Hello! My name is Saurabh Garg and I am a second year PhD student at Machine Learning Department at CMU where I am advised by Prof. Zachary Lipton and Prof. Zico Kolter. I also work closely with Prof. Siva Balakrishnan. I am broadly interested in building robust and interpretable machine learning systems. Machine learning algorithms are typically developed and evaluated under simplistic assumptions that are often violated in practice. I am interested in understanding the behavior of machine learning models in real-world scenarios and building provable methods to make progress towards relaxing simplifying assumptions in order to make robust and trustworthy models.
I did my undergrad from IIT Bombay, India with major and honors in CS and minors in Applied Statitics in 2018. After that, I spent one amazing year at Samsung Headquaters, Korea. In the past, I have worked with Prof. Suyash Awate on building statistical machine learning algorithms for exact MCMC samspling as a part of my Bachelor’s thesis. During my stay at IITB, I have also spent major time working with Prof. Preethi Jyothi on the problem of building robust langauge models for code switched speech. I was also fortunate to work with Prof. Soumen Chakrabarti on building interpretable question answering systems using KG and corpus.