Natansh Mathur
Senior R&D Scientist, Quantinuum
Singapore
Nationality: Indian
Hello! I am Natansh Mathur (Hindi: नतांश माथुर), a Senior R&D Scientist at Quantinuum in Singapore, working on quantum machine learning and optimisation algorithms.
Before Quantinuum, I spent six years at QC Ware in Paris, most recently as an Associate Staff Scientist, where I built quantum machine learning solutions for industrial partners across pharmaceuticals, finance, and automotive. Alongside this, I completed an industrial PhD (CIFRE) in Computer Science at IRIF, CNRS & Université Paris Cité, supervised by Prof. Iordanis Kerenidis, on the theory and applications of Hamming-weight preserving quantum neural networks. I hold a Master’s (MPRI) from Université Paris Cité and a B.Tech in Computer Science and Engineering from the Indian Institute of Technology, Roorkee.
My research focuses on quantum algorithms for machine learning: orthogonal and Hamming-weight preserving quantum neural networks, quantum vision transformers, Bayesian quantum neural networks, and their applications to real-world problems in medical imaging, anomaly detection, and financial forecasting.
news
| Aug 01, 2026 | Joined Quantinuum in Singapore as a Senior R&D Scientist, working on quantum machine learning and optimisation algorithms. |
|---|---|
| Jun 15, 2026 | Our paper “Scalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data Imputation” was accepted at IEEE QCE 2026, with a talk at IEEE Quantum Week 2026 in Toronto, Canada. |
| Sep 01, 2025 | Our paper “Bayesian Quantum Orthogonal Neural Networks for Anomaly Detection” was accepted at IEEE QCE 2025, with talks at QTML 2025 (Singapore) and IEEE Quantum Week 2025 (Albuquerque), and a poster at QCTiP 2025 (Berlin). |
selected publications
- IEEE QCEScalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data ImputationIEEE International Conference on Quantum Computing and Engineering (QCE), 2026
- IEEE QCEBayesian Quantum Orthogonal Neural Networks for Anomaly DetectionIn IEEE International Conference on Quantum Computing and Engineering (QCE), 2025
- npj QI
- Quantum