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Zoran Obradovic

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Zoran Obradovic

  • College of Science and Technology

    • Computer and Information Sciences

      • Laura H. Carnell Professor

Biography

Zoran Obradovic is L.H. Carnell Professor of Data Analytics at Temple University, Professor in the Department of Computer and Information Sciences with a secondary appointment in Statistics, and is the Director of the Center for Data Analytics and Biomedical Informatics. He is an Academician at the Academia Europaea (link is external) (the Academy of Europe) and a Foreign Academician at the Serbian Academy of Sciences and Arts (link is external). He is the executive editor at the journal on Statistical Analysis and Data Mining, which is the official publication of the American Statistical Association and is an editorial board member at eleven journals. He was the chair at the SIAM Activity Group on Data Mining and Analytics for 2014 and 2015 years, was co-chair for 2013 and 2014 SIAM International Conference on Data Mining and was the program or track chair at many data mining and biomedical informatics conferences. His work is published in more than 300 articles and is cited more than 15,000 times (H-index 48).

Research interests: Data mining, Biomedical informatics

Courses Taught

Number

Name

Level

CIS 4523

Knowledge Discovery and Data Mining

Undergraduate

CIS 4524

Analysis and Modeling of Social and Information Networks

Undergraduate

CIS 5523

Knowledge Discovery and Data Mining

Graduate

CIS 5524

Analysis and Modeling of Social and Information Networks

Graduate

Selected Publications

Recent

  • Zhao, B., Katuwawala, A., Oldfield, C., Dunker, A., Faraggi, E., Gsponer, J., Kloczkowski, A., Malhis, N., Mirdita, M., Obradovic, Z., Söding, J., Steinegger, M., Zhou, Y., & Kurgan, L. (2021). DescribePROT: Database of amino acid-level protein structure and function predictions. Nucleic Acids Research, 49(D1), D298-D308. doi: 10.1093/nar/gkaa931.

  • Alshehri, J., Stanojevic, M., Dragut, E., & Obradovic, Z. (2021). Stay on Topic, Please: Aligning User Comments to the Content of a News Article. In doi: 10.1007/978-3-030-72113-8_1.

  • Baembitov, R., Dokic, T., Kezunovic, M., Hu, Y., & Obradovic, Z. (2021). Fast extraction and characterization of fundamental frequency events from a large PMU dataset using big data analytics. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January, 3195-3204.

  • Ljubic, B., Pavlovski, M., Roychoudhury, S., Neste, C.V., Salhi, A., Essack, M., Bajic, V., & Obradovic, Z. (2021). Genes and comorbidities of thyroid cancer. Informatics in Medicine Unlocked, 25. doi: 10.1016/j.imu.2021.100680.

  • Hai, A., Dokic, T., Pavlovski, M., Mohamed, T., Saranovic, D., Alqudah, M., Kezunovic, M., & Obradovic, Z. (2021). Transfer Learning for Event Detection from PMU Measurements with Scarce Labels. IEEE Access, 9, 127420-127432. doi: 10.1109/ACCESS.2021.3111727.

  • Saranovic, D., Pavlovski, M., Power, W., Stojkovic, I., & Obradovic, Z. (2021). Interception of automated adversarial drone swarms in partially observed environments. Integrated Computer-Aided Engineering, 28(4), 335-348. doi: 10.3233/ICA-210653.

  • Pavlovski, M., Alqudah, M., Dokic, T., Hai, A., Kezunovic, M., & Obradovic, Z. (2021). Hierarchical Convolutional Neural Networks for Event Classification on PMU Measurements. IEEE Transactions on Instrumentation and Measurement, 70. doi: 10.1109/TIM.2021.3115583.

  • Kezunovic, M., Pinson, P., Obradovic, Z., Grijalva, S., Hong, T., & Bessa, R. (2020). Big data analytics for future electricity grids. Electric Power Systems Research, 189. doi: 10.1016/j.epsr.2020.106788.

  • Ljubic, B., Roychoudhury, S., Cao, X., Pavlovski, M., Obradovic, S., Nair, R., Glass, L., & Obradovic, Z. (2020). Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction. Computer Methods and Programs in Biomedicine, 197. doi: 10.1016/j.cmpb.2020.105765.

