Benjamin Panet

Benjamin Panet

Undergraduate Student
Email: ben.panet@mail.utoronto.ca
GitHub: https://github.com/Uruk-Haiku
Department of Computer Science

Education

HBSc – Trinity College, University of Toronto (Sept. 2021 – present)

  • Computer Science / Evolutionary Biology double major
  • Completed Arts & Science Internship Program with 8-month industry software development co-op
  • Former speaker for the Trinity College Literary Institute

Skills & Qualifications

  • Experienced with Python, Ruby, R, MATLAB, C, C++, Java, SQL, HTML & CSS.
  • Comfortable with Linux, Bash, Makefiles, Vim, Git and command-line work.
  • Experienced with Windows, PowerShell and Microsoft Office Suite (Word, Excel, Powerpoint).
  • Trained with handling lab animals.
  • Working proficiency in French.
  • NLS-certified lifeguard & certifying with NAUI as open-water SCUBA diver.

Experience & Projects

Software Developer Co-op @ Clio – Cloud Based Legal Technology (Summer + Fall 2024)

  • Created and solved Jira tickets, discovered and tracked bugs, reviewed and shipped pull requests to production Ruby on Rails codebase.
  • Worked on a new service to abstract common database call, providing centralized implementation, safer database handling, analytics and foundation to add caching.
  • Performed database migrations, wrote admin reports, and fixed bugs in both back and frontend.

Summer Student @ Sunnybrook Research Institute (Summer 2023)

  • Wrote MATLAB scripts to facilitate selection and analysis of regions of interest on ultrasound scans.
  • Created a networking system between embedded Windows environments on research ultrasound machines and team computers to allow efficient file transfer.
  • Prepared material for a new website in WordPress for the lab, with a focus on maintainability.
  • Anaesthetized mice and maintained their health and vital signs during ultrasound and fluorescent imaging experiments.

Other projects

  • Full literature review for a prospective project on Drosophila and Arabidopsis transcriptomic analysis in hypercapnic environments.
  • Implemented comparative machine-learning analysis of Wikipedia articles to assess quality using a variety of methods and metrics.
  • Developed a terminal application to rapidly find and display solutions to Word Hunt (an iMessage word game) with an innovative UI method to display results.
  • Analyzed geolocation data from across Toronto to examine the relationship between restaurant density and COVID-19 cases.