Physics • Scientific Software • Deep Tech

Tobias M. Kaufmann

Physicist and scientific software developer working across quantum sensing, nanofabrication, optical instrumentation, scientific computing, and AI-enabled physical systems.

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About

I am completing an M.Sc. in Physics at ETH Zurich and currently doing visiting research at Harvard University. My work sits at the interface of spin-defect-based quantum sensing, two-dimensional materials, nanofabrication, optical instrumentation, and scientific software.

I am especially interested in deep-tech problems where physics, software, and experimental systems meet, including semiconductor/metrology tooling, quantum sensing, advanced materials, and AI for physical systems.

Current work

Spin-defect sensing platforms for 2D quantum materials

At Harvard, I am working on sensing concepts for two-dimensional quantum materials using hBN defects, optical readout, ODMR, device design, and scientific Python modeling. The broader goal is to develop sensing approaches for fragile correlated electronic phases and nanoscale material systems.

  • Quantum sensing
  • hBN defects
  • ODMR
  • 2D materials
  • Scientific Python

Selected projects

View GitHub →

ODMR Simulation Framework

Python framework for simulating spin-defect ODMR and quantum sensing protocols, including field-dependent transitions, ensemble/single-defect regimes, and pulsed sequences such as Ramsey, Hahn echo, and XY8.

Python • NumPy/SciPy • Quantum sensing
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Scattering Analysis and Bootstrapping Tools

Research software for model fitting, bootstrapping, parameter estimation, uncertainty quantification, and scattering-data analysis workflows.

Python • Statistics • Model fitting
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Real-Time GIWAXS / XRD Analysis

Tools for real-time visualization and analysis of synchrotron scattering data during experimental campaigns, connecting raw detector outputs to interpretable plots and fitted parameters.

Python • Synchrotron data • Visualization
Repository →

Writing

I write occasional technical essays on mathematical physics, topology, quantum materials, AI-enabled physical systems, and deep-tech startup ideas.

Read on Substack →

Contact

For research, deep-tech, startup, or technical opportunities, feel free to reach out.

tkaufmann@fas.harvard.edu GitHub LinkedIn