STEM Student Spotlight: Bao Nguyen, University of Alberta

Welcome to our STEM Student Spotlight series, where we highlight the incredible initiatives and achievements led by STEM students in Canada. Our mission is to empower and inspire the next generation of engineers and innovators by celebrating the achievements of student leaders. In today’s spotlight, we’re excited to showcase Bao Nguyen! Bao is a student from the University of Alberta, and he participated in our Work Integrated Learning opportunity.

Bao has been learning about the fundamentals of Machine Learning and Artificial intelligence. Through this blog post, we delve into Bao’s exciting experience with learning new technical skills and exploring how data analysis and reinforcement learning can be an effective tools in the field of finance.

Bao shared his insights into the projects he worked on and the technical skills he learned:

Throughout the ML/AI Fall Program, I have delved deeper into the deeper subsets of machine learning and been introduced to artificial intelligence. Firstly, my projects with graph search courses taught me the fundamental graph search algorithms, which I believe is important in any programming-related field I pursue. Followed by the GPS System course, the most important concept I came across was the A* algorithm, which is simple and yet so powerful in many map apps today.

Bao explained how his newfound technical skills helped him spearhead his own GPS project and taught him more effective and efficient problem-solving methods.

With my new algorithm knowledge, I will seek to complete my own GPS project. From my reinforcement learning projects, I learned how introducing rewards alone makes this area a deeper, richer subset of machine learning in its own way. An excellent example of this area’s application is value iteration, which I found beginner-friendly and intuitive given perfect environment conditions. Last but not least, the Q-learning courses and projects helped me understand a more efficient, applicable method compared to value iteration using practical examples.

With his new technical skills in ML/AI, Bao explained how this experience in ML/AI will help empower his career in finance.

From what I learned with Markov Decision Processes, this concept will be very useful for applying machine learning and reinforcement learning to finance. Along with other topics introduced in this program, I have developed solid fundamentals in data science and machine learning to continue in my field. Without this opportunity, I wouldn’t have understood machine learning conceptually to the same degree as well as realize its strengths and limitations

In an age where ML/AI plays an increasingly significant role in our daily lives, Bao has explored the power of integrating these skills to excel across diverse industries, like finance. Stay tuned for more inspiring stories from our STEM Student Spotlight series!