About

A more personal view of the work, the direction I am heading, and the kind of systems I want to build next.

About me

Research-minded engineering, with a bias for clarity and delivery.

I'm Ganesh Chandrasekar, an AI/ML engineer with a Master of Computer Science from Concordia University. My thesis, Evidence-Grounded Biomedical Question Answering: Design, Analysis, and Evaluation, brought together large-scale retrieval, reranking, LLM inference, and evaluation. I defended it in August 2026.

I do my best work where research depth and engineering constraints both matter. Alongside AI research, I have built GCP-backed APIs and product workflows, so I am comfortable carrying systems from modeling and measurement through backend services and user-facing interfaces.

Retrieval and RAGLLM evaluationApplied AI engineering
EXPERIENCE

Snapshot from my CV

A short version of the roles that shaped how I work.

Research Assistant
CLaC Lab, Concordia University · Montreal, Canada
Sep 2023 - Aug 2026
Teaching Assistant
Concordia University · Montreal, Canada
Sep 2024 - May 2026
Solution Developer
OrangeScape Technologies Pvt Ltd · Chennai, India
Jul 2022 - Aug 2023
Software Engineering Intern
Basik Marketing Pvt Ltd · Chennai, India
May 2022 - Jul 2022
View full experience timeline →
APPROACH

How I like to work

The kind of teams, problems, and engineering habits that bring out my best work.

Measure first. I care about systems that are strong enough to be useful outside a paper, not just impressive in isolation.
Bridge research with interfaces. I like building evaluation views, tooling, and APIs that make model behavior easier to inspect.
Ship clearly. The strongest work usually comes from turning complex pipelines into something another person can actually trust and use.
LINKS

Where to find me

The fastest routes to my work, writing, and contact details.

Portrait of Ganesh Chandrasekar
Profile
Ganesh Chandrasekar
AI/ML Engineer · MCompSc
Based in
Montreal, QC, Canada

Research-minded engineering work, with strong delivery and evaluation habits.

Current status
Thesis defended · August 2026

Open to full-time AI/ML, NLP, and information retrieval roles.