Sidhika Balachandar

Hello! My name is Sidhika. I am a third-year Computer Science PhD student at UC Berkeley. I work on problems at the intersection of machine learning, fairness, and healthcare. I am advised by Emma Pierson and Nikhil Garg. I am fortunate to be supported by the NSF GRFP.

I am interested in creating models in settings where outcome data is missing or biased (e.g., ICLR 2024). In particular, my research has focused on the following questions: What are the challenges of using outcome data collected from human decision makers or crowdsourced platforms? What identification approaches can we use to create models in these settings? Can we leverage external, domain specific information or data?

I started my PhD and received a Masters in CS from Cornell University. I was at Cornell's beautiful NYC campus, Cornell Tech! During my PhD I was also lucky to do an internship at Microsoft Research Cambridge, UK with Cecily Morisson, Bhaskar Mitra, and Camilla Longden on the Teachable AI Experiences (TAIX) team.

Before my PhD, I received my undergraduate degree in CS at Stanford University. At Stanford, I worked with Ron Dror and Alex Powers on a drug docking project. I also worked with Leonidas Guibas and Adrien Poulenard on a project about rotation equivariant machine learning for 3D point clouds.

My hobbies include dance (I've been trained in classical Indian dance), hiking, cooking, and reading.

My CV is available here. My pronouns are she/her/hers.