Joseph Jay Williams: Director of IAI Group, Assistant Professor of Computer Science at the University of Toronto
Sam Maldonado: Research Programmer
Graduate Students
Arghavan Modiri
Master’s Student, working on the design of mobile health intervention systems
Mobile health intervention systems combines human-computer interaction with statistical machine learning to discover how to personalize text messages to people in order to motivate them to do more exercise and improve adherence to physical activity.
Also, studying contextual Multi-Armed Bandits (MABs) and similar algorithms and their applications in health.
Jacob Nogas
Master’s Student, generally interested in statistics and machine learning applied to HCI. For my masters, I am working on issues pertaining to statistical inference from data collected by Multi-Armed Bandit algorithms in online educational experiments. I am interested in how type 1 errors (false positives) can be controlled in adaptive experiments, and validating these methods in real world online education settings.
Jaemarie Solyst
Incoming PhD student in fall 2020
Working on computer science education.
Affiliated graduate students
Hammad Shaikh
Fifth-year PhD student in economics, working on improving study habits of students on online platforms through technology-mediated interventions that leverage insights from behavioral science. To be more concrete, we evaluate the impact of varying messaging interventions that aim to induce students to do optional ungraded problems and start homework earlier in an online setting using experiments.
Veronica Bergstrom
Second-year PhD student in psychology, collaborating with Goodlife Fitness to investigate whether personalized text messages can increase adherence to one’s workout schedule. In her primary line of research she investigates biases between various religious (Christian, Muslim) and nonreligious (atheist, agnostic) groups.
Visiting graduate students
Nina Deliu
PhD Student in Methodological Statistics at the University of Rome La Sapienza. Research areas: Bayesian Statistics, Causal Inference, Reinforcement learning and Multi-armed bandits with applications in healthcare domains, Adaptive Interventions.
Undergraduate Students
Jai Aggarwal
Fourth-year computer science and cognitive science student
Working on the student stress and DIAMANTE projects.
Ben Prystawski
Third-year computer science and cognitive science student working on personalized explanations.
Jiading Zhu
Fourth-year Engineering Science student in Machine Intelligence Option. Background in ML/RL.
Working on an undergraduate thesis with Joseph on factorial design, also helping out on DIAMANTE and Goodlife.
Yuya Asano
Fourth-year undergraduate student in computer science. His research interests are in natural language processing and applied machine learning with a mixture of human-computer interaction and education. His long term research goal is to provide better computational aids to intellectual activities such as reading comprehension and discussion. He is currently working on the personalized explanation project and the automatic code progress detection project.
Qi Yin Zheng
Second-year computer science specialist working on students on track and personalized explanations projects.
Samantha Quinto
Fifth-year computer science specialist and cognitive science student. Her primary research interests include computational linguistics and human-computer interaction. She is currently working on the mental health intervention project with collaborators from Northwestern University.
Emmy Liu
Third-year computer science and cognitive science student, working on metaskills interventions.
Huizhen Cui
First-year computer science student
Working on the personalized explanations project.
Previous lab members or collaborators
