06 · About
A bit more
I started with HTML and CSS at sixteen, moved to C and C++, and never really stopped. I studied biomedical engineering in Tabriz, then came to Montréal for a master's in telecommunication, where I spent two years putting people in VR headsets and measuring what happened to them.
Since then the work has moved toward AI products. Language models, retrieval, voice. But the underlying question hasn't changed much: how do you make a machine that a person can work with, and trust?
I have deliberately worked across niches: clinical research, smart devices at Huawei, legal tech, retrieval over large document corpora. I think you should keep putting yourself somewhere unfamiliar. It is the fastest way to hit problems you have no template for, which is the only way I know to actually learn something.
I like problems where the stakes are real. Health, accessibility, tools that save someone hours. And I like finishing things, which turns out to be the rarer skill.
I'm in Montréal, I write in English and Persian, and I'm open to what comes next.
01 · Work
Where I've built things
Seven roles, mostly in health AI and applied research. The common thread is getting models out of notebooks and into production.
- Early-stage work on an AI product for legal teams. Too soon to say much publicly.
- Same pattern as last time: build the thing, put it in front of people, keep what works.
- Built the AI pipelines and data infrastructure behind the platform, and tuned LLM performance in production.
- The AI features cut churn by 10% and lifted feature adoption by 25%. Deployed on Azure and AWS EC2.
- Shipped a full-stack AI product on my own: web platform, voice AI, audio features, plus RAG pipelines and a citation engine over a large document corpus.
- Made every technical call, then sold the company and the technology behind it.
- Built the data pipelines and AI infrastructure, and put deep learning models into production for medical use, including Parkinson's detection.
- Ran the stack on GCP Cloud Run and AWS EC2.
- Led the AI work for precision medicine in the mental health department at the Lady Davis Institute.
- Took models from research question to something clinicians could actually use.
- Built AI and IoT features for phones, homes, and cars, and cut system latency by 20%.
- Prototyped ideas, demoed them, and contributed to patents.
- Built a virtual companion for patients in Unity, running on the ChatGPT API.
- Improved speech recognition and text-to-speech, and engagement went up 55%.
- Worked on DREAM BIG, a consortium of 10+ institutions studying how genes, prenatal adversity, and early childhood environment shape children's wellbeing.
- Built federated-learning decision support systems and hardened the models to keep sensitive data safe.
Record
Education and awards
Education
2021 – 2022
MSc, Telecommunication
INRS, University of Quebec
Thesis: Enhancing motor imagery-based brain-computer interface efficacy using multisensory virtual reality training.
2016 – 2020
BSc, Biomedical Engineering
University of Tabriz
Where the signal processing and medical side of my work started.
Awards
- Outstanding Team AwardHuawei Canadian Research Centre
- MEITAMcGill University
- Graduate Excellence FellowshipMcGill University
- International Student Tuition ExemptionUniversity of Quebec
- 1st place, Popular Vote, and Best SSVEP GameBCI Game Jam
05 · Publications
Peer-reviewed work
A systematic review, a multisensory study, an instrumented headset, and the sound-detection work behind ImmerseGuard.
Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management
2024Sensors
Optimizing Auditory Immersion Safety on Edge Devices: An On-Device Sound Event Detection System
2024Odyssey
Multisensory Immersive Experiences: A Pilot Study on Subjective and Instrumental Human Influential Factors Assessment
2022QoMEX
Towards instrumental quality assessment of multisensory immersive experiences using a biosensor-equipped head-mounted display
2023Quality and User Experience
04 · Skills
What I work with
Tools I've actually shipped with, not a list I collected.
Machine learning
LLMs and RAG
Data and storage
Shipping and ops
Product surface
07 · Contact
Say hello
If you're building something in AI and want another pair of hands on it, or you just want to talk about a problem, reach out on LinkedIn or GitHub. I answer.