  • Ljubic, B., Hai, A., Stanojevic, M., Diaz, W., Polimac, D., Pavlovski, M., & Obradovic, Z. (2020). Predicting complications of diabetes mellitus using advanced machine learning algorithms. Journal of the American Medical Informatics Association, 27(9), 1343-1351. doi: 10.1093/jamia/ocaa120.

  • Pavlovski, M., Gligorijevic, J., Stojkovic, I., Agrawal, S., Komirishetty, S., Gligorijevic, D., Bhamidipati, N., & Obradovic, Z. (2020). Time-Aware User Embeddings as a Service. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 3194-3202. doi: 10.1145/3394486.3403371.

  • Asadi, N., Wang, Y., Olson, I., & Obradovic, Z. (2020). A heuristic information cluster search approach for precise functional brain mapping. Human Brain Mapping, 41(9), 2263-2280. doi: 10.1002/hbm.24944.

  • Zhou, F., Gillespie, A., Gligorijevic, D., Gligorijevic, J., & Obradovic, Z. (2020). Use of disease embedding technique to predict the risk of progression to end-stage renal disease. Journal of Biomedical Informatics, 105. doi: 10.1016/j.jbi.2020.103409.

  • Ljubic, B., Pavlovski, M., Alshehri, J., Roychoudhury, S., Bajic, V., Neste, C.V., & Obradovic, Z. (2020). Comorbidity network analysis and genetics of colorectal cancer. Informatics in Medicine Unlocked, 21. doi: 10.1016/j.imu.2020.100492.

  • Alqudah, M., Dokic, T., Kezunovic, M., & Obradovic, Z. (2020). Prediction of solar radiation based on spatial and temporal embeddings for solar generation forecast. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-January, 2971-2980.

  • He, L., Han, C., Mukherjee, A., Obradovic, Z., & Dragut, E. (2020). On the dynamics of user engagement in news comment media. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(1). doi: 10.1002/widm.1342.

  • Power, W., Pavlovski, M., Saranovic, D., Stojkovic, I., & Obradovic, Z. (2020). Autonomous Navigation for Drone Swarms in GPS-Denied Environments Using Structured Learning. IFIP Advances in Information and Communication Technology, 584 IFIP, 219-231. doi: 10.1007/978-3-030-49186-4_19.

  • Gillespie, A., Gardiner, H., Fink, E., Reese, P., Gadegbeku, C., & Obradovic, Z. (2020). Does sex, race, and the size of a kidney transplant candidate's social network affect the number of living donor requests? A multicenter social network analysis of patients on the kidney transplant waitlist. Transplantation, 2632-2641. doi: 10.1097/TP.0000000000003167.

  • Cao, X., Han, C., Glass, L., Kindman, A., & Obradovic, Z. (2019). Time-to-event estimation by re-defining time. Journal of Biomedical Informatics, 100. doi: 10.1016/j.jbi.2019.103326.

  • Obradovic, Z. (2019). Editorial Message. Big Data, 7(4), 216-217. doi: 10.1089/big.2019.29033.zob.

  • Albarakati, N. & Obradovic, Z. (2019). Multi-domain and multi-view networks model for clustering hospital admissions from the emergency department. International Journal of Data Science and Analytics, 8(4), 385-403. doi: 10.1007/s41060-018-0147-5.

  • Obradovic, Z. (2019). Editorial Message. Big Data, 7(3), 1139. doi: 10.1089/big.2019.29031.zob.

  • Gligorijevic, J., Gligorijevic, D., Stojkovic, I., Bai, X., Goyal, A., & Obradovic, Z. (2019). Deeply supervised model for click-through rate prediction in sponsored search. Data Mining and Knowledge Discovery, 33(5), 1446-1467. doi: 10.1007/s10618-019-00625-3.

  • Stanojevic, M., Alshehri, J., & Obradovic, Z. (2019). Surveying public opinion using label prediction on social media data. Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, 188-195. doi: 10.1145/3341161.3342861.

  • Gligorijevic, J., Gligorijevic, D., Pavlovski, M., Milkovits, E., Glass, L., Grier, K., Vankireddy, P., & Obradovic, Z. (2019). Optimizing clinical trials recruitment via deep learning. Journal of the American Medical Informatics Association, 26(11), 1195-1202. doi: 10.1093/jamia/ocz064.

