Director
Joseph Jay Williams is an Assistant Professor in Computer Science at the University of Toronto (with Graduate Appointments in Psychology and Statistical Science), leading the Intelligent Adaptive Interventions research group. He was previously an Assistant Professor at the National University of Singapore's School of Computing in the Department of Information Systems & Analytics, a Research Fellow at Harvard's Office of the Vice Provost for Advances in Learning, and a member of the Intelligent Interactive Systems Group in Computer Science. He completed a postdoc at Stanford University in Summer 2014, working with the Office of the Vice Provost for Online Learning and the Open Learning Initiative. He received his PhD from UC Berkeley in Computational Cognitive Science, where he applied Bayesian statistics and machine learning to model how people learn and reason. He received his B.Sc. from the University of Toronto in Cognitive Science, Artificial Intelligence and Mathematics, and is originally from Trinidad and Tobago.
Associate Director
Michael is an Assistant Professor, Teaching Stream in the Department of Mathematical and Computational Sciences at the University of Toronto Mississauga (UTM). He is a computer science educator who prides himself in fostering a welcoming environment of educational excellence through active and experiential learning, as well as, through the use of behavioural intervention strategies. Michael has received the University of Toronto's Student Life Award for Outstanding Faculty Guidance & Support.
Regular Internal Faculty Collaborators
Andrew is an Associate Professor, Teaching Stream in the Department of Mathematical and Computational Sciences at the University of Toronto Mississauga (UTM). He takes special pride in his role as an educator and has received the University of Toronto’s President’s Teaching Award and the OCUFA Teaching Award. Andrew led the development of the online exercise system used in CS courses at U of T, and much of his research focuses on the analysis of data from that system. Graduate Students & Staff in Computer Science
My research works focus on developing and understanding the role of
technology in helping people manage their psychological well-being. I
have developed several text messaging services, mobile applications, and
websites to help people reduce their stress, reflect on negative
emotions, and self-monitor moods. Collaborating with Mental Health America,
I have closely worked with vulnerable population to understand their
needs and expectations from digital mental health platforms, eventually
allowing us to develop an AI-powered chat tool. Additionally, I have conducted field studies in Bangladesh to understand how much of the existing support behavior techniques align with local people's customs and values. Working closely with a major crisis helpline in Bangladesh (Kaan Pete Roi), I have interacted with helpline volunteers and critically evaluated befriending model, one of the most common approaches followed by helplines around the world. Through my work, I aim to shift the research direction in mental health interventions from ‘individual’ to ‘social’. My research works have been published in top venues like CHI, CSCW, and JMIR. Here are links to my Website, LinkedIn, and Twitter. 
First-year PhD student (and Master of Science in CS), interested in computer science education and HCI. Currently focused on interventions to help students with planning ahead and time management, in order to motivate them to stay on track when learning online and mitigate procrastination.
Fred-Haochen Song Incoming first year PhD student in the Department of Statistical Science. I'm still deciding on what path I could take for the program, but very likely to be on Bandit Algorithm and Allocation Probability Staff. I am very opening to more ideas and feel free to help me shape my incoming a few years!
You can find a paper I have worked on before in the Implicit Bias of Gradient Descent at: https://ieeexplore.ieee.org/document/9730384
I am currently working on a transfer learning Convolutional Neural Network model to detect Covid-19 Lungs Images.
You can find my Linkedin Pages at: https://www.linkedin.com/in/red1995/ or reach me at haochensong2022@gmail.com
Looking forward to talking to you!
First-year PhD student in the Department of Computer Science. My research interests lie in Human-Computer Interaction, Machine Learning, Natural Language Processing and their intersection with Social Sciences. Currently working on an adaptive text-messaging service to help people better manage their mental health, in collaboration with Northwestern University and Mental Health America. Also designing communication strategies to encourage people to get vaccinated. In a previous life, I worked as a Software Engineer at JPMorgan Chase where I was responsible for building the firm-wide chatbot-as-a-service framework and built autonomous drones for warehouse management as a Research Analyst at McKinsey. Besides work, I enjoy running, playing badminton, writing tunes on my guitar and taking care of my startup.
Ilya Musabirov I'm a 1st year PhD student. My research interests are in developing tools and approaches to support the theory-driven and instructor-led design of instructional, motivational and self-regulation adaptive interventions in education. More broadly I am interested in HCI, EdTech, Computer/Data Science Education (especially for non-STEM majors), Learning Engineering, Design and Analytics and Computational Social Science. Previously I was a Senior Lecturer and Jr Research fellow at HSE University St.Petersburg where I co-designed and taught courses and programs in Data Science, Computational Social Science and HCI, targeted primarily to non-STEM students.
