
University of Toronto CS | Automotive SWE Intern @ Qualcomm, Prev @ Hitachi Rail
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fluidity
December 3, 2024 – January 10, 2025
(unfinished and abandoned) Cross-platform and real-time 2D fluid simulator, rendered in OpenGL, with fluid computations done through CUDA.
View Projectzirconium
August 5, 2024 – Present
DLL-injectable internal game cheat for Plutonium BO2 zombies
View Projectpixelify
December 11, 2023 – August 5, 2024
GUI image processor that applies convolution kernels (Gaussian blur, Laplace operators, etc) to images using CUDA.
View Projectroad-ai
April 29, 2023 – May 10, 2023
Implementing artificial intelligence to detect collisions at traffic intersections.
View Projectautomated-ucheck
February 24, 2022 – July 26, 2024
Automates UCheck at the University of Toronto.
View Projectinjector
July 11, 2021 – February 12, 2025
Barebones command-line DLL injector for Windows.
View Projectassault-cube-external-trainer
July 5, 2021 – September 19, 2021
External trainer made in C++ that utilizes winapi to read/write process memory. Can change health, ammo, armour, and teleport to co-ordinates.
View Projectgoodlife-booking-alerter
August 23, 2020 – December 25, 2024
A bot that checks for free sessions at Goodlife Fitness.
View Projectpocket-wiki
August 2, 2020 – August 2, 2020
A Spigot plugin in 1.16 that displays the wiki page of an item when held in hand.
View ProjectCultural Fit Analysis
The candidate's project portfolio is diverse in terms of technologies (C++, Java, Python, JavaScript, CUDA) and problem domains (game cheats, fitness bots, AI, image processing, fluid simulation). However, the projects are exclusively personal and do not provide insight into collaboration or working within a team. The target role is 'Frontend Developer', but the majority of projects lean towards backend, systems, or scientific computing, with only one project mentioning JavaScript/CSS. This indicates a potential misalignment with the specific frontend focus, though the breadth of technical skills suggests adaptability.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are primarily technical and personal, offering no insight into collaboration, communication, or problem-solving in a team context.