SLOBODAN VUCETIC


Associate Professor

 

Address:

Department of Computer and Information Sciences
Center for Data Analytics and Biomedical Informatics
Temple University
1805 N. Broad Street, 304 Wachman Hall
Philadelphia, PA 19122-6094

Telephone: (215) 204-5535
Fax: (215) 204-5082
Email: vucetic ( at ) temple.edu
Office: 304 Wachman Hall


Resume


Research Interests

Research Areas:

Data Mining

Machine Learning

Big Data

I am interested in solving real-life knowledge discovery and statistical analysis problems through development of novel machine learning algorithms. My research is driven by open big data analytics problems in a wide array of disciplines such as

Healthcare, Epidemiology, Biology, Geosciences, Education, Marketing, Social Networks and Crowdsourcing, Finance, Traffic Engineering, Industrial Engineering, Power Systems. 

Research Highlights:

-         CAREER award from National Science Foundation

-         Outstanding paper at IJCAI 2013: Best paper in the AI and Computational Sustainability Track

-         Leader of one of the top performing teams at CAFA/AFP 2011 Protein Function Prediction Assessment

-         Member of a team with the best protein disorder predictor at CASP 5, CASP 6, and CASP 7 Protein Structure Prediction Assessment 

Representative Funded Research Projects:

-         Discriminative Modeling of Spatial-Temporal Data in Remote Sensing (funded by National Science Foundation)

-         Computational Advertising (supported by Yahoo! Faculty Research and Engagement Program)

-         Memory-Constrained Predictive Data Mining (funded by National Science Foundation)

-         Machine Learning for Distributed Fault Diagnosis (supported by ExxonMobil)

-         Bioinformatics - Genomics, Analysis of Protein Disorder, Proteomics, Biomedical Text Mining (funded by Pennsylvania Department of Health, NIH

Program Committee member (in 2014):

-       31th International Conference on Machine Learning (ICML), Beijing, China, June 21-26, 2014.

-       20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), New York City, NY, USA, August 24-27, 2014.

-       17th International Conference on Artificial Intelligence and Statistics (AISTATS), Reykjavik, Iceland, April 22-25, 2014.

-       (reviewer) 2014 Neural Information Processing Systems Conference (NIPS), Montreal, Canada, December 8-13, 2014.

-       (Local and Ph.D. Forum Chair) SIAM International Conference on Data Mining (SDM), Philadelphia, PA, USA, April 22-24, 2014.

-       2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, Canada, July 13-18, 2014.

-       2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Belfast, UK, November 2-5, 2014.

-       6th International Conference on Information Visualization Theory and Applications (IVAPP), Berlin, Germany, March 11-14, 2015.

-       6th International Conference on knowledge Discovery and information retrieval (KDIR), Rome, Italy, October 21-24, 2014.


Recent Selected Publications (check the complete list with preprints)

-       Lan, L., Malbasa, V., Vucetic, S., Spatial Scan for Disease Mapping on a Mobile Population, 28th AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, 2014.

-       Djuric, N., Grbovic, M., Radosavljevic, V., Bhamidipati, N., Vucetic, S., Non-linear Label Ranking for Large-scale Prediction of Long-Term User Interests, 28th AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, 2014.

-       Grbovic M., Vucetic S., Generating Ad Targeting Rules using Sparse Principal Component Analysis with Constraints, International World Wide Web Conference (WWW), Seoul, South Korea, 2014.

-       Zhang, K., Lan, L., Kwok, T.J., Vucetic, S., Parvim, B., Large Scale Semi-Supervised Learning via Sparse Nonparametric Prototype Model, IEEE Transactions on Neural Networks and Learning Systems, in press, 2014.

-       Coric, V., Djuric, N., Vucetic, S., Frugal Traffic Monitoring with Autonomous Participatory Sensing, SIAM Conference on Data Mining (SDM), Philadelphia, PA, 2014.

-       Djuric, N., Lan, L., Vucetic, S., Wang, Z., BudgetedSVM: A Toolbox for Scalable SVM Approximations, Journal of Machine Learning Research (JMLR), 2013. BudgetedSVM web site

-       Djuric, N., Vucetic, S., Efficient Visualization of Large-scale Data Tables through Reordering and Entropy Minimization, IEEE International Conference on Data Mining (ICDM), Dallas, TX, 2013.

-       Djuric, N., Kansakar, L., Vucetic, S., Semi-Supervised Learning for Integration of Aerosol Predictions from Multiple Satellite Instruments, 23rd International Joint Conference on Artificial Intelligence (IJCAI),, Beijing, China, 2013. (Outstanding IJCAI paper: the best paper in the AI and Computational Sustainability Track)

-       Grbovic, M., Djuric, N., Vucetic, S., Multi-Prototype Label Ranking with Novel Pairwise to Total Rank Aggregation, 23rd International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013.

