I've worked across the entire stack: dockerizing frontend & backend applications, setting up AWS VMs (SSL certificates, NGINX configurations etc.), building React components & managing states with Redux, implemented and maintained Python server housing ML APIs, designed (under guidance of CTO) and implemented ML APIs for entity extraction and summarization of clinical data
I have a B.Eng in Biomedical Engineering and since graduating, I have worked: as an Analyst in one of the top cancer institutes in the world (Princess Margaret) and a Sales Engineer/R&D Engineer at a medical device startup (tool to help surgeons with hip replacement surgeries).
Currently, I'm working through the fast.ai lectures with the goal of creating a 'smart compose' for clinical notes.
- I've been tinkering with some form of technology from an early age. My earliest memories include:
-- making custom Neopets pages for myself and friends
-- turning my Sony Vaio into a Hackintosh - it worked fairly well except for the WiFi module which was solved by attaching a USB WiFi adapter.
- I have prototyped gadgets with Arduinos and even built a 2-lead ECG as University project.
- My capstone project was an attempt to sort a given audio clip into one of four categories; I was responsible for building the classifier in MATLAB. This project peaked my interest in Machine Learning.
- I have since worked as an Analyst in one of the top cancer institutes in the world (Princess Margaret), a Sales Engineer at a medical hardware startup.
- In the last 1.5 years, I've worked as a software engineer (amongst other hats) at a healthcare startup that was focused on automating clinical workflows; of note: we attempted to generate clinical notes from patient-physician conversations. I was heavily involved in all aspects of the project from implementing the voice functionality to prototyping with large language models and conducting interviews with end-users etc.
- Currently, in my free time, I'm following the fast.ai lectures with the goal of creating a 'smart compose' for clinical notes - an idea that's stuck with me from my discussions with our end users.
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Location: Toronto, Canada
Remote: I'm open to remote & in-person opportunities in the Toronto region.
What are your thoughts on using Google Docs to prototype this? Correct me if I'm wrong in my logic. You're looking for a way to link end results of your analysis to a 'Word' document that will auto-populate with each re-run. The physicians etc. want a 'clean' manuscript that mimics graphs in the format of the preferred paper + has version control.
It's really too bad Mendeley butchered public groups feature, it could've helped solve the "are there any more readings about this topic that I'm missing" problem. You're preaching to the choir re: latex.
If you had a choose 1 issue that really grinds your gears, which one would it be?
a side-note - Have you tried a solution like Evernote to organize your thoughts?
A software engineer with a background in Biomedical Engineering. I've spent the past year & half working in the healthcare technology space. I've tackled a range of tasks, from implementing voice features in React applications to configuring NGINX and setting up VMs on AWS.
One of my proudest accomplishments has been developing a Python backend that can extract clinical entities from text and summarize conversations using Large Language Models like GPT-J, GPT-3 and Macaw.
With a passion for tinkering with computers and electronics, I made the decision to transition into programming during the pandemic. Since then, I've been eager to learn, take on new challenges and expand my skillset.
I'm seeking a full-time Junior Software Engineering role, where I can continue to grow as a developer and make a meaningful impact.
Remote: Yes + In-Person in Toronto, Ontario region
Technologies: Python, JavaScript, TypeScript, React, Docker, FastAPI
Resume: https://standardresume [dot] co/r/zardarkhan
Email: zardar [dot] khan @ icloud.com
Who am I?
~1.5 years of experience as a software engineer.
I've worked across the entire stack: dockerizing frontend & backend applications, setting up AWS VMs (SSL certificates, NGINX configurations etc.), building React components & managing states with Redux, implemented and maintained Python server housing ML APIs, designed (under guidance of CTO) and implemented ML APIs for entity extraction and summarization of clinical data
I have a B.Eng in Biomedical Engineering and since graduating, I have worked: as an Analyst in one of the top cancer institutes in the world (Princess Margaret) and a Sales Engineer/R&D Engineer at a medical device startup (tool to help surgeons with hip replacement surgeries).
Currently, I'm working through the fast.ai lectures with the goal of creating a 'smart compose' for clinical notes.
P.S. I'm open to internships as well.