SLOBODAN VUCETIC


Associate Professor, Vice Chair

Department of Computer and Information Sciences
Temple University

Address:

1925 N. 12th St., 314 SERC
Philadelphia, PA 19122-6094

Telephone: (215) 204-5535
Fax: (215) 204-5082
Email: vucetic ( at ) temple.edu
Office: 314 SERC


Resume


Research Interests

Research Areas:

Data Mining

Machine Learning

Big Data

I am interested in solving real-life knowledge discovery problems through development of novel machine learning algorithms. My research is driven by open data science problems in a wide array of disciplines such as Public Health, Medicine, Biology, Geosciences, Education, Marketing, Social Sciences, Traffic Engineering, and Industrial Engineering. 

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 2010-12 and CAFA 2013-14 (Critical Assessment of Protein Function Annotation)

-         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:

-        Deep Learning for Representation of Medical Claims (funded by the National Institutes of Health)    

-        Space-Time Models for Health Geographic Analysis (funded by the National Science Foundation)

-        Customizing Therapy for Individuals with Autism (funded by the National Science Foundation)

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

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

-        Memory-Constrained Predictive Data Mining (funded by the 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 2015):

-       32nd International Conference on Machine Learning (ICML), Lille, France, Jul 6 - 11, 2015.

-       21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Sydney, Australia, Aug 10 - 13, 2015.

-       18th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego, USA, May 9 - 12, 2015.

-       29th AAAI Conference on Artificial Intelligence (AAAI), Austin, USA, Jan 25 - 30, 2015.

-       24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, Jul 25 - 31, 2015.

-       (reviewer) 2015 Neural Information Processing Systems Conference (NIPS), Montreal, Canada, Dec 7-12, 2015.

-       2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, Jul 26 - 31, 2015.

-       2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, USA, Nov 9 - 12, 2015.

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


Recent Representative Publications (check the complete list with preprints)

-        Djuric, N., Kansakar, L., Vucetic, S., Semi-Supervised Combination of Experts for Aerosol Optical Depth Estimation, Artificial Intelligence Journal (AIJ), 2016.

-        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, 2015.

-        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.

-       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:

Shanshan Zhang (Ph.D.)

Tian Bai (Ph.D.)

Aniruddha Maiti (Ph.D.)

Maxim Shapovalov (Ph.D.)

Graduated Ph.D. Students:

Vladimir Coric (Ph.D., 2014, first position: Lead Data Scientist, SEI Investments)

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

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

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

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

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

For Prospective Students:

I am interested in mentoring highly motivated graduate students interested in machine learning and data science. I am looking both at the traditional CS students and at the non-CS students with a strong background in mathematics (with degrees such as electrical engineering, physics, operations research, applied math, statistics). 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.


Recent Teaching

Fall 2015: Machine Learning (CIS 5526)

Fall 2015: Math Concepts in Computing I (CIS 1166)

Spring 2015: Principles of Data Science (CIS 3715)

Spring 2015: Math Concepts in Computing II (CIS 2166)

Fall 2014: Machine Learning (CIS 5526)

Fall 2013: Introduction to Computer Science (CIS1001)

Fall 2013: Machine Learning (CIS 5526)

Spring 2013: Introduction to Computer Science (CIS1001)

Spring 2013: Mathematical Concepts in Computing II (CIS2166)