- D. Petkovic, M. Sosnick-Pérez, K. Okada, R. Todtenhoefer, S. Huang, N. Miglani, A. Vigil: “Using the Random Forest Classifier to Assess and Predict Student Learning of Software Engineering Teamwork” Proc. of Frontiers in Education FIE 2016, Erie, PA, 2016
- Dragutin Petkovic: “Using Learning Analytics to Assess Capstone Project Teams”, IEEE Computer, Issue No.01 - Jan. (2016 vol.49). (invited)
- Dragutin Petkovic, Marc Sosnick-Pérez, Shihong Huang, Rainer Todtenhoefer, Kazunori Okada, Swati Arora, Ramasubramanian Sreenivasen, Lorenzo Flores, Sonal Dubey: “SETAP: Software Engineering Teamwork Assessment and Prediction Using Machine Learning”, Proc. FIE 2014, Madrid, Spain 2014
- L. Buturovic, M. Wong, G. Tang, R. Altman, D. Petkovic: “High precision prediction of functional sites in protein structures”, PLoS ONE 9(3): e91240. doi:10.1371/journal.pone.0091240
- PI of collaborative NSF TUES grant 1140172 “ Transforming the Understanding, Assessment and Prediction of Teamwork Effectiveness in Software Engineering Education using Machine Learning”. Includes joint teaching and research on global SW engineering with co-PIs Prof. R. Todtenhoefer (Fulda, Germany), and Shihong Huang (FAU, Florida) , ongoing.
SFSU PI of NIH sub-grant U54EB020405 “Mobility Data Integration to Insight”, Stanford, PI Prof. S. Delp, $35 K direct costs/year, for four years, 2015-2019.
SFSU PI of NIH sub-grant 2R01LM005652-19A1 (main PI Prof. R. Altman, Stanford University): :”Text Mining for High-fidelity Curation and Discovery of Gene-drug-phenotype Relationships “. Engaged in SW Engineering, usability and data management aspects, with one SFSU co-PI, CCLS research staff and SFSU graduate students, 2016-2020