Shantanu Jain
(he/him/his)
Associate Research Scientist
Research interests
- Machine learning
- Artificial intelligence
- Data science
- Statistics
Education
- PhD in Computer Science, Indiana University
- MS in Computer Science, Indiana University
- MS in Applied Statistics, Indiana University
- B-Tech in Computer Engineering, Nirma University — India
Biography
Shantanu Jain is an associate research scientist in the Khoury College of Computer Sciences at Northeastern University. He is interested in the field of statistical modeling and machine learning. Jain’s research focuses on developing semi-supervised methods under data constraints for which standard approaches lead to biased estimates.
Prior to joining Northeastern in 2018, Jain received his doctorate and master’s in computer science from Indiana University. His recent work has addressed issues in binary classification and its evaluation that arise due to the absence of labeled examples from one of the classes (positive-unlabeled learning) and incorrectly labeled examples and bias in the labeled examples. Jain’s research has been applied to many bioinformatics problems and mass spectrometry data, as well as published in journals including AAAI, Pacific Symposium on Biocomputing, and the Scandinavian Journal of Statistics. Outside of research, Jain enjoys solving puzzles, singing, and dancing.
Recent publications
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Class Prior Estimation with Biased Positives and Unlabeled Examples
Citation: Jain S, Delano J, Sharma H, Radivojac P. Class Prior Estimation with Biased Positives and Unlabeled Examples. In Proceedings of the AAAI Conference on Artificial Intelligence 2020 Apr 3 (Vol. 34, No. 04, pp. 4255-4263). doi:10.1609/aaai.v34i04.5848 -
Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies
Citation: Ramola R, Jain S, Radivojac P. Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies. Pac. Symp. Biocomput. (2019) 24: 124-135. -
Identifiability of two‐component skew normal mixtures with one known component
Citation: Jain S, Levine M, Radivojac P, Trosset MW. Identifiability of two-component skew normal mixtures with one known component. Scand. J. Stat. (2019).