Professor of Computer Science
Associate Dean of Research
Khoury College of Computer Sciences
Northeastern University
177 Huntington Avenue
Boston, MA 02115, U.S.A.
Office: Room 908 @ 177 Huntington Avenue
Phone: (617) 373-7428
Email:..predrag@northeastern.edu.
Download my curriculum vitae in pdf format (last updated on 06/22/2022). Google Scholar profile.
Interested in working with us? We have broad research interests. Please check our selected three publications in the areas of semi-supervised learning, evaluation of machine learning algorithms, general machine learning, graphs and hypergraphs, genome interpretation, protein function, mass-spectrometry proteomics, and post-translational modifications. Also see our review papers.
Courtesy appointments. Department of Chemistry and Chemical Biology; Barnett Institute Fellow; Affiliate Faculty of the Roux Institute; Core Faculty Member of the Institute for Experiential AI.
Recent Updates
- i. ☀️ (September 2022) Three lab papers accepted to PSB 2023 and a collaborative paper with Sriraam Natarajan’s group. Congratulations to Clara, Shantanu, Hoyin, Rashika, and Dan! Great work together with David Haas, Sean Mooney, Lilia Iakoucheva, and Vikas Pejaver.
- ii. ☀️ (August 2022) Kym’s, Hoyin’s, and Rashika’s paper connecting type II diabetes polygenic score with the level of exercise to assess risk of gestational diabetes in pregnant women published in JAMA Network Open. A large collaboration, particularly with Rafael Guerrero, David Haas, Matthew Hahn, and Sriraam Natarajan. Congratulations to all!
- iii. ☀️ (August 2022) Rashika’s paper on the state of affairs in the protein function prediction field appears in Bioinformatics Advances. Congratulations Rashika!
- iv. ☀️ (June 2022) My Cell Systems article previewing a beautiful paper by Bileschi et al. from Nature Biotechnology.
- v. ☀️ (June 2022) Jose started as an Assistant Professor of Computer Science at Carnegie Mellon University. Congratulations!
- vi. (May 2022) CAGI flagship preprint posted on arXiv.
- vii. (March 2022) Our new preprint on the recommendations for the use of computational models in the clinic is now posted on bioRxiv.
- viii. (March 2022) Two new preprints posted on medRxiv describing (1) a GWAS study about adverse pregnancy outcomes and (2) interaction between genetic predisposition and physical activity in gestational diabetes.
- ix. (December 2021) The submission season for CAGI6 is closing on December 31, 2021.
- x. (September 2021) Yuxiang’s paper on prioritizing de novo autism risk variants published in Human Genetics.
- xi. (September 2021) NIH announces the IGVF Consortium. We are a part of it!
- xii. (September 2021) Vikas started as an Assistant Professor of Genetics and Genomic Sciences at Icahn School of Medicine at Mount Sinai. Congratulations!
Awards and Honors
Honorary Fellow of the Institute for Advanced Study at the Technical University of Munich, 2017
August-Wilhelm Scheer Visiting Professor at Technical University of Munich, 2016
Senior Member, International Society for Computational Biology, 2015
National Science Foundation CAREER Award, 2007
Outstanding Young Researcher, University of Novi Sad, 1998
Major Student Awards
Kymberleigh Pagel, Ian Lawson Van Toch Memorial Award, ISMB/ECCB 2017
Wyatt Clark, Ian Lawson Van Toch Memorial Award, ISMB/ECCB 2013
Professional Activities
President-elect, International Society for Computational Biology (ISCB), 2023-
Board of Directors Member, International Society for Computational Biology (ISCB), 2012-2021
Associate Editor, PLoS Computational Biology, 2014-2021
Editorial Board Member, Bioinformatics, Oxford University Press, 2010-
Editorial Board Member, Human Genetics, Springer, 2020-
Research Interests
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
Biomedical Informatics
- • Understanding and predicting molecular mechanisms of disease
- • Genome interpretation
- • Precision medicine and precision health
Machine Learning
- • 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: September 12, 2022