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Welcome back, everyone! 👋
Welcome (back) to my newsletter! It’s been a while since I wrote my last newsletter - I’ve been up to a bunch of cool things over this summer and I’m excited to share major updates! I decided against writing a July newsletter since I wanted to spend time prioritizing my internship and I wanted to give a high-level and deeper overview of my life in a summer newsletter :) I’m going to be making some changes regarding the timings of my newsletter, but I’ll outline that later in the newsletter. Let’s dive into what I’ve been up to this summer!! This summer has been nothing short of amazing, I interned at Interac, did many AI research sprints, did a ton of reading and I’m preparing for my freshman year at the University of Toronto in the fall. Those are just a couple of the highlights, let’s get into the thick of this newsletter :)
Interning at Interac 🏦
Most of my time over the summer has been spent at Interac. In my previous newsletter, I mentioned that I would be starting my role as a research intern at Interac. My term only just recently ended and my experience has been nothing short of amazing. It’s not every day a teenager gets to work at the biggest Canadian Interbank network. Reflecting back on my term, I honestly couldn’t have asked for a better internship experience. My role as a research intern involved expanding insights that we received from the Signals Exchange Forum (SEF) Event at the end of June. The big idea behind the SEF event was to answer this question:
What may drive significant change in Canadian academia in the next 10 years and how might this impact Canada’s future and beyond academia?
These insights guided my research in the Academia sector and I spent the majority of my term taking those insights and converting them into Foresight Scenarios that reflect a potential future for Canadian Academia. The other piece of research I worked on was a research piece that exploits inefficiencies in the Canadian banking system with emerging technologies, specifically Artificial Intelligence.
Overall, these 8 weeks were full of new learnings & growth and it was an extremely valuable experience that I’ll hold close to my heart. My most memorable moment throughout the entire internship was the Interac Scavenger Hunt we had - it was a great bonding experience and built some meaningful relationships throughout the scavenger hunt.
I want to extend my gratitude to the entire Interac team for being really welcoming and helping me transition smoothly. I want to give a huge shoutout to Marc Folch for being a great mentor and helping in accelerating my growth throughout the summer.
AI Research Sprints 🔬
During my off hours in the summer, I spent my free time diving deep into topics that I’m interested in. Over the last year or so, I’ve immersed myself in the AI/ML space, reading, writing & building cool projects with the many unique subsets of Artificial Intelligence. My curiosity drove me to do in-depth and technical research in AI and I wrote about my learnings on medium. I looked into a bunch of cool AI topics and they all definitely have the potential to drive significant innovative change, but I primarily focused on 2 key subsets of Artificial Intelligence, Natural Language Processing & Federated Learning.
Natural Language Processing 🗣
The first research sprint that I did was in the domain of computational linguistics, Natural Language Processing (NLP). NLP is on the more linguistics side of AI, so its applications include Chatbots, Language Translators, Website Summarizers, etc. The main function of NLP is to help computers understand words and sentences that are written in a language that a human understands. The entire process of researching Natural Language Processing involved watching some introductory videos to reading advanced research papers that broke down the NLP pipeline. I loved this entire process and I converted all these inputs into an article on medium.
In my article, I break down the subsets of NLP and how each step in the NLP pipeline works and its importance. Feel free to check it out :)
Natural Language Processing Article
Federated Learning 💾
The second and most recent research sprint I completed was in a new and recently researched subset of Machine Learning, Federated Learning (FL). Federated learning is a new subset of AI that is being researched currently, it was initially discovered a couple of years back, in 2017. To give a rough overview of Federated Learning, it’s essentially decentralized machine learning. The purpose/goal behind FL was to protect the privacy and data of users by exploiting decentralized data and decentralized computing power — providing a more personalized experience by keeping user data confidential. In other words, Federated Learning is a Machine Learning method that is used to train algorithms on decentralized edge devices while keeping the data local to each device.
In my article, I break down Federated Learning; how it compares to centralized machine learning; how federated learning works; FL frameworks; and its future applications. Check it out in my article below 😁👇
Current Read: You’re Too Good to Feel This Bad 📖
Another one of my core focuses over the summer has been self-growth and optimizing to be the best version of myself. As such, I’ve recently made it a personal goal to read books to get a better understanding of the importance of completing day-to-day tasks to a high standard. And so, recently, I’ve started to read You're Too Good to Feel This Bad by Nate Dallas. Despite only being halfway through the book, I’ve gained unique insights on how to break away from cultural norms and deviate away from the mediocre middle. I would definitely recommend reading this book as it provides a brand new perspective to understanding and living life; it has already inspired me to establish changes in my day-to-day life & routine.
Summer 2022 Highlights
What lies ahead… 😤
Now that my summer has come to an end, I’ve got some big plans for the future and I’m so excited to share all that with everyone. There’s going to be a lot happening and I’m so pumped for the fall to start!!
🚨 IMPORTANT 🚨:
Before diving into the big plans, I wanted to say that I’m going to be moving away from monthly newsletters to bi-monthly newsletters (once every 2 months). With my freshman year starting and committing to different things, I found that I could best display my growth through bi-monthly newsletters.
Now that we’ve gotten that out of the way, let’s jump into what the next chapter looks like for me 😤
Growth Fellowship at Coda 📈
Earlier in the summer, I applied for a Fellowship at Coda and I recently got accepted into their Fall Cohort. I’m super pumped to start as a growth fellow and get involved with the team and learn from their mentors!
Coda is a Silicon Valley Unicorn that was founded in 2014. Its primary function is to serve as an all-in-one doc that brings words, data, and teams together.
I’ve had the opportunity to meet with alumni and some of the current team and I’m thoroughly looking forward to getting started and adding as much value as I can. My fellowship starts in September and I’ll post an update about the progress of my fellowship in my next newsletter, keep an eye out for that 😁
Technical Writer at University of Toronto Machine Intelligence Team (UTMIST)
Following that, I committed myself to the University of Toronto Machine Intelligence Team as a technical writer. UTMIST is an organization that focuses on Machine Learning & Artificial Intelligence - researching new AI advancements and building out impactful projects. My research sprints over the summer prompted me to apply as a technical writer and now I’ll be writing technical AI articles every month about recent ML/AI papers so make sure to look out for those on my LinkedIn! This is an exciting opportunity and I can’t wait to write out some technical articles and assist in building out some cool and unique AI projects! Stay in tune for updates in my next newsletter 😉
Goals 📝
Wow, that was a long newsletter and there was a lot to go through, but now that we’re at the end, in typical newsletter fashion, I’m going to sign off by highlighting some things to look out for during my next newsletter 😁
Starting my freshman year @ University of Toronto for Computer Science 🎓
Research in Data Science x Medical Imaging under a professor @ UofT 🧑🏽🔬
Building out some AI projects 🤖
Writing in-depth & technical AI articles about recent papers and advancements ✍🏼
That’s all from me! I hope you all had an amazing summer! Thank you for spending time to read my newsletter and I’ll see everyone in the next edition! If you missed the important announcement earlier, I’ll be doing bi-monthly newsletters so I’ll see everyone at the end of October! :)
If you enjoyed this, feel free to share and subscribe to my newsletter by putting your email down below 👇. Thanks for reading, I’ll see you soon!
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