Uploaded January 2025 | Updated September 2026, 10 hours ago
Abstract:
How can we design AI-driven systems that go beyond isolated features and quantified metrics to truly understand and adapt to the broader narratives of users' lives? In this talk, I will share insights from my fieldwork in the USA, Canada, and Bangladesh, along with systems I developed using generative AI, to demonstrate how technology can address the complex challenges users face and help them navigate their experiences. I will discuss how these systems empower users to construct meaningful narratives and provide adaptive support that acknowledges their unique contexts. Finally, I will explore how these ideas can extend to support researchers in managing multiple goals, addressing research challenges, and fostering collaboration across teams.
Bio:
I am Ananya Bhattacharjee, a Ph.D. candidate in Computer Science at the University of Toronto. I study, design, and build interactive, AI-driven systems that understand and adapt to individual and social narratives. These systems broadly aim to promote psychosocial wellbeing—the overall state of an individual’s mental, emotional, and social health. Drawing on insights from surveys, interviews, and field experiments, I design interventions that employ generative AI and reinforcement learning to adaptively support users' evolving needs and contexts. The interventions I deploy can take many forms, including web platforms that simulate peer support, mobile applications that promote reflection or assist in managing stress, and text messaging programs that alleviate symptoms of depression and anxiety.
I contributed to the development of the Small Steps SMS program—a two-month intervention to help people manage anxiety and depression symptoms—which has reached over 5,000 users (with shortened versions
reaching an additional 5,000 more) in North America. My research has also contributed to integrating personality traits into Microsoft Copilot and led to policy changes at two major helplines. I have published 14 first-authored papers (20+ total) in venues such as CHI, CSCW, TOCHI, AAAI HCOMP, and
JMIR. My work received a Best Paper Award and two Best Paper Honorable Mentions at CHI. I have also been supported by several fellowships, including the Schwartz Reisman Graduate Fellowship and the Inlight Research Fellowship.
Abstract:
How can we design AI-driven systems that go beyond isolated features and quantified metrics to truly understand and adapt to the broader narratives of users' lives? In this talk, I will share insights from my fieldwork in the USA, Canada, and Bangladesh, along with systems I developed using generative AI, to demonstrate how technology can address the complex challenges users face and help them navigate their experiences. I will discuss how these systems empower users to construct meaningful narratives and provide adaptive support that acknowledges their unique contexts. Finally, I will explore how these ideas can extend to support researchers in managing multiple goals, addressing research challenges, and fostering collaboration across teams.
Bio:
I am Ananya Bhattacharjee, a Ph.D. candidate in Computer Science at the University of Toronto. I study, design, and build interactive, AI-driven systems that understand and adapt to individual and social narratives. These systems broadly aim to promote psychosocial wellbeing—the overall state of an individual’s mental, emotional, and social health. Drawing on insights from surveys, interviews, and field experiments, I design interventions that employ generative AI and reinforcement learning to adaptively support users' evolving needs and contexts. The interventions I deploy can take many forms, including web platforms that simulate peer support, mobile applications that promote reflection or assist in managing stress, and text messaging programs that alleviate symptoms of depression and anxiety.
I contributed to the development of the Small Steps SMS program—a two-month intervention to help people manage anxiety and depression symptoms—which has reached over 5,000 users (with shortened versions
reaching an additional 5,000 more) in North America. My research has also contributed to integrating personality traits into Microsoft Copilot and led to policy changes at two major helplines. I have published 14 first-authored papers (20+ total) in venues such as CHI, CSCW, TOCHI, AAAI HCOMP, and
JMIR. My work received a Best Paper Award and two Best Paper Honorable Mentions at CHI. I have also been supported by several fellowships, including the Schwartz Reisman Graduate Fellowship and the Inlight Research Fellowship.