  • Asadi, N., Rege, A., & Obradovic, Z. (2019). Pattern discovery in intrusion chains and adversarial movement. 2019 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, Cyber SA 2019. doi: 10.1109/CyberSA.2019.8899391.

  • Ljubic, B., Gligorijevic, D., Gligorijevic, J., Pavlovski, M., & Obradovic, Z. (2019). Social network analysis for better understanding of influenza. Journal of Biomedical Informatics, 93. doi: 10.1016/j.jbi.2019.103161.

  • Dokic, T., Pavlovski, M., Gligorijevic, D., Kezunovic, M., & Obradovic, Z. (2019). Spatially aware ensemble-based learning to predict weather-related outages in transmission. Proceedings of the Annual Hawaii International Conference on System Sciences, 2019-January, 3484-3493.

  • Han, C., Cao, X., Stanojevic, M., Ghalwash, M., & Obradovic, Z. (2019). Temporal graph regression via structure-aware intrinsic representation learning. SIAM International Conference on Data Mining, SDM 2019, 360-368. doi: 10.1137/1.9781611975673.41.

  • Roychoudhury, S., Zhou, F., & Obradovic, Z. (2019). Leveraging subsequence-orders for univariate and multivariate time-series classification. SIAM International Conference on Data Mining, SDM 2019, 495-503. doi: 10.1137/1.9781611975673.56.

  • Stanojevic, M., Alshehri, J., Dragut, E., & Obradovic, Z. (2019). Biased News Data Inuence on Classifying Social Media Posts. CEUR Workshop Proceedings, 2411.

  • Tadic, P., Asadi, N., Popovic, N., & Obradovic, Z. (2018). Improving the Efficiency of the Support Vector Decomposition Machine. 2018 14th Symposium on Neural Networks and Applications, NEUREL 2018. doi: 10.1109/NEUREL.2018.8586993.

  • Fourati, S., Talla, A., Mahmoudian, M., Burkhart, J., Klén, R., Henao, R., Yu, T., Aydın, Z., Yeung, K., Ahsen, M., Almugbel, R., Jahandideh, S., Liang, X., Nordling, T., Shiga, M., Stanescu, A., Vogel, R., Abdallah, E., Aghababazadeh, F., Amadoz, A., Bhalla, S., Bleakley, K., Bongen, E., Borzacchielo, D., Bucher, P., Carbonell-Caballero, J., Chaudhary, K., Chinesta, F., Chodavarapu, P., Chow, R., Cokelaer, T., Cubuk, C., Dhanda, S., Dopazo, J., Faux, T., Feng, Y., Flinta, C., Guziolowski, C., He, D., Hidalgo, M., Hou, J., Inoue, K., Jaakkola, M., Ji, J., Kumar, R., Kumar, S., Kursa, M., Li, Q., Łopuszyński, M., Lu, P., Magnin, M., Mao, W., Miannay, B., Nikolayeva, I., Obradovic, Z., Pak, C., Rahman, M., Razzaq, M., Ribeiro, T., Roux, O., Saghapour, E., Saini, H., Sarhadi, S., Sato, H., Schwikowski, B., Sharma, A., Sharma, R., Singla, D., Stojkovic, I., Suomi, T., Suprun, M., Tian, C., Tomalin, L., Xie, L., Yu, X., Pandey, G., Chiu, C., McClain, M., Woods, C., Ginsburg, G., Elo, L., Tsalik, E., Mangravite, L., & Sieberts, S. (2018). A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nature Communications, 9(1). doi: 10.1038/s41467-018-06735-8.

  • Asadi, N., Rege, A., & Obradovic, Z. (2018). Analysis of adversarial movement through characteristics of graph topological ordering. 2018 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2018. doi: 10.1109/CyberSA.2018.8551361.

  • Delibašić, B., Radovanović, S., Jovanović, M., Obradović, Z., & Suknović, M. (2018). Ski injury predictive analytics from massive ski lift transportation data. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 232(3), 208-217. doi: 10.1177/1754337117728600.

  • Obradovic, Z. (2018). Editorial Message. Big Data, 6(3), 171-172. doi: 10.1089/big.2018.29027.zob.

  • Singh, L., Deshpande, A., Zhou, W., Banerjee, A., Bowers, A., Friedler, S., Jagadish, H., Karypis, G., Obradovic, Z., Vullikanti, A., & Zuo, W. (2018). NSF BIGDATA PI meeting – domain-specific research directions and data sets. SIGMOD Record, 47(3), 32-35. doi: 10.1145/3316416.3316425.

