YouTube Playlist of Public Lectures (link)
This playlist includes all public lectures I’ve given, including my Amii AI Seminar talk, two custom deliveries of foundational machine learning content for the AI in Medical Systems Society, a talk for the Undergraduate AI Society, and for AlphaStar Academy.
Intelligent Tutoring Systems for Math, CS, and Games (pdf) (video)
Presented at the Alberta Machine Intelligence Institute’s AI Seminar in Spring 2025.
Abstract of the talk: Justin Stevens will detail a path toward creating intelligent tutoring systems for math education, computer science education, and video games. His plan involves finding the right time to give a learner or player a hint, the best hint to give, and seeing how useful the hints are. He will also connect these tutoring systems with his past work on AI for games and using analogies to improve AI education.
AAAI New and Future AI Educator Award Talk 2024 (pdf) (video)
At the 2024 Educational AI Symposium, I gave a talk on my blue sky idea for the future of AI Education: creating a database of analogies for AI educators to use while teaching.
Surprises in Puzzle Video Games (pdf) (video)
Presented at the University of Alberta’s Undistinguished Lecture Series in Winter 2022. I talked about how surprising behavior can emerge within simple systems in computers, and how these ideas are applied to game design in the puzzle video games, The Witness and Baba is You.
How to win two-player impartial games using number theory (video)
Presented to AlphaStar Academy students in Summer 2020 on two-player impartial games that can be analyzed with strategies involving number theory. I taught the winning strategies so that you can beat your friends at these games, and also showed how these ideas were also used in DeepBlue, the chess program which beat Garry Kasparov at chess.
Cellular Automata Presentations (pdf) (pdf2)
Two talks from my summer research project in Summer 2020. The goals of these talks were to see how cellular automata could be used for a wide range of applications, with a specific emphasis on their applicability in heuristic search.
Solving Pell Equations with Continued Fractions and Algorithms (pdf) (blog post)
A talk I gave at the Seminar in Number Theory for Alberta Students in Fall 2019. I wrote a computer program which could produce the fundamental solution of a Pell equation given the continued fraction representation of \(\sqrt{d}\) too.
Gradient Descent Towards Neural Networks (pdf) (video)
An introduction to neural networks for a handwritten digit recognizer using the MNIST data set from April 2019. Practical examples of the code were also given using Tensorflow’s Keras.
Welcome to Undergraduate Artificial Intelligence Society (pdf)
A talk I gave to a new student group I founded in October 2018, with the goal of making everyone excited about artificial intelligence. The talk was well attended and ran two times, and the student group is still around today. Check out their activities here.