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Adith Swaminathan
Senior Researcher
Adith Swaminathan is a Principal Researcher at Microsoft, based in Redmond, Washington. He has been with Microsoft since February 2017, progressing from Researcher to Senior Researcher, and most recently to Principal Researcher in September 2023.1
Education and Early Career
Swaminathan completed his Ph.D. in Computer Science at Cornell University from August 2011 to January 2017. His thesis focused on machine learning for interactive systems, specifically studying batch learning under bandit feedback models.1 He also holds a Bachelor of Technology degree in Computer Science and Engineering from the Indian Institute of Technology, Bombay, and a Master of Science degree in Computer Science from Cornell University.2
Research Focus
Swaminathan's research primarily centers on:
- Machine learning for interactive systems
- Counterfactual evaluation and learning from logged user feedback
- Bandits, causality, and reinforcement learning
He is particularly interested in developing principles and algorithms that can re-use interaction logs of systems to inform the design of future systems.2
Professional Experience
Throughout his career, Swaminathan has gained diverse experience:
- Microsoft Research: Currently a Principal Researcher, he has been with Microsoft since 2017, working in the Deep Learning Technology Center.12
- Academic Visits: Spent the 2015-16 academic year visiting the Information and Language Processing Systems group at the University of Amsterdam.12
- Internships: Completed multiple research internships at Microsoft, including stints at Microsoft Research NYC, Redmond, and Silicon Valley.12
- Industry Experience: Worked as a Strategist at Tower Research Capital from May 2010 to July 2011, where he implemented automated high-frequency trading systems.1
Publications and Achievements
Swaminathan has authored numerous publications in prestigious machine learning conferences and journals. Some notable works include:
- "Recommendations as Treatments: Debiasing Learning and Evaluation" (ICML 2016)
- "Unbiased Learning-to-Rank with Biased Feedback" (WSDM 2017, Best Paper Award)
- "Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization" (JMLR 2015)3
His research has garnered significant attention in the field, with several of his papers receiving hundreds of citations.3
Adith Swaminathan's work at Microsoft Research continues to focus on advancing machine learning techniques, particularly in the areas of interactive systems and counterfactual learning.