  • Cao, X., Han, C., & Obradovic, Z. (2018). Learning a dynamic-based representation for multivariate biomarker time series classifications. Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018, 163-173. doi: 10.1109/ICHI.2018.00026.

  • Gligorijevic, D., Gligorijevic, J., Raghuveer, A., Grbovic, M., & Obradovic, Z. (2018). Modeling mobile user actions for purchase recommendation using deep memory networks. 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018, 1021-1024. doi: 10.1145/3209978.3210138.

  • Obradovic, Z. (2018). Editorial Message. Big Data, 6(2), 67-68. doi: 10.1089/big.2018.29026.zob.

  • Jelisavcic, V., Stojkovic, I., Milutinovic, V., & Obradovic, Z. (2018). Fast learning of scale-free networks based on Cholesky factorization. International Journal of Intelligent Systems, 33(6), 1322-1339. doi: 10.1002/int.21984.

  • Cao, X., Obradovic, Z., & Kim, K. (2018). A simple yet effective model for zero-shot learning. Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018, 2018-January, 766-774. doi: 10.1109/WACV.2018.00089.

  • Siddiqui, S., Zhang, Y., Lloret, J., Song, H., & Obradovic, Z. (2018). Pain-Free Blood Glucose Monitoring Using Wearable Sensors: Recent Advancements and Future Prospects. IEEE Reviews in Biomedical Engineering, 11, 21-35. doi: 10.1109/RBME.2018.2822301.

  • Rege, A., Obradovic, Z., Asadi, N., Parker, E., Pandit, R., Masceri, N., & Singer, B. (2018). Predicting adversarial cyber-intrusion stages using autoregressive neural networks. IEEE Intelligent Systems, 33(2), 29-39. doi: 10.1109/MIS.2018.111145153.

  • Jordanski, M., Radovic, M., Milosevic, Z., Filipovic, N., & Obradovic, Z. (2018). Machine Learning Approach for Predicting Wall Shear Distribution for Abdominal Aortic Aneurysm and Carotid Bifurcation Models. IEEE Journal of Biomedical and Health Informatics, 22(2), 537-544. doi: 10.1109/JBHI.2016.2639818.

  • Asadi, N., Rege, A., & Obradovic, Z. (2018). Assessment of group dynamics during cyber crime through temporal network topology. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10899 LNCS, 401-407. doi: 10.1007/978-3-319-93372-6_44.

  • Pavlovski, M., Zhou, F., Arsov, N., Kocarev, L., & Obradovic, Z. (2018). Generalization-aware structured regression towards balancing bias and variance. IJCAI International Joint Conference on Artificial Intelligence, 2018-July, 2616-2622. doi: 10.24963/ijcai.2018/363.

  • Kezunovic, M., Obradovic, Z., Dokic, T., & Roychoudhury, S. (2018). Systematic framework for integration of weather data into prediction models for the electric grid outage and asset management applications. Proceedings of the Annual Hawaii International Conference on System Sciences, 2018-January, 2737-2746.

  • Negri, T., Zhou, F., Obradovic, Z., & Gonzaga, A. (2018). Extended color local mapped pattern for color texture classification under varying illumination. Journal of Electronic Imaging, 27(1). doi: 10.1117/1.JEI.27.1.011008.

  • Gligorijevic, D., Stojanovic, J., Satz, W., Stojkovic, I., Schreyer, K., Portal, D.D., & Obradovic, Z. (2018). Deep attention model for triage of emergency department patients. SIAM International Conference on Data Mining, SDM 2018, 297-305. doi: 10.1137/1.9781611975321.34.

  • Reljin, I., Obradović, Z., Popović, M., & Mladenov, V. (2018). New Methods for Analyzing Complex Biomedical Systems and Signals. Complexity, 2018. doi: 10.1155/2018/6405121.

  • Stojkovic, I. & Obradovic, Z. (2017). Predicting Sepsis Biomarker Progression under Therapy. Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2017-June, 19-24. doi: 10.1109/CBMS.2017.16.

  • Albarakati, N. & Obradovic, Z. (2017). Disease-Based Clustering of Hospital Admission: Disease Network of Hospital Networks Approach. Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2017-June, 636-641. doi: 10.1109/CBMS.2017.87.