Third-year Ph.D. student in Computer Science. I do research at the intersection of HCI and Education Technology. Currently, I am looking at ways to make it easier for instructors and researchers to collaborate and run experiments in digital learning platforms using novel tools that facilitate faster, better, and cheaper learning science research. I am also investigating the effects of various interventions intended to improve first-year CS students’ “meta-skills”, which are transferable skills that can help them in multiple areas of their lives (e.g. planning, growth mindset, stress management, etc). Before coming to the University of Toronto, I completed my M.Sc. in HCI from the Department of Computer Science at the University of British Columbia, where I focused on Computer-Assisted Language Learning and Multimodal Interfaces.
The easiest way to reach me is to email mohireza [at] [cs.toronto.edu]
The MOOClet Framework: Unifying Experimentation, Dynamic Improvement & Personalization in Online Courses
Mohi Reza, Juho Kim, Ananya Bhattacharjee, Anna N. Rafferty, Joseph Jay Williams
L@S 2021 | Paper | Video Designing CAST: A Computer-Assisted Shadowing Trainer for Self-Regulated Foreign Language Listening Practice
Mohi Reza and Dongwook Yoon
CHI 2021 | Paper | Video | Website Designers Characterize Naturalness in VUIs: Their Goals, Practices, and Challenges
Yelim Kim, Mohi Reza, Joanna McGrenere, and Dongwook Yoon
CHI 2021 | Paper | Video
Dana Kulzhabayeva First-year PhD student in Psychology. I just completed my Bachelor's in Psychology and Cognitive Science, and look forward to exploring my research interests in mental health and learning. I'm currently working on a project which investigates how manipulating emotion and certainty through public health messages can encourage behavioral change in relation to COVID-19 vaccination.
 Tong Li First-year PhD student in Statistics (started my PhD from Sept 2021). I'm currently doing research on Bandit algorithms for randomized experiments, with the hope of understanding the performance of traditional Bandit algorithms such as Thompson Sampling and developing new algorithms that can achieve a better treadoff between regret and statitical inference. I'm also in the Mental Health America project where we use Bandit algorithm to find text messages that can better help people with mental health issues.
Pan Chen is a first-year master's student in Computer Science. He studied Computer Science & Statistics during his undergraduate. He is working within the Voice Reflections & TenQ teams.
Master's student in Computer Science. I am currently working on projects that examine student behaviours in online learning communities, mindset reframing, and reflection systems. As an undergraduate, I studied Computer Science at the University of Toronto Mississauga.
Affiliated graduate students
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.
Undergraduate Students
Emmy is a fourth-year undergraduate student specializing in computer science and majoring in cognitive science. She is broadly interested in computational cognitive science and computational linguistics. She is currently the project manager for the metaskills project.
Qi Yin Zheng
Third-year computer science specialist primarily focusing on the students on track project which aims to improve online homework participation in CS1. In the past I have also worked on the personalized explanations project.
I am an undergraduate student studying computer science at UofT. I am interested in natural language processing and human-computer interaction, especially the application of these techniques to education. At the IAI lab, I am working on the personalized explanation project. I am also collaborating with CMU on 1) human-in-loop approach to generate instructionally beneficial hints for programming questions and 2) extracting actionable insights from student reflections.
3rd Year Undergraduate at the University of Toronto, pursuing Computer Science Specialist and Mathematics major. I am interested in using AI to create autonomous systems and using ML in interesting ways to create real-world applications to help with mental health. I am involved in OnTrack, TenQ and statistically considerate bandits.
Second year computer science specialist student working on the statistically considered bandit projects.
Alvina Lai
2nd year psychology and cognitive science student, minoring in sociology. Working on mental health america intervention project with collaborators from Northwestern university, leading recruitment and webpage development for a text messaging service.
Angelina is a second year student currently pursuing a Psychology specialist and Nutritional Science major. Currently involved with OnTack, MHA and Metaskills projects.
Anna Ly
I'm a 2nd year UofT student specializing in Applied Statistics from the Mississauga campus. For now, I usually assists with organizing undergraduate meetings. I also really like animals.
Arissa is a 4th year Criminology & Psychology student. Besides trying to survive U of T, she's generally involved with project management in the lab such as MHA and Personalized Explanations.
I'm a third year computer science and cognitive science student interested in HCI and social computing. I'm currently working on designing a text message based intervention system to help manage common concerns like depression and anxiety.
I'm a third year life sciences student, majoring in Physiology and Global Health. At the IAI Group, I'm involved in project management and research with the OnTrack Project. In my spare time, I like to cook, read US history, and play with my dogs.
