I’m a Bullard Postdoctoral Fellow at the University of Texas at Austin School of Information, where I work with Prof. Soo Young Rieh. My research sits at the intersection of the learning sciences, information science, and human-AI interaction.

I study how to support deep thinking and learning in people in the age of AI. To do this, I build interactive systems and interventions that help people think critically and support trust calibration in AI-generated information. For example, I explore how supporting people’s metacognition—their ability to reflect on and regulate their own thinking—can lead to more thoughtful and responsible use of generative AI tools.

I graduated with a PhD from the University of Michigan School of Information, advised by Christopher Brooks and Xu Wang. My dissertation investigated strategies to promote students' higher-order thinking skills by engaging them in learnersourcing, an approach where students actively contribute to the generation of educational artifacts while participating in pedagogically meaningful activities. I also explored how AI can support learners' engagement in learnersourcing, while encouraging them to critically evaluate AI-generated content. 

My work has been recognized with several Best Paper Awards at leading conferences on learning and technology, and contributed to the development of a personalized hint-generation system for a large online data science course at the University of Michigan.

I graduated from the Indian Institute of Technology Delhi in 2017, with an Integrated Bachelor's and Master's in Mathematics and Computing. Before my PhD, I worked for 2 years at IBM Research, Bangalore. 

In my spare time, I enjoy music, dancing, yoga, crocheting, and playing with my two cats :)