My life goal is to become great at a few things that are fulfilling, meaningful and fun. These are some of them.
Art runs in the family. Every painting in the home that I grew up in was either painted by my dad, crafted by my mom or penciled and watercolored by my sister or myself. This early exposure to practicing creativity had me designing and building things from a young age. Going from water colors and pencil art to a print magazine on art and design, and later, user interfaces and product experiences.
In highschool I founded a print magazine with over 30 artists and writers from around the world. We designed and published it for the better part of five years up until I went off to university. From there on, more of my core interests shifted onto programming, genetics and startups. My inner designer lives on as a foundational pillar in everything I do.
I started dabbling in basic programming shortly after I got my first computer at age 10. I remember building little applications in visual basic; notably, a token verification system that I could use to generate and verify serial keys for software I was yet to write. (I know, call it planning ahead 🤷.)
I got more serious about writing code when I wanted to build the things I designed. I picked up a few web languages at first, followed by Python, SQL, and some self-taught C in high school to eventually getting reasonably proficient at full-stack development and being able to take things from idea to design and live product.
My love for data science sprawled in several directions. As I pursued my specialization in Bioinformatics, I found myself interested in data analysis and got involved with several exciting real-world projects; notably, through maintaining and building several machine learning models used by the student’s council at Western University, and the Ontario Liberal Party respectively (no political affiliation in either case). To some degree, my interest in data science lead me to my first startup in university.
On the bioinformatics front, I worked on assembling and annotating the mitochondrial genome of H. Lacustris for my thesis and came up with some pretty cool ways to leverge the tech we use to deploy and scale web servers to run various search and analysis software for my genetics research at scale.
Much of my design and engineering output goes towards Clew, a startup I founded with my friend Haishan. So far, I’ve been the sole designer and developer for Clew and looking back to work done so far, it’s been a thrilling experience architecting the end-to-end development of Clew.
Clew might seem relatively straightforward at first, but it’s a neat piece of software that does quite a lot under-the-hood. To share a few, here’s a quick outline of the various components that make up Clew:
- Integration service; a single abstraction for utilizing data across integrations like Google Drive, Dropbox, GitHub, Figma, etc. It’s a serverless application written in PHP that can simultaneously search across dozens of integrations in seconds, milliseconds, if you take into account the caching layer that accounts for external latencies. The API even listens for updates on any resource it has access to; these can be used for consolidating notifications on the front-end.
- A beautiful front-end based on a blazing fast progressive web application (PWA) written in Next JS and deployed to serverless with CloudFront distributions close to all our core users. Almost all pages on Clew score a 100% performance score on Lighthouse.
- A REST backend that serves graph-like content among other resources and can manage, authorize, tag and keep track of any content. It facilitates a central repository for all your work—data from all your tools, in one place, in one unified, consistent and reliable API.
- All of this is continuously deployed such that I could go from saving code on my local desktop to fully deployed in a few minutes, with no human intervention. Almost all of the deployment environment is specified in code and deployed using several custom docker images.
Rainbow Six Siege is an online tactical shooter my friends and I play frequently. It’s also the only game most of us have played for over a 1000 hours.
While the learning curve was steep to begin, it’s now an activity we’ve enjoyed and socialized over for the last two years.
Here’s a neat little kill/death ratio vs time graph since I started. I’ve love seeing my reaction times visibly improve over time.
I learned to handle most cars my Dad owned for as long as my legs could reach the pedals, mostly just racing them up and down empty roads in private property—a very sandboxed environment, but one that I enjoyed a lot never-the-less.
It’s been a fascinating experience putting together my sim-racing rig so I can take part in online races and bring in a little more realism to a very fun activity.
I’ve loved seeing my reaction times improve over time, and the state of flow you get into midway through a race is pure meditation.