-       Ristovski, K., Radosavljevic, V., Vucetic, S., Obradovic, Z., Continuous Conditional Random Fields for Efficient Regression in Large Fully Connected Graphs, 27th AAAI Conference on Artificial Intelligence (AAAI), Bellevue, WA, 2013.

-       Grbovic M., Djuric, N., Guo, S., Vucetic S., Supervised Clustering of Label Ranking Data using Label Preference Information, Machine Learning Journal (MLJ), 2013.

-       Grbovic M., Li W., Subrahmanya N. A., Usadi A. K., Vucetic S., Cold Start Approach for Data Driven Fault Detection, IEEE Transactions on Industrial Informatics, 2013.

-       Lan, L., Djuric, N., Guo, Y., Vucetic, S., MS-kNN: Protein Function Prediction by Integrating Multiple Data Sources, BMC Bioinformatics, 2013. (reporting about our CAFA/AFP 2011 participation where we were one of the top performing teams; we are among co-authors of a joint CAFA paper: Radivojac, P., ..., Lan, L., Djuric, N., Guo, Y., Vucetic, S., ... Friedberg, I., A Large-scale Evaluation of Computational Protein Function Prediction, Nature Methods, 2013.)

-       Wang, Z., Crammer, K., Vucetic, S., Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training, Journal of Machine Learning Research (JMLR), 2012.

-       Grbovic, M., Dance, C., Vucetic, S., Sparse Principal Component Analysis with Constraints, AAAI Conference on Artificial Intelligence (AAAI), Toronto, Canada, 2012.

-       Djuric, N., Grbovic, M., Vucetic, S., Convex Kernelized Sorting, AAAI Conference on Artificial Intelligence (AAAI), Toronto, Canada, 2012.

-       Wang, Z., Lan, L. Vucetic, S., Mixture Model for Multiple Instance Regression and Applications in Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing (TGARS), 2012.

-       Ristovski, K., Vucetic, S., Obradovic, Z., Uncertainty Analysis of Neural Network-Based Aerosol Retrieval, IEEE Transactions on Geoscience and Remote Sensing (TGARS), 2012.

-       Grbovic, M., Djuric N., Vucetic S., Supervised Clustering of Label Ranking Data, SIAM Conf. on Data Mining (SDM), Anaheim, CA, 2012 (Best of SDM 2012: a top 10 paper).

-       Wang, Z., Djuric, N., Crammer, K. Vucetic, S., Trading Representability for Scalability: Adaptive Multi-Hyperplane Machine for Nonlinear Classification, ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD), San Diego, CA, 2011. (link to software)

-       Malbasa, V., Vucetic., S., Spatially Regularized Logistic Regression for Disease Mapping on Large Moving Population, ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD), San Diego, CA, 2011.


Students

Current Students:

Vladimir Coric (Ph.D.)

Lakesh Kansakar (Ph.D.)

Shanshan Zhang (Ph.D.)

Marko Milosevic (Ph.D.)

Graduated Ph.D. Students:

Nemanja Djuric (Ph.D., 2013, first position: Research Scientist, Yahoo! Labs)

Liang Lan (Ph.D., 2012, first position: Research Scientist, Huawei Noah Ark Lab)

Mihajlo Grbovic (Ph.D., 2012, first position: Research Scientist, Yahoo! Labs)

Vuk Malbasa (Ph.D., 2011, first position: Postdoctoral Associate, Texas A&M University)

Zhuang Wang (Ph.D., 2010, first position: Research Scientist, Siemens Corporate Research)

For Prospective Students:

I am interested in mentoring highly motivated graduate students interested in machine learning and data mining. Interested students are encouraged to contact me by e-mail. Please, send me your CV and write a short description about your academic background and research interests.


Teaching (since 2010)

Fall 2013: Introduction to Computer Science (CIS1001)

Fall 2013: Machine Learning (CIS 8526)

Spring 2013: Introduction to Computer Science (CIS1001)

Spring 2013: Mathematical Concepts in Computing II (CIS2166)

Fall 2012: Introduction to Computer Science (CIS1001)

Spring 2012: Introduction to Computer Science (CIS1001)

Spring 2012: Mathematical Concepts in Computing II (CIS2166)

Fall 2011: Machine Learning (CIS8526)

Spring 2011: Data Mining (CIS4350).

Fall 2010: Machine Learning (CIS8526)

Spring 2010: Introduction to Computer Science (CIS1001)