Francis Lau

Designing and implementing an AI-enhanced authorization insights platform analyzing historical utilization management and policy data to generate predictive approval insights and operational decision support for clinical workflows Building full-stack analytics and dashboard solutions using Python, .NET, Azure, Snowflake, Power BI, and OpenAI APIs; developing backend services, scalable data pipelines, and dashboards for healthcare reporting and model explainability Collaborating with utilization management engineers, architects, and cross-functional stakeholders to integrate generative AI capabilities, enhance authorization analysis workflows, and deliver production-oriented clinical technology solutions

Software Engineering Intern - Humana - Louisville, KY

(2026-05)

• Designing and implementing an AI-enhanced authorization insights platform analyzing historical utilization management and policy data to generate predictive approval insights and operational decision support for clinical workflows
• Building full-stack analytics and dashboard solutions using Python, .NET, Azure, Snowflake, Power BI, and OpenAI APIs; developing backend services, scalable data pipelines, and dashboards for healthcare reporting and model explainability
• Collaborating with utilization management engineers, architects, and cross-functional stakeholders to integrate generative AI capabilities, enhance authorization analysis workflows, and deliver production-oriented clinical technology solutions

AI Engineer Intern - Crypt0Nest AI - Remote

(2026-01 - 2026-04)

• Built a modular portfolio analytics platform aggregating market data and on-chain metrics; designed scalable data ingestion and feature pipelines for trading signals, enabling portfolio analytics and signal generation
• Implemented a production-grade backtesting engine with strict lookahead-bias controls over 50K+ records; optimized data storage using Parquet for efficient querying and reproducibility, reducing end-to-end latency by ~35%
• Added logging, monitoring, and error handling to improve system reliability and observability

AI Research Engineer Intern - Handshake AI - Remote

(2025-12 - 2026-04)

• Developed a Python-based evaluation framework to benchmark model outputs across 1,000+ test cases; designed extensible scoring pipelines for correctness and reasoning validation in CS and math tasks
• Built a structured feedback processing system for 500+ edge cases using JSON-based annotations and automated parsing pipelines; integrated outputs into model training workflows, reducing hallucinations by 25% across evaluation benchmarks

Quantitative Analyst Intern - Six Point Capital - Dallas, TX

(2025-09 - 2025-12)

• Designed and implemented a large-scale risk analytics engine processing 2M+ borrower records; optimized data pipelines and vectorized transformations in Pandas/NumPy to improve runtime efficiency and ensure reliable batch processing
• Built a standalone backend service to map model outputs to cashflow projections; implemented a Monte Carlo simulation framework supporting 1,000+ scenarios with <3% error vs historical data
• Established end-to-end model validation pipelines leveraging statistical metrics (Brier score, c-index) and historical benchmarks; documented system architecture, data flows, and deployment workflows to support production maintenance

BSc. - Computer Science w/ Mathematics Minor - Cornell University, College of Engineering (2028-06)