ProofRound
Connecting résumé claims to project evidence, then turning the gaps into focused interview preparation.
Problem → implementation → evaluation
Data Scientist · Los Angeles
I’m Rui “Ricky” Sun, a UC Irvine applied mathematics graduate. I build and evaluate AI products and machine-learning systems—from interview preparation and nutrition tracking to conversational data analysis and optical design.
Applied AI · Product Engineering · Scientific ML · Model Evaluation
Open to early-career Data Scientist roles in Los Angeles, Orange County, and hybrid or remote teams.
Selected work
Connecting résumé claims to project evidence, then turning the gaps into focused interview preparation.
Problem → implementation → evaluation
A daily nutrition workspace for adults with ADPKD, designed around food records, individual targets, and care-team context.
Problem → implementation → evaluation
A conversational multi-table analysis workspace that keeps source tables, transformations, and results inspectable.
Problem → implementation → evaluation
Conditional generation of freeform optical patterns, evaluated with electromagnetic simulation rather than visual similarity alone.
10,000 simulated designs · APS poster
Featured research
My UC Irvine research connects conditional generative modeling with electromagnetic simulation for metasurface inverse design.
Explore the research ↗The generator is one part of the system. Evaluation design and optimization strategy determine whether an output becomes a useful design.
Experience
UC Irvine · Physics & Astronomy
Building data, model-training, and physics-evaluation workflows for metasurface inverse design.
ProofRound · Nepholio · Realy
Building user-facing AI workflows with traceable outputs, persistent context, and careful handling of incomplete data.
Beijing Jinye Paper Co., Ltd.
Worked on forecasting and business analytics in an operating company environment.
How I work
Frame the decision, metric, and constraints before choosing a model.
Create reproducible data and modeling workflows with clear assumptions.
Use controlled comparisons, diagnostics, and domain-specific evaluation.
Turn results and limitations into an action someone can defend.
Let’s talk
I’m open to early-career Data Scientist opportunities, research collaborations, and thoughtful technical conversations.