I'm a Computer Science student at The University of Texas at Austin (class of 2027) with a minor in social and behavioral sciences. I'm especially interested in machine learning and computer vision.
Outside of the classroom, I spent four years on the Texas Men's Swim and Dive team, contributing to back-to-back national championships and four conference championships. I am projected to be the first four-year varsity athlete at UT to earn a B.S. in Computer Science. My athletic background shaped how I work: with discipline, consistency, and continuous improvement under pressure.
In my free time, I enjoy cooking, spending time with friends, working out, and exploring new places.
B.S. Computer Science — Minor: Social & Behavioral Sciences — Expected May 2027 · Full detail on the resume page.
Honors
High school
Aliant+ — Remote — Summer 2026
TexBioMed — Austin, TX — Summer 2026
Private Triathlon Coaching — Austin, TX — 2024 – Present
UT Men’s Swim & Dive — Austin, TX — 2022 – 2026
Longhorn Aquatics — Austin, TX — 2025 – Present
Athletic highlights (NCAA championships, Olympic Trials, etc.) are listed on the resume PDF.
Click 'Learn more' on any project to see a detailed case study.
Built Pintos educational operating system: a pedagogical project for understanding core OS concepts on 80x86 architecture. I developed and refined kernel threads, virtual memory management, user program execution, and file system features.
GitHub unavailable — source cannot be published under course academic integrity policies.
Built a machine learning pipeline to predict whether FAA-reported wildlife strikes would cause aircraft damage using historical aviation incident data. Focused on imbalanced classification, feature engineering, and improving balanced accuracy across damage classes.
I competed as an elite swimmer while balancing a rigorous course load at The University of Texas at Austin. More than anything, that experience taught me how to operate in high-performance environments built around accountability, repetition, and measurable results.
I bring that same mindset to engineering. I’m drawn to systems that need to perform reliably under pressure, where iteration, feedback, and disciplined execution matter more than flashy ideas. The process of improving software feels very familiar to improvement in sport: measure honestly, identify weaknesses quickly, and compound small gains over time.
The fastest way to reach me is email. You can also find me on GitHub, LinkedIn, and Instagram.
mhhaskal@gmail.com