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RAMANUJAN FELLOWS
SHIVANI AGARWAL
Assistant Professor, Computer Science
Indian Institute of Science
Bangalore-560012, Karnataka
[email protected]
Shivani Agarwal is an Assistant Professor in the Department of Computer Science and Automation at the Indian Institute of Science.
Prior to this she was a postdoctoral lecturer and associate in the Computer Science and Artificial Intelligence Laboratory at MIT. She
obtained her PhD in Computer Science at the University of Illinois, Urbana-Champaign; an MA in Computer Science at Trinity College,
University of Cambridge; and a BSc with Honors in Mathematics at St Stephen's College, University of Delhi.
RESEARCH DESCRIPTION
Machine learning is the study of computer systems and algorithms that automatically improve performance by
learning from data. It is a highly interdisciplinary field that brings together techniques from a variety of engineering
and mathematical disciplines, including in particular computer science, statistics, and mathematical optimization,
in order to analyze complex data and learn predictive models from it. Indeed, machine learning techniques are
already being used with success in a variety of domains, for example in computer vision to develop face recognition
systems, in computational biology to discover new genes, and in drug discovery to prioritize chemical structures for
screening.
Our research in recent years has focused on the study of ranking methods in machine learning, a relatively new class
of machine learning methods that find applications in recommender systems, information retrieval, bioinformatics,
drug discovery, and a variety of industrial prioritization tasks. Our research group in the Department of Computer
Science and Automation at IISc is currently exploring a variety of questions in machine learning and learning theory,
including statistical properties of learning algorithms, applications of machine learning in bioinformatics, and
questions related to privacy in machine learning.
SELECTED PUBLICATIONS
Arun Rajkumar and Shivani Agarwal. A differentially private stochastic gradient descent algorithm for multiparty classification. In Proceedings of the
15th International Conference on Artificial Intelligence and Statistics (AISTATS), 2012.
Shivani Agarwal. Learning to rank on graphs. Machine Learning, 81(3):333-357, 2010.
Shivani Agarwal, Deepak Dugar and Shiladitya Sengupta. Ranking chemical structures for drug discovery: A new machine learning approach. Journal of
Chemical Information and Modeling, 50(5):716-731, 2010.
Shivani Agarwal and Partha Niyogi. Generalization bounds for ranking algorithms via algorithmic stability. Journal of Machine Learning Research,
10:441-474, 2009.
Shivani Agarwal, Thore Graepel, Ralf Herbrich, Sariel Har-Peled and Dan Roth. Generalization bounds for the area under the ROC curve. Journal of
Machine Learning Research, 6:393-425, 2005.
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