Bio
Welcome to my page! I’m a PhD candidate in Computer Science at the University of Toronto, where I also teach courses in Data Science. I am also an incoming (July 2025) Educational Leadership Assistant Professor at the UBC’s Department of Computer Science. Alongside my studies, I consult in EdTech and educational data science areas.
My work focuses on building platforms that make educational and behavioral interventions adaptive, aiming to make learning more engaging and effective for students. This includes developing tools for data-driven decision-making that rely on computational interaction methods: Bayesian models, multi-armed bandits, data visualization, and optimization.
I’m also exploring how we can combine experimental and observational methods to better design and understand these interventions, especially through approaches like MOST and SMART, and how multi-armed bandit designs can enhance these methods.
Before coming to Toronto, I spent seven years at HSE University in St. Petersburg, where I designed data science and computer science courses, with a particular focus on students not majoring in STEM fields. My goal was to help them build solid research and analytical skills.
Beyond my specific projects, I’m broadly interested in how we teach computer and data science, including to students outside the typical STEM fields, and how machine learning can improve human-computer interaction. I’m also keen on learning engineering, the design and analytics behind effective learning, and the insights computational social science can bring to these areas.
I hope this site gives you a good sense of what I’m working on and what excites me in the world of technology and education.