Third year student majoring in Psychology and Statistics. Currently working on the Mental Health America project.
First-year undergraduate student in Life Sciences stream. Excited to be working with the IAI Group as a Lab Assistant.
Helena Jovic
Second-year undergraduate at the University of Toronto studying Computer Science and Biology. Currently involved with the Mental Health America intervention project and Personalized Explanations.
Huizhen Cui
First-year computer science student
Working on the personalized explanations project.
Ishra Haq
2nd year diaspora and transnationalism student. Helping with the MHA project and other tasks around the lab.
Jehan Vakharia
In charge of implementing Multi-Armed Bandit solutions for the Mental Health America (MHA) Project. Also managing the coordination of different internal UofT teams for the MHA project.
Third-year computer science student working on bandit algorithms such as improving statistical inference in Thompson Sampling.
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.
Third-year computer science & statistic student
Volunteering on the on track project and the technical infrastructure in the mental health America project
Lillian Xu
I am a fourth year undergraduate student pursuing a double major in Global Health and Nutritional Sciences, with a minor in psychology. I am thrilled to be joining IAI Labs as a Work Study student for Fall 2020.
Stephanie Cristea
Stephanie is a second-year undergraduate student double majoring in cognitive science and statistics at UofT. She's interested in using data science and machine learning to improve human-computer interactions. Outside of the lab, she spends her time learning to play the electric guitar, reading in coffee shops, and trying to keep her plants alive.
Hello, I am a second year Computer Science student at the UofT St. George campus. I am currently pursuing a specialist in computer science with a focus on artificial intelligence, a major in cognitive science and a minor in mathematics. I am working in the IAI lab on the Personalized Explanations project.
Undergraduate student in Computer Science and Statistics. Interest: applications of machine learning and designing / improving human-computer interaction experiences.
Trisha ThakurUndergraduate student at the University of Toronto, majoring in Computer Science and Cognitive Science with a minor in Statistics. With interests in Machine Learning and Human-Computer Interaction, I am currently working on the personalized explanations project.
Xin PengThird-year computer science and data science student working on Mental Health America project.
Second-year student pursuing a specialist in finance and economics and a major in statistics.
Working on the students on track project
Sophomore pursuing a Specialist in Computer Science with a Minor in Economics. Currently working on Statistical Bandits and the Entrepreneurship model for the project with Mental Health America!
I am a second year Cognitive Science and Psychology double major. I'm interested in computer-human interactions, as a way to connect my studies in both computer science and psychology. In the lab, I am working with the OnTrack group and Personalized Explanations. My other hobbies include playing violin and mario kart.
A third-year student majoring in Computer Science, Cognitive Science and a Psychology minor. Working on the personalised explanations project by analysing qualitative and quantitative data as well as co-ordinating tasks in the team.
 Muhammad Hamza Khan
Second-year student with an interest in data science, pursuing a double major in Public Policy and Economics, with focus in Data Analytics.
Mathematics & Statistics undergraduate student, focused on issues pertaining to statistical inference from data collected by Multi-Armed Bandit (Reinforcement Learning) algorithms.
I'm a second-year student at U of T majoring in Statistics and Economics, minoring in Computer Science. I'm interested in ML, AI, HCI and their practical implementations. Besides academics, I love to work out, biking, reading.
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.
I am an undergraduate student in computer science and writing & rhetoric. Currently, I am involved with MHA Product Design and statistically considerate bandits.
Stella Cai
I’m in my third year as a CS Specialist and doing minors in economics and statistics on the side. I’m thinking about going into natural language processing because I’ve always loved to study and learn new languages, but I’m also interested in creating great user experience designs.
I'm an undergraduate student studying Mathematics and its Application Specialist at UofT. I'm working in the IAI lab on the Personalized Explanations project.
Really appreciate Prof. Joseph offered me a position in the team. Enrich myself lots of valuable skills in IAI lab, like collaboration, time-managements, etc. Furthermore, people here are so nice!! It's really an unforgettable experience to me.
I am an undergraduate computer science and maths student interested in machine learning and its applications into different fields. In the IAI lab, I lead the software development of the mental health intervention project for Mental Health America (MHA). I also help in data analysis and the implementation of reinforcement learning algorithms. In my free time, I enjoy exercising and binge-watching TV shows!
Third-year undergraduate student at the University of Toronto specializing in Finance and Economics through the Rotman Commerce program and minoring in Statistics. Interested in behavioural economics, data science, international affairs, and policy reform. Currently involved on the OnTrack project and the entrepreneurship branch of the Mental Health America project.
