Industry
Alongside my doctoral work I have spent time building quantum software in a startup setting and working on quantitative research in finance. This page collects that side of my work; the academic record lives on the Publications and CV pages.
FieldQuantum — Founding Partner, Head of Quantum Algorithms
Feb 2026 – Aug 2026
FieldQuantum is a venture-backed quantum computing startup of roughly 50 staff, which has raised ¥245M from investors including Sequoia China and InnoAngel. I joined as a founding partner and built the quantum algorithm team from scratch, owning its technical roadmap, hiring, and delivery.
What I worked on
- fieldqkit — shipped an open-source Python SDK that connects users to quantum hardware: a unified interface across multiple cloud platforms, with automatic transpilation, error mitigation, and variational algorithms built in.
- Large-scale molecular simulation — led a programme simulating systems of up to 12,000 atoms, combining tensor-network and classical-quantum hybrid methods.
- Real-time quantum error correction — led the effort behind the company’s whitepaper on the real-time QEC system stack (arXiv:2605.30765), which sets out the decoding-latency and control-stack requirements for closing the error-correction loop within a device’s coherence budget.
- Automated ansatz discovery — designed an evolutionary search over variational ansätze built on AlphaEvolve, replacing hand-designed circuit families with an automated search procedure.
Optiver — Quantitative Research Intern
Offer accepted; internship summer 2027
The offer followed PhD QuantFocus, a selective Optiver programme covering mental arithmetic, options and contract pricing, market-making strategy design, and factor research.
In the programme’s trading-strategy competition — a timed build ranked against the full cohort across nine parameter regimes — I placed first, finishing roughly 30% ahead of second place and submitting the only entry that was profitable in every regime.
Technical Toolkit
- Languages — Python (expert)
- Numerical & optimisation — large-scale linear algebra, tensor contraction, MILP (Gurobi), Monte Carlo, stochastic optimisation
- Machine learning & data — PyTorch, NumPy/SciPy, evolutionary search