Dragutin Petkovic

Contact Information

1. D. Petkovic, S. Barlaska, J. Young, R. Todtenhoefer: “From Explaining How Random Forest Classifier Predicts Learning of Software Engineering Teamwork to Guidance for Educators” Frontiers in Education FIE 2018, October 2018, San Jose CA
2. D. Petkovic (Chair), L. Kobzik, C. Re: “Workshop on Machine learning and deep analytics for biocomputing: call for better explainability”, Pacific Symposium on Biocomputing PSB 2018, Hawaii
3.  Paul Previde, Brook Thomas, Mike Wong, Emily K Mallory, Dragutin Petkovic, Russ B Altman, Anagha Kulkarni: “GeneDive: A gene interaction search and visualization tool to facilitate precision medicine”, Pacific Symposium on Biocomputing PSB 2018, Hawaii
4. D. Petkovic, R. Altman, M. Wong, A. Vigil: “Improving the explainability of Random Forest classifier – user centered approach”, Pacific Symposium on Biocomputing PSB 2018, Hawaii

Awards:

1. 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.

2. 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.

3. 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