Computer Engineering @ University of Florida

Elan Loewinger

Software Engineering · AI/ML · Data Engineering

I'm a fourth year Computer Engineering student at the University of Florida graduating in December 2027 with interests in software engineering, artificial intelligence, and machine learning. I'm also pursuing a certificate in AI Fundamentals & Applications to complement my engineering coursework and hands-on experience.

I'm currently looking for opportunities in software engineering and AI/ML where I can continue tackling challenging problems, learning from experienced teams, and building technology with real-world impact.

Let's connect.

LinkedIn561-212-0470
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Elan Loewinger headshot

Selected work

Projects built to be inspected, not just listed.

Dive into each project to see the problem, system architecture, engineering decisions, and product demos.

Experience

Industry engineering and applied research.

Honeywell

May – Aug 2026

AI/ML Engineering Intern

  • Engineered Python and Databricks pipelines processing 1B+ new telemetry records daily across thousands of devices, completing ingestion, transformation, and analysis within 4 hours.
  • Ingested, normalized, filtered, and feature-engineered 50B+ records across multi-terabyte datasets, transforming raw device telemetry into structured datasets for predictive failure modeling.
  • Developed SQL workflows to extract, join, and validate large-scale modeling datasets, improving data consistency and reproducibility across the ML pipeline.
  • Built Databricks dashboards to analyze device telemetry, model outputs, failure predictions, and confidence metrics, enabling internal evaluation of a predictive capability that did not previously exist.
  • Co-developed the end-to-end data and analytics pipeline within a 2-person engineering team, contributing across data architecture, pipeline development, model evaluation, and analytics.

AltaScient

Jan 2026 – Present

Software Engineering Intern

  • Serve as primary developer of a customer-facing global trade and supply-chain analytics platform, architecting the React frontend, FastAPI backend, data infrastructure, analytics engine, and nearly 100 interactive visualizations.
  • Built Python data pipelines processing 100M+ records across 100+ datasets and hundreds of data sources, covering global trade flows from 2008–present across ~75 HS commodity codes.
  • Automated ingestion, normalization, and analysis workflows to update commodity databases in under 1 hour, reducing processing time by 50% through parallelization, vectorization, Parquet storage, and optimized computation.
  • Designed a precomputation and caching architecture for data-intensive statistical analyses, reducing customer-facing analytics load times from 10+ seconds to under 1 second.
  • Developed AI features including a daily LLM-powered current-events system that identifies, scores, and summarizes industry-relevant events, and a separate 175M-parameter Hugging Face chatbot running client-side to answer questions about platform functionality and data.

UF Machine Learning Research Lab

Aug 2026 – Present

Machine Learning Research Assistant

  • Conducting research evaluating AI models' ability to grade student work across varying rubrics against human graders.
  • Designing and executing experiments to measure grading accuracy, consistency, and agreement between AI models and human evaluators.
  • Analyzing experimental results and contributing to research methodology and co-authoring findings for publication.

UF Machine Learning Research Lab

Jan – Apr 2026

  • Independently developed a full-stack admissions platform using React, FastAPI, and SQLite to support structured evaluation of application materials.
  • Built asynchronous Python PDF ingestion, section detection, and text extraction pipelines to automatically identify and process relevant application sections.
  • Developed a React interface with click-to-grade PDF section viewing, real-time score persistence, and Excel export.
  • Architected FastAPI endpoints, relational data models, and asynchronous processing to manage data and PDF assets.

Boats Group

Jun – Aug 2025

  • Developed an AI-powered boat valuation tool using React, Tailwind, and OpenAI APIs for market estimates, image analysis, and confidence scoring.
  • Standardized metadata and data-decoration attributes to improve analytics consistency and user behavior tracking.
  • Authored documentation to streamline onboarding, environment setup, and deployment across multiple repos.
  • Improved UI/UX and navigation across multiple apps with reusable components and state-aware routing.

Personal Project

Nov 2025 – Present

AI-Powered Shopping Assistant

  • Built a SwiftUI iOS app for grocery lists, multi store item search, and price comparison with best store cart totals.
  • Developed a Python FastAPI scraping service with Playwright to search and normalize products across various retailers.
  • Designed a manager-worker architecture to run store-specific scrapers in parallel and isolate failures.