Zach Wang
PhD Researcher @ UCL · he/him
Quantitative research systems, made visible.
Quantitative research systems, machine learning infrastructure, and AI-assisted research orchestration.
As a researcher, I am interested not only in the outcomes of quantitative research, but also in the process that produces them. Robust research requires transparent methodology, rigorous validation, and evidence that remains visible throughout the investigation.
To support this philosophy, I built Zeto, an LLM-assisted quantitative research platform that brings together machine learning, systematic experimentation, validation diagnostics, and AI-assisted orchestration in a single reproducible environment. The objective is not simply to generate results, but to make the research process itself observable, explainable, and repeatable.
Explore the Architecture section to learn how Zeto is designed. Visit the Research section to see a complete quantitative investigation and its supporting evidence. Explore Orchestration to see how AI can accelerate research workflows while maintaining research integrity and human judgement.
A validation-first quantitative research environment combining systematic experimentation, machine learning, and AI-assisted research orchestration.
Zeto combines deterministic quantitative research infrastructure with AI-assisted orchestration. Research execution, validation, and evidence generation remain reproducible and human-governed, while AI assists with planning, interpretation, and iterative investigation.
- Intent Parser
- Workflow Router
- Config Synthesiser
- Human Approval
- Data Acquisition
- Feature Engineering
- Signal Research
- Machine Learning
- Portfolio Construction
- Walk-Forward Validation
- Regime Analysis
- IC Diagnostics
- Drift Detection
- Failure Visibility
- Reports
- Diagnostics
- Figures
- Registries
- Provenance Records
- Context Builder
- Failure Detection
- LLM Review
- Iteration Proposal
- Experiment Draft
- Intent Parser
- Workflow Router
- Config Synthesiser
- Human Approval
- Data Acquisition
- Feature Engineering
- Signal Research
- Machine Learning
- Portfolio Construction
- Walk-Forward Validation
- Regime Analysis
- IC Diagnostics
- Drift Detection
- Failure Visibility
- Reports
- Diagnostics
- Figures
- Registries
- Provenance Records
- Context Builder
- Failure Detection
- LLM Review
- Iteration Proposal
- Experiment Draft