Research Systems · Dashboard UX
AI Trading Research Lab
My Robinhood Trading Bots project, presented as a research environment for turning trading ideas into traceable experiments and human-reviewed evidence.
Research & decision support
Research / paper only
Disabled
Turn curiosity into a process.
The starting question was how to investigate trading ideas systematically, with enough context to understand what a result actually means. I directed a research lab that brings hypotheses, experiments, reports, and dashboards together so that progress and unresolved questions can be examined in one place.
Define what counts as evidence.
Through product direction and AI-assisted building, I shaped workflows for research orchestration, backtests, isolated observations, and paper validation. The system distinguishes demonstrations from market evidence and keeps data provenance, costs, and incomplete outcomes visible. A promising chart alone is not treated as proof of a successful strategy.
Design for review, including the gaps.
The dashboards connect research status with the controls that govern the next step. Missing data, unverified costs, and unfinished paper-trading lifecycles remain blockers rather than disappearing into a positive summary. The portfolio visual is an explanatory workflow, with no private account details or connection to the research services.
The result is a research capability.
This remains a partially verified research and paper-trading prototype, with live trading disabled. It does not establish profitability, investment returns, or readiness to trade real money. Its value as a case study is the design of a complex decision process: clear evidence boundaries, understandable reporting, and human review.