Maahir Garg work experience. What I've worked on, roughly in order.

Trying to catch cheating in coding assessments without accusing anyone innocent, which turns out to be a statistics problem more than an engineering one. The most useful thing I built was the test that showed a promising 0.778 AUROC was indistinguishable from chance, and a plain lookup of which question a student got beat it anyway.

Teaching CS3230, the algorithms course I took myself as a student, and CS3263, foundations of AI. Four semesters in, students rate the teaching 4.8 out of 5, and it got me onto the NUS Honour List of Student Tutors.

Two summers advising student teams from architecture to release. In 2025 every team I advised hit its target grade.

Six months building AI tooling for a team where the usual shortcuts, like pointing Copilot at a problem, aren't allowed. I'm prouder of the guardrails I built to check every action an agent takes than of the agents themselves, and of a Snowflake-and-SharePoint pipeline that turned hunting for audit evidence into something close to instant.

Hand and eye tracking on Apple Vision Pro and iPhone for stroke rehabilitation, in collaboration with Apple. I built the visionOS side and the iPhone companion app, and it was tested with real clinicians and real patients. A paper is in preparation and a patent application is in progress.

Built the data pipelines for a study of what actually predicts a good Stack Overflow answer, since upvotes and being marked accepted turn out not to be the same signal.

A summer in Jakarta building dashboards and databases a non-technical ops team used every day, plus some SEO and performance work on the side.

Supported NUS IT's bug-bounty and security programme, including vendor negotiation and running security-awareness sessions for people who mostly wanted to get back to work.

An economics paper had a deadline that wasn't moving and a mountain of citation data to collect by hand. I wrote a script instead, and it saved about 520 hours.

An air-quality study needed years of pollutant readings from a system that assumed a human would copy them out by hand. I wrote the scraper so nobody had to.

Ran sessions for a large AR/VR motion-sickness study with Meta, which mostly meant calibrating headsets and reassuring people that feeling slightly sick was, unfortunately, the data.