I build infrastructure for AI agents and quantitative systems.
My work is centered on one question:
How do we make autonomous systems reliable enough to operate in complex, high-stakes engineering environments?
I focus on modular system design, evaluation, monitoring, replay testing, and operational safety. My current projects involve AI agent workflows, quant research infrastructure, market data pipelines, and execution systems.
- Agent workflow design
- Tool-use architecture
- Evaluation and scoring frameworks
- Instruction-following and compliance measurement
- Human-in-the-loop control
- Observability, auditability, and replay
- Backtesting architecture
- Market data pipelines
- Orderbook analysis
- Signal generation and execution diagnostics
- Risk controls and system monitoring
- PostgreSQL-based research data models
- Linux / WSL / remote development environments
- Modular service design
- CI, testing, logging, metrics, rollback, and reproducibility
- Systems programming, numerical computing, and research tooling
- Rust
- C / C++
- OCaml
- SystemVerilog
- Python
- Bash
- R
- C# / .NET
- q / kdb+
- Go
- TypeScript
- Chinese
- English
- German
I study Condensed Matter Physics and Algebraic, Differential Topologuy at UC Berkeley.
I am also a classical musician and have professional experience in the German legal field.
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I love driving my old Jeep into untouched wilderness—deserts, forests, and coastlines—with my dog, a vintage large-format camera, and my diving gear (without my ThinkPad laptop)
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I am currently building a hybrid wheeled quadruped robot, which I hope will be able to carry 100 kg of diving equipment for me across rocky reefs. I am also modifying my Choptima CCR and developing a high-performance diver propulsion vehicle.
Please reach me through GitHub.