Professional Experience
Building intelligent systems and robust software across industries.
Accounting & Reporting Assurance Intern
Worked with fund-audit teams to map workflows and identify where automation could meaningfully reduce repetitive work. Designed and implemented a maintainable VBA pipeline that automated 30% of deterministic audit tasks, improving operational efficiency and allowing teams to spend more time on higher-value work.
Data Science Intern
Worked on a real-world road-sign detection problem involving large-scale map data, combining spatial, geometric, and relational signals to improve detection performance. Developed and deployed a neural network that increased accuracy from 82% to 98%, eliminating approximately 1,500 hours of manual fieldwork each week and improving data utilization across 5+ downstream OEM products.
City Scholar
Selected as 1 of 25 students for UIUC's premier academic-corporate fellowship connecting students with Chicago's technology ecosystem. Engaged with technology leaders, executives, and civic stakeholders across the cohort, developing a broader perspective on how technology, business, and organizational decision-making intersect.
Artificial Intelligence Intern
Spearheaded the development of an agentic synthetic data capability that served as a foundation for Onix's broader vision of an NLP-driven synthetic data platform. Designed simulation workflows capable of generating FHIR-compliant healthcare data spanning 20+ entities, translating a broader product vision into a technically executable capability. Worked across engineering leadership, developers, and prospective healthcare and insurance customers to navigate technical trade-offs, demonstrate the capability, and secure buy-in from 4 of 5 engineering leaders to advance it into the product roadmap.
Artificial Intelligence Lead Engineer
Led a 10-member engineering team delivering 8 emerging-technology solutions across AI and machine learning. Served as the primary point of contact between university stakeholders, my manager, and the engineering team, translating project requirements into technical direction and supervising solution architecture and execution. Supported engineers through technical roadblocks and held regular office hours to help the team move projects forward.
Artificial Intelligence Intern
Evaluated and benchmarked vehicle-tracking approaches for NEC's MiEye platform across 1,500+ traffic cameras in Delhi NCR, comparing technical performance and architectural implications. Synthesized the findings into a recommendation for a scalable architecture and presented the analysis to leadership, influencing approval and funding for a Phase 1 pilot projected to reduce compute costs by 40%.
Project Intern
Worked directly with the founder and Chief of Engineering at an early-stage financial technology company to develop a real-time trading analytics dashboard. Translated leadership requirements into a system for visualizing algorithmic trading activity and portfolio value fluctuations, while optimizing backend data processing to improve efficiency by 60% and enable faster analysis of high-volume trade activity.
Website Developer Intern
Partnered directly with the Director of the Lemann Center for Brazilian Studies as an embedded technical member of the program team. Translated stakeholder needs into website and UX improvements while proactively identifying opportunities to improve the user experience and digital presence. Also supported outreach and event initiatives promoting Brazilian studies and study-abroad opportunities in Brazil.
Software Engineering Intern
Led a 4-member team in developing an interactive demonstrator for India's Unified Logistics Interface Platform (ULIP), a government platform integrating 141 APIs across 13 ministries. Given an open-ended mandate to showcase the platform's capabilities, designed a use case demonstrating how multiple logistics services could work together rather than showcasing individual APIs in isolation. Worked directly with NEC leadership and government officials and conducted 10+ live demonstrations to communicate the platform's potential.
Research Assistant
Collaborated with Professor Ian Kash and another researcher on a multi-semester study evaluating election forecasting models using Brier scores and quantitative analysis. Replicated and evaluated models from FiveThirtyEight, The Economist, and other sources, exploring different approaches to measuring forecast accuracy and geographic variation in polling data. Continued the research across three semesters and prepared quantitative findings for presentation at the DIMACS 2024 conference.