Professor of Computer Science
Adjunct Professor of Statistics
Department of Computer Science
700 North Woodlawn Avenue
Bloomington, IN 47408
Office: Luddy Hall 2048 ☀️
Phone: (812) 856-1851
Download my curriculum vitae in pdf format (last updated on 12/23/2017). Google Scholar profile.
- i. ☀️ (January 2018) Shantanu’s identifiability paper for skew normal distributions posted on arXiv.
- ii. ☀️ (December 2017) Shawn’s and Yuxiang’s paper on calculating cardinality of ontological output spaces posted on arXiv.
- iii. ☀️ (December 2017) Our feature selection paper with Makoto Yamada as lead accepted to TKDE. The paper is available on arXiv.
- iv. ☀️ (December 2017) Ruiyu defends Ph.D. thesis. Congratulations!
- v. ☀️ (November 2017) Pedja gives a keynote at IEEE BIBM.
- vi. (October 2017) Indiana University is hiring faculty in computational systems biology and other areas related to precision medicine and health. See the ad here.
- vii. (October 2017) Pedja gives a keynote at the HGVS/ASHG meeting on predicting molecular mechanisms of disease.
- viii. (July 2017) Kym receives Ian Lawson Van Toch Memorial Award at ISMB 2017.
- ix. (July 2017) Pedja re-elected to the ISCB Board of Directors.
- x. (July 2017) The Function SIG meeting featuring CAFA results to take place on July 24-25 during ISMB 2017.
Awards and Honors
August-Wilhelm Scheer Visiting Professor at Technical University of Munich, 2016-2017
Senior Member, International Society for Computational Biology, 2015
National Science Foundation CAREER Award, 2007
Outstanding Young Researcher, University of Novi Sad, 1998
Board of Directors Member, International Society for Computational Biology (ISCB), 2012-
Associate Editor, PLoS Computational Biology, 2014-
Editorial Board Member, Bioinformatics, Oxford University Press, 2010-
Bioinformatics and Computational Biology
- • Protein structure and function; method development and evaluation of function prediction
- • Post-translational modifications (PTMs)
- • Mass spectrometry (MS) and MS/MS proteomics
- • Understanding and predicting molecular mechanisms of disease
- • Genome interpretation
- • Precision medicine and precision health
- • Supervised and semi-supervised learning: learning from positive and unlabeled data; learning from biased data
- • Structured-output learning and evaluation; extreme classification
- • Kernel-based inference on sequences, time-series, and graphs
Last updated: January 20, 2018