Hi!
I am a PhD candidate at the University of Michigan School of Information, advised by Christopher Brooks and Xu Wang. My research lies at the intersection of Learning Sciences, Human-Computer Interaction, and AI.
I am interested in designing human-AI collaborative systems that encourage active and critical engagement with online information. Through these systems, I aim to harness people's creativity and unique insights to generate new knowledge, while also helping them learn deeply.
In my dissertation, I studied and experimented with educational technology that is both powered by and created for learners. I conducted field studies that involved students in creative learning activities that not only fostered their higher-order thinking skills but also led to the generation of educational artifacts, e.g., students generating hints or multiple-choice questions. Recently, I explored the potential of using LLMs to support learners' engagement in such activities and studied the impact of different forms of student-AI collaboration on students' learning outcomes.
My work has been recognized with two Best Paper Awards at leading conferences on educational technology. My research during an internship with the PROSE team at Microsoft led to the deployment of a tool for providing programming hints to students in a large online data science course at the University of Michigan.
Before this, I worked at IBM Research Labs, India on AI+HCI applications in early childhood learning and civic welfare. I graduated from the Indian Institute of Technology Delhi (IIT Delhi) in 2017, with a Master's and Bachelor's in Mathematics and Computing.
In my spare time, I enjoy music, dancing, traveling, and playing with my two cats :)