Teaching introductory data science and AI
I teach courses DS110 and DS340, where students build conceptual and programming foundations for working with data, models, and AI systems.
Teaching →Teaching · AI education · Interactive systems
Teaching data science and AI in the age of LLMs.
I’m a Professor of the Practice in Boston University’s Faculty of Computing & Data Sciences. I teach introductory data science, machine learning, and AI, and I study how LLMs can support learning without short-circuiting it.
Current focus
What I’m working on now
My current work is centered on the practical classroom questions raised by modern AI: what students should learn, what tools should do, and how courses can make AI use productive rather than substitutive.
Studying LLMs for learning
Recent projects examine LLM-powered tutors, practice problem generation, and how students interact with AI tools while learning programming and data science.
Research →Designing interactive systems
My past work includes successful text-based games and earlier AI research. That background still shapes how I think about designing compelling learning experiences.
Games →Recent research
AI education is moving fast. The classroom still has to make sense.
The questions I’m most interested in are concrete: when does an LLM tutor actually help? What kinds of generated practice are useful? How should beginner programming courses change when code-generation tools are always nearby?
Also
Games
My alter ego is as a game designer - I write games where choices matter and players need to reflect on what kind of world they want to create and live in.
Choice of Robots
A text-based game about building human-level robots, shaping society, and living with the consequences.
Choice of Magics
An upbeat postapocalyptic fantasy with extreme branchiness and many possible endings.
Choice of Alexandria
A historical interactive fiction game about science, politics, and the decline of ancient Alexandria.