Bio
I’m a Course Instructor and a PhD student in the Department of Computer Science at the University of Toronto, and an EdTech/Ed Data Science consultant.
I work on developing scalable adaptive experimentation platforms for motivational and self-directed context-aware adaptive behavior change microinterventions, including LLM-based. I also create tools to support stakeholder-centered development and decision-making based on adaptive experiments using computational interaction (Bayesian statistics, multiarmed bandits, data visualization and optimization).
I am also interested in experimental and observational causal methods, in particular, experimental designs and methodologies for educational and behavioral interventions (e.g. MOST, SMART) and introducing multiarmed bandit designs into these methodologies, as well as in designing tools for supporting stakeholder decision-making based on adaptive experiments.
Before UofT I worked for seven years at the Higher School of Economics (HSE University) St.Petersburg, designing curricula and courses in Data & Computer Science, Systems & HCI, mostly targeted to non-STEM majors, and developing students’ research & analytical skills in these areas.
More broadly, I am interested in Computer/Data Science Education (especially for non-STEM majors), ML Systems Design for HCI, Learning Engineering, Design and Analytics and Computational Social Science.