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You Need to Meet: Brooke Joseph, an Innovator Passionate About AI and Privacy-Preserving Technology

You need to meet Brooke Joseph, a The Knowledge Society (TKS) alumna and current Computer Science student at the University of Waterloo, specializing in federated learning and data privacy. Brooke’s ambitious and impactful projects span multiple focus areas and disciplines, though her most notable and recent project explores using Brain-Computer Interfaces and Artificial Intelligence for Bipolar Disorder. Brooke loves math and has pioneered projects in TensorFlow Federated, Raspberry Pi simulations, and Convolutional Neural Networks (CNNs) for semiconductor inspection. Brooke is currently working with Large Language Models (LLMs) building a platform bridging the gaps in knowledge of students interested in complex topics. Brooke is an educational content creator, public speaker, and role model for women and girls in STEM.

As a math enthusiast and a Canadian innovator, what inspires you to address some of the world’s most pressing challenges through your projects in areas like BCI for Bipolar Disorder diagnosis and automation in the operating room (OR)?

Building and creating new things from nothing has always been an interest of mine. My passion for taking on challenging tasks started with my love for math. In grade school, I attended math classes at my local university where we focused on proof-based problems, usually taken from math competitions. We would start with a problem we had no idea how to approach and come up with a path. We would fail to make it work sometimes, but eventually, we would solve the problem and present it to the teacher who would rip apart the solution we spent so much time coming up with. 

This class taught me so much more than math; it introduced me to problem-solving and being okay with failing in front of a large group of people. I didn’t know it at the time, but it taught me so many important skills that successful builders and entrepreneurs need to have. When I started exploring real-world applications of math and building projects of impact I started to notice how valuable these skills were.

Before starting your current projects — building a platform connecting people with their family stories and culture and DocBot, a platform to query YouTube videos to help better understand complex topics — what were you focused on? How did your previous experiences shape your current interests and projects?

Following my love for math, my last projects focused on finding an area of high impact that would also require me to fall back on these skills. I spent some time investigating and came across Federated Learning, which was addressing many issues in the world of Data Privacy and Artificial Intelligence (AI). I got curious and tried to learn as much as possible, diving into different projects working with various technologies. I then got into Differential Privacy (a mathematical framework for managing privacy risks) and fell in love with reading papers and extracting all the value from the paper. Every night after finishing school work, I would stay up reading paper after paper. This area of work spearheaded my love for building things that matter to the world. 

With your diverse experience in projects ranging from writing on a paper on all the math behind Neural Networks to using CNNS for silicon wafer inspection, what is the biggest lesson you’ve learned so far? How has this influenced your approach to learning and your work in technology and mathematics?

Learning has been such a big part of my life, and learning how to learn is something I have been heavily focused on. In high school, you spend a lot of time learning the fundamentals of various fields, but it isn’t until you go to university that you can niche down and learn more in-depth. Therefore, a lot of my endeavours have required me to learn things that were considered far above me and my current level of knowledge. This was something I felt while trying to translate a mathematically dense paper on differential privacy into something I could easily understand. This experience taught me how to break down a complex topic into starting with something I could understand and filling in the gaps by reaching out to the right people, finding textbooks, and consuming a lot of content on various topics. I would say that taking on intimidating projects has taught me how to learn on a curve and fast!

What unique challenges have you faced as a young woman making a significant impact in fields like AI, computer vision, and neural networks? Could you share any specific obstacles you’ve overcome in your journey?

As a woman, entering communities of entrepreneurs, builders, and hackers can be difficult as you’re often the only woman there. I used to struggle with this and questioned my sense of belonging. However, over time I converted this sense of uncertainty into a challenge to push myself and prove to myself that I could keep up with the people around me. 

What is one of the most important things you’ve discovered about yourself? How has this realization influenced your approach to your projects and aspirations, especially in robotics, AI, and federated learning?

One of the biggest things I realized about myself is that I tend to obsess over what I’m learning about and working on. When I find a new area of exploration, I tend to go super deep and try to learn everything possible. For example, when I was first learning how to lift weights and get into the gym, I spent months learning the correct diet, form, and what worked best for me. This helped me develop a plan that I follow to this day. This is similar to how I do things in my professional life. When I was learning how privacy tech and decentralized learning, I went deep and tried to cover as much surface area as possible, before niching down and building specifically in Federated Learning and Data Privacy. 

If you had an extra hour in your day, how would you spend it?

With extra time in the day, I would likely spend it working on my projects. Although I love school and it can be very exciting to learn about different breadths of mathematics and computer science, I love building. It brings a thrill like no other, and unfortunately, being a computer science student can sometimes make it difficult to find time to build the things I want. Having extra time would allow me to meet with more cool people working on similar endeavours, debug code, ideate, and overall, build projects out.

To keep up with Brooke, connect with her on X (formerly Twitter), Medium, YouTube, and LinkedIn.