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.

My work aims to foster deep thinking and learning in people in the age of AI. To do this, I develop interactive AI-based learning technologies and interventions that support people's critical thinking, reflection and agency. 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. Methodologically, my work integrates empirical lab and field studies with design-based research to conceptualize and experiment with human-AI interaction approaches for learning and information seeking.

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 technologies. I have also had the opportunity to deploy learning technologies I've developed in diverse educational settings, including graduate-level data science courses and MOOCs.

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 as a research engineer at IBM Research, Bangalore. 

In my spare time, I enjoy music, dancing, yoga, reading and being out in nature!