Beñat Froemming Aldanondo

About Me

I am currently pursuing a master’s degree in Computer Science at the University of Minnesota – Twin Cities, with an expected graduation in May 2026. I earned my undergraduate degree in Data Science from the same institution. My goal is to make a meaningful impact through my work, and I am passionate about robotics, computer vision, artificial intelligence, data, and mapping.

Education

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University of Minnesota

Masters's in Computer Science, Computer Science & Engineering Department

September 2025 - May 2026

GPA: 4.0 / 4.0

Relevant Courses: Deep Learning, Computer Vision, Robotics, Intelligent Agents, VIS4AI, and ML for Healthcare.

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University of Minnesota

Bachelor's in Data Science, Computer Science & Engineering Department

September 2021 - May 2025

GPA: 3.75 / 4.0

Relevant Courses: Software Engineering, Data Structures & Algorithms, Computer and Database Systems, Project Management, Operations Research for Data Science, Data Mining, Machine Learning, Artificial Intelligence, and Natural Language Processing.

Skills

Python
Java
C/C++
SQL
ROS
OpenCV
Machine Learning
PyTorch
React.js
Linux

Languages

Basque
English
Spanish

Experience

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Software Engineer (Part-Time)

The Toro Company

Bloomington, MN

September 2025 - March 2026

  • Built a full-stack telematics dashboard for commercial engineering diagnostics and deployed it using Azure DevOps.
  • Developed backend services in Python for data extraction using SQL and the Snowflake API.
  • Implemented the frontend with React and Vite, featuring interactive data visualization and live mapping tools.
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    Engineering Data Analytics Intern

    The Toro Company

    Bloomington, MN

    May 2025 - August 2025

  • Increased telematics data accuracy by 55% by creating automated Python tests for the machine-to-cloud pipeline.
  • Researched and presented AI integration strategies to the executive board to enhance product safety, reliability, and durability.
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    Undergraduate Research Intern

    Minnesota Robotics Institute

    Minneapolis, MN

    September 2024 - December 2024

  • Applied reinforcement learning to optimize train speed control and maximize rail utilization.
  • Conducted research under Professor Maria Gini and presented results at the AAAI-25 conference.
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    Research Intern

    National Science Foundation - Lawrence Tech University & Michigan State University

    Detroit, MI

    May 2024 - August 2024

  • Reduced vehicle idling time at intersections by 75% by developing adaptive speed-control algorithms.
  • Designed and deployed lightweight vision-based lane-following systems on electric vehicles using ROS, Python, OpenCV, and Scikit-Learn.
  • Prototyped a low-cost roadside unit for vehicle-to-infrastructure communication of real-time traffic signal states.
  • Led a cross-functional research team, managed GitHub workflows, and co-authored two papers accepted at top-tier engineering
    • conferences.

    Contact

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