SLOBODAN VUCETIC


Professor

Department of Computer and Information Sciences
Temple University

Address:

1925 N. 12th St., 304A SERC
Philadelphia, PA 19122-6094

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


Resume


News: Ranking of the U.S. Computer Science Doctoral Programs Our new study revealed that U.S. News ranking of CS doctoral programs, which is based purely on peer assessment, is surprisingly highly correlated with faculty citations. Our resulting ranking is available here.


Research Interests

Research Areas:

Cognitive Computing

Data Science

Machine Learning

Big Data

I am interested in solving real-life knowledge discovery problems through development of novel machine learning algorithms. I am also interested in building software that has intelligent behavior and can enhance human capabilities. 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)

-       Dynamic Evolution of Smart-Phone Based Emergency Communications Network (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 2017):

-       34nd International Conference on Machine Learning (ICML)

-       23st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

-       20th International Conference on Artificial Intelligence and Statistics (AISTATS)

-       31th AAAI Conference on Artificial Intelligence (AAAI)

-       26th International Joint Conference on Artificial Intelligence (IJCAI)

-       (reviewer) 2017 Neural Information Processing Systems Conference (NIPS)

-       2017 IEEE International Conference on Data Mining 2017 (ICDM)

-       26th ACM International Conference on Information and Knowledge Management (CIKM)

-       2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

-       2017 IEEE International Conference on Big Data (BigData)


Recent Representative Publications (check the complete list with preprints)

-      Vucetic, S., Chanda, A.K., Zhang, S., Bai, T., Maiti, A., Peer Assessment of CS Doctoral Programs Shows Strong Correlation with Faculty Citations, Communications of the ACM, 61:09, 70-77, 2018.

-      Bai, T., Chanda, A.K., Egleston, B.L., Vucetic, S., EHR Phenotyping via Jointly Embedding Medical Concepts and Words into a Unified Vector Space, BMC Medical Informatics and Decision Making, 2018.

-      Bai, T., Zhang, S., Egleston, B.L., Vucetic, S., Interpretable Representation Learning for Healthcare via Capturing Disease Progression through Time, KDD, 43-51, 2018.

-      Zhang, S., He, L., Vucetic, S., Dragut, E., Regular Expression Guided Entity Mention Mining from Noisy Web Data, EMNLP, 2018


Students

Current Students:

Shanshan Zhang (Ph.D.)

Tian Bai (Ph.D.)

Aniruddha Maiti (Ph.D.)

Maxim Shapovalov (Ph.D.)

Ashis Chanda (Ph.D.)

Saman Enayati (Ph.D.)

Ziyu Yang (Ph.D.)

Sandro Hauri (Ph.D.)

Shi Kai Fang (M.S.)

Phong The Ha (undergraduate)

Kevin Esslinger (undergraduate)

Hoang Nguyen Khanh Ho (undergraduate)

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, current: Airbnb)

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 self-motivated graduate students interested in machine learning, cognitive computing, 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 2018: Machine Learning (CIS 5526)

Spring 2018: Principles of Data Science (CIS 3715)

Spring 2017: Principles of Data Science (CIS 3715)

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)