Area | Scope |
|---|---|
| Quantum computing | QAOA, VQE, quantum circuits, quantum algorithms, and near-term quantum workflows. |
| Quantum machine learning | Quantum kernels, data re-uploading, quantum CNNs, noisy-device experiments, and QML tutorials. |
| Optimization | Hybrid quantum-classical solvers, numerical optimization, portfolio problems, routing, and combinatorial methods. |
| AI for science | Tool-using AI systems for reading, coding, testing, evaluation, and research acceleration. |
| Scientific computing | Numerical linear algebra, computational physics, high-energy physics simulations, CUDA, and performance-aware Python/C++ workflows. |
| Project | Description |
|---|---|
| Learn Quantum Computing For Free | Curated free resources for quantum computing, math, physics, and supporting foundations. |
| Quantum Machine Learning on Near-Term Quantum Devices | QML projects covering classification, quantum kernels, quantum CNNs, and applied near-term experiments. |
| Learn Quantum Machine Learning | Hands-on notebooks for learning quantum machine learning through code. |
| Quantum Finance and Numerical Methods | Python resources for finance, numerical methods, and optimization-oriented workflows. |
| Numerical Linear Algebra | Notebook-based material for linear algebra, numerical methods, and computational problem solving. |
| Quantum Codebooks | Walkthroughs and code notebooks for quantum algorithms and online quantum codebook exercises. |
| Quantum Classroom | Open learning material for quantum computing, built as a structured classroom-style resource. |
Quantum: Qiskit PennyLane Cirq QuTiP Amazon Braket pytket D-Wave Ocean
AI / ML: PyTorch TensorFlow scikit-learn MLX Transformers
Languages: Python C++ C Rust CUDA Java JavaScript
Systems: Linux Docker Git Jupyter VS Code
- Medium - technical notes on quantum computing, machine learning, and scientific computing.
- Quantum Classroom - structured quantum computing tutorials and learning resources.
- Portfolio - selected work, writing, and research background.
Email | LinkedIn | X / Twitter | Medium | YouTube | LeetCode