  • Rege, A., Obradovic, Z., Asadi, N., Singer, B., & Masceri, N. (2017). A temporal assessment of cyber intrusion chains using multidisciplinary frameworks and methodologies. 2017 International Conference On Cyber Situational Awareness, Data Analytics And Assessment, Cyber SA 2017. doi: 10.1109/CyberSA.2017.8073398.

  • Vujicic, T., Glass, J., Zhou, F., & Obradovic, Z. (2017). Gaussian conditional random fields extended for directed graphs. Machine Learning, 106(9-10), 1271-1288. doi: 10.1007/s10994-016-5611-7.

  • Gillespie, A., Fink, E., Traino, H., Uversky, A., Bass, S., Greener, J., Hunt, J., Browne, T., Hammer, H., Reese, P., & Obradovic, Z. (2017). Hemodialysis Clinic Social Networks, Sex Differences, and Renal Transplantation. American Journal of Transplantation, 17(9), 2400-2409. doi: 10.1111/ajt.14273.

  • Delibasic, B., Markovic, P., Delias, P., & Obradovic, Z. (2017). Mining Skier Transportation Patterns from Ski Resort Lift Usage Data. IEEE Transactions on Human-Machine Systems, 47(3), 417-422. doi: 10.1109/THMS.2016.2633438.

  • Stojanovic, J., Gligorijevic, D., Radosavljevic, V., Djuric, N., Grbovic, M., & Obradovic, Z. (2017). Modeling healthcare quality via compact representations of electronic health records. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(3), 545-554. doi: 10.1109/TCBB.2016.2591523.

  • Glass, J. & Obradovic, Z. (2017). Structured Regression on Multiscale Networks. IEEE Intelligent Systems, 32(2), 23-30. doi: 10.1109/MIS.2017.37.

  • Radovic, M., Ghalwash, M., Filipovic, N., & Obradovic, Z. (2017). Minimum redundancy maximum relevance feature selection approach for temporal gene expression data. BMC Bioinformatics, 18(1). doi: 10.1186/s12859-016-1423-9.

  • Negri, T., Zhou, F., Obradovic, Z., & Gonzaga, A. (2017). A robust descriptor for color texture classification under varying illumination. VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 4, 378-388. doi: 10.5220/0006143403780388.

  • Brzan, P., Obradovic, Z., & Stiglic, G. (2017). Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patients. PeerJ, 2017(4). doi: 10.7717/peerj.3230.

  • Rege, A., Obradovic, Z., Asadi, N., Parker, E., Masceri, N., Singer, B., & Pandit, R. (2017). Using a real-time cybersecurity exercise case study to understand temporal characteristics of cyberattacks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10354 LNCS, 127-132. doi: 10.1007/978-3-319-60240-0_16.

  • Pavlovski, M., Zhou, F., Stojkovic, I., Kocarev, L., & Obradovic, Z. (2017). Adaptive Skip-Train Structured Regression for Temporal Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10535 LNAI, 305-321. doi: 10.1007/978-3-319-71246-8_19.

  • Stojkovic, I., Ghalwash, M., & Obradovic, Z. (2017). Ranking Based Multitask Learning of Scoring Functions. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10535 LNAI, 721-736. doi: 10.1007/978-3-319-71246-8_44.

  • Roychoudhury, S., Ghalwash, M., & Obradovic, Z. (2017). Cost Sensitive Time-Series Classification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10535 LNAI, 495-511. doi: 10.1007/978-3-319-71246-8_30.

  • Stojkovic, I., Jelisavcic, V., Milutinovic, V., & Obradovic, Z. (2017). Fast sparse Gaussian Markov Random fields learning based on Cholesky factorization. IJCAI International Joint Conference on Artificial Intelligence, 2758-2764. doi: 10.24963/ijcai.2017/384.

  • Stojkovic, I. & Obradovic, Z. (2017). Sparse Learning of the Disease Severity Score for High-Dimensional Data. Complexity, 2017. doi: 10.1155/2017/7120691.

  • Han, C., Ghalwash, M., & Obradovic, Z. (2017). Continuous conditional dependency network for structured regression. 31st AAAI Conference on Artificial Intelligence, AAAI 2017, 1962-1968.