Regular External collaborators
Audrey is an Assistant Professor in the Computer Science and Software Engineering department, and the Electrical Engineering and Computer Engineering department, at Université Laval. She is also affiliated with Mila — Quebec Artificial Intelligence Institute through a Canada CIFAR AI Chair. Her research aims at bridging the gap between theory and practice in reinforcement learning (RL).
I am a Researcher at the MRC Biostatistics Unit - University of Cambridge (UK), and a PhD Candidate in Methodological Statistics at Sapienza University of Rome (Italy). My research interests lie at the intersection between Bayesian methods, statistical reinforcement learning & multi-armed bandits, and modern real-world applications based on adaptive experimentation.
Dr. Sealfon brings considerable experience with physics education research, faculty development, and Bayesian cosmostatistics to her growing interest in learning analytics. She currently facilitates learning in the largest introductory physics courses at U of T (Physics 131 and 132). She aims to apply learning analytics to empower diverse learners through fostering both scientific reasoning and compassion.
I am a programme leader track at the MRC Biostatistics Unit (University of Cambridge, UK). My research involves the developing of design and analysis methodology for adaptive clinical trials that incorporates bandit dynamic optimisation ideas. I am interested particularly in the use of this novel approach to the design of clinical trials for rare diseases but also for the development of complex interventions such as digital therapeutics.
Anna Rafferty is an assistant professor at Carleton College in Computer Science. She completed her Ph.D. at the University of California, Berkeley, and was advised by Professor Tom Griffiths. Her recent work has been most concerned with how to apply machine learning and artificial intelligence techniques to improve education. Her projects have included developing algorithms to automatically diagnose students' understanding from their actions as well as more applied projects related to improving chemistry learning in the classroom.
I am an Associate Professor jointly appointed by the Centre for Quantitative Medicine and the Program in Health Services and Systems Research, Duke-NUS Medical School, and the Department of Statistics and Applied Probability at the National University of Singapore. I also hold an Adjunct Associate Professor position with the Department of Biostatistics and Bioinformatics at Duke University.
Thomas W. Price is an Assistant Professor in the Computer Science Department at North Carolina State University, where he runs the HINTS Lab. His research goal is to re-imagine educational programming environments as adaptive, data-driven systems that support students automatically as they pursue learning goals that are meaningful to them. His lab develops intelligent, adaptive technology that use data to automatically support students learning to program. His research sits at the intersection of Computing Education Research (CER), Educational Data Mining (EDM) and Intelligent Tutoring Systems (ITS).
Alumni & Previous lab members
Sam Maldonado
I am a research programmer with the IAI lab. I build and maintain applications for the lab, such as the MOOClet Engine, our solution for A/B testing and adaptive experimentation in online contexts, as well as building systems for adaptive messaging in contexts such as education and mental health.
First-year Ph.D. student interested in HCI, education, social psychology and the psychology of learning, storytelling, and digital media.
I am a fourth-year undergraduate student in computer science and cognitive science. My work in the IAI lab is developing multi-armed bandit algorithms that produce reliable data in adaptive experiments. I am generally interested in computational cognitive science, language, and theory of mind.
IAI MSc graduate. During my time at IAI I worked on issues pertaining to statistical inference from data collected by Multi-Armed Bandit algorithms in online educational experiments. In particular, I focussed on developing methods for balancing statistical inference against reward maximization in adaptive experiments, and validating these methods in real world online education settings. I am currently seeking full time employment in experimentation, data science, and machine learning.
I am a PhD student in the Human-Computer Interaction Institute at Carnegie Mellon University, and I worked in the IAI Lab on the Personalized Explanations project in 2019 and 2020 in-person and remotely. My research interests are in HCI and Education.
Jai Aggarwal
Fourth-year computer science and cognitive science student Working on the student stress and DIAMANTE projects.
Michal FishkinSecond-year engineering science student Project manager for the exercise and mental health projects
Arghavan graduated with a master's in CS in January 2021. During her collaboration with the IAI lab, she worked on the design of mobile health intervention systems. In particular, her research was in the intersection of human-computer interaction and machine learning in order to make positive behavioral changes in people. She also studied contextual Multi-Armed Bandits (MABs) and similar algorithms, including their applications in health.
Zarif Mahmud
Third-year computer science and statistics student
Working on the students on track project and organizing lab meetings
PhD Student in CSE at the Hong Kong University of Science and Technology
Working on visual analytics of online learning data
Previously a visiting PhD student in the lab
Weiwen Leung
Amazon.
Sasha Poquet
University of New South Wales.
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