In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We sat down with Prakhar Ganesh to learn about his work on responsible AI, which is focussed on the concept of multiplicity. We found out more about some of the projects he's been involved in, his future plans, and how he got into the field. Could you start with a quick introduction to yourself, where you're studying, and the broad topic of your research? My name is Prakhar Ganesh. I'm also affiliated with Mila, which is a research institute in Montreal. My supervisor is Professor Golnoosh Farnadi.

Machine learning is now an integral part of decision-making processes across various domains, e.g., medical applications [

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The performance of any supervised learning model depends strongly on the quality of input instances.

For this reason, it is important to design algorithms that are able to maintain a stable and high quality solution and that at the same time can process updates efficiently.