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DIAL Publications

2014

  1. Everaldo Aguiar, G. Alex Ambrose, Nitesh V. Chawla, Victoria E. Goodrich, and Jay B. Brockman. “Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Persistence.” Journal of Learning Analytics, 1(3):7–33, 2014. PDF
  2. Yang Yang, Yuxiao Dong, and Nitesh V. Chawla. “Predicting Node Degree Centrality with Node Prominence Profile.” Scientific Reports, 4:7236, 2014. PDF SUPP
  3. Keith Feldman and Nitesh V. Chawla. “Admission Duration Model for Infant Treatment (ADMIT).” Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 583–587, 2014. PDF
  4. Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, and Nitesh V. Chawla. “Inferring User Demographics and Social Strategies in Mobile Social Networks.” Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 15–24, 2014. PDF
  5. Jian Xu, Thanuka L. Wickramarathne, Nitesh V. Chawla, Erin K. Grey, Karsten Steinhaeuser, Reuben P. Keller, John M. Drake, and David M. Lodge. “Improving Management of Aquatic Invasions by Integrating Shipping Network, Ecological and Environmental Data: Data Mining for Social Good.” Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1699–1708, 2014. PDF
  6. Thanuka L. Wickramarathne, Kamal Premaratne, Manohar Murthi, and Nitesh V. Chawla. “Convergence Analysis of Iterated Belief Revision in Complex Fusion Environments.” IEEE Journal of Selected Topics in Signal Processing (J-STSP), 8(4):598–612, 2014. PDF
  7. Andrew K. Rider, Tijana Milenković, Geoffrey H. Siwo, Richard S. Pinapati, Scott J. Emrich, Michael T. Ferdig, and Nitesh V. Chawla. “Networks’ Characteristics are Important for Systems Biology.” Network Science, 2(02):139–161, 2014. PDF SUPP
  8. Dipanwita Dasgupta and Nitesh V. Chawla. “Disease and Medication Networks: An Insight into Disease-Drug Interactions.” Proceedings of the 2nd International Conference on Big Data Analytics in Healthcare (BDAH), 2014. PDF
  9. Keith Feldman and Nitesh V. Chawla. “Scaling Personalized Healthcare with Big Data.” Proceedings of the 2nd International Conference on Big Data Analytics in Healthcare (BDAH), 2014. PDF
  10. Andrea Dal Pozzolo, Reid A. Johnson, Olivier Caelen, Serge Waterschoot, Nitesh V. Chawla, and Gianluca Bontempi. “Using HDDT to Avoid Instances Propagation in Unbalanced and Evolving Data Streams.” Proceedings of the 24th International Joint Conference on Neural Networks (IJCNN), pp. 588–594, 2014. PDF
  11. Victoria E. Goodrich, Everaldo Aguiar, G. Alex Ambrose, Leo H. McWilliams, Jay B. Brockman, and Nitesh V. Chawla. “Integration of ePortfolios in a First-Year Engineering Course for Measuring Student Engagement.” Proceedings of the American Society for Engineering Education Annual Conference (ASEE), pp. 24.785.1–24.785.16, 2014. PDF
  12. Dipanwita Dasgupta, Keith Feldman, Disha Waghray, W. A. Mikels-Carrasco, Patty Willaert, Debra A. Raybold, and Nitesh V. Chawla. “An Integrated and Digitized Care Framework for Successful Aging.” Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 440–443, 2014. PDF
  13. Everaldo Aguiar, Nitesh V. Chawla, Jay B. Brockman, G. Alex Ambrose, and Victoria E. Goodrich. “Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Retention.” Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK), pp. 103–112, 2014. PDF
  14. Ryan N. Lichtenwalter and Nitesh V. Chawla. “Vertex Collocation Profiles: Theory, Computation, and Results.” SpringerPlus, 3(1):116, 2014. PDF
  15. Andrew K. Rider, Geoffrey H. Siwo, Scott J. Emrich, Michael T. Ferdig, and Nitesh V. Chawla. “A Supervised Learning Approach to the Ensemble Clustering of Genes.” International Journal of Data Mining and Bioinformatics (IJDMB), 9(2):199–219, 2014. PDF

2013

  1. Saurav Pandit, Jonathan Koch, Yang Yang, Brian Uzzi, and Nitesh V. Chawla. “Red Black Network: Temporal and Topological Analysis of Two Intertwined Social Networks.” Proceedings of the 32nd Annual International Conference for Military Communications (MILCOM), pp. 719–724, 2013. PDF
  2. Pablo Meyer, Geoffrey H. Siwo, Danny Zeevi, Eilon Sharon, Raquel Norel, DREAM6 Promoter Prediction Consortium, Eran Segal, and Gustavo Stolovitzky. “Inferring Gene Expression from Ribosomal Promoter Sequences, A Crowdsourcing Approach.” Genome Research, 23(11):1928–1937, 2013. PDF SUPP
  3. Andrew K. Rider, Reid A. Johnson, Darcy A. Davis, T. Ryan Hoens, and Nitesh V. Chawla. “Classifier Evaluation with Missing Negative Class Labels.” Advances in Intelligent Data Analysis XII (IDA), pp. 380–391, 2013. PDF
  4. Nathan Regola, David A. Cieslak, and Nitesh V. Chawla. “The Need to Consider Hardware Selection When Designing Big Data Applications Supported by Metadata.” Big Data Management, Technologies, and Applications, pp. 381–396, 2013. PDF
  5. Yuxiao Dong, Jie Tang, Tiancheng Lou, Bin Wu, and Nitesh V. Chawla. “How Long Will She Call Me? Distribution, Social Theory and Duration Prediction.” Proceedings of the 24th European Conference on Machine Learning and the 17th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 16–31, 2013. PDF
  6. Andrew K. Rider and Nitesh V. Chawla. “An Ensemble Topic Model for Sharing Healthcare Data and Predicting Disease Risk.” Proceedings of the ACM Conference on Bioinformatics, Computational Biology, and Biomedical Informatics (ACM-BCB), pp. 333–340, 2013. PDF
  7. Nitesh V. Chawla and Darcy A. Davis. “Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework.” Journal of General Internal Medicine (JGIM), 28(3):660–665, 2013. PDF
  8. T. Ryan Hoens, Marina Blanton, Aaron Steele, and Nitesh V. Chawla. “Reliable Medical Recommendation Systems with Patient Privacy.” ACM Transactions on Intelligent Systems and Technology (TIST), 4(4):67, 2013. PDF
  9. Andrew K. Rider, Nitesh V. Chawla, and Scott J. Emrich. “A Survey of Current Integrative Network Algorithms for Systems Biology.” Systems Biology, pp. 479–495, 2013. PDF
  10. Yang Yang, Nitesh V. Chawla, Prithwish Basu, Bhaskar Prabhala, and Thomas La Porta. “Link Prediction in Human Mobility Networks.” Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 380–387, 2013. PDF
  11. Darcy A. Davis, Ryan N. Lichtenwalter, and Nitesh V. Chawla. “Supervised Methods for Multi-Relational Link Prediction.” Social Networks Analysis and Mining (SNAM), 3(2):127–141, 2013. PDF
  12. T. Ryan Hoens and Nitesh V. Chawla. “Imbalanced Datasets: From Sampling to Classifiers.” Imbalanced Learning: Foundations, Algorithms, and Applications, pp. 43–59, 2013. PDF
  13. Robert Thompson and Nitesh V. Chawla. “Addressing Challenges in Prescription Management.” Proceedings of the 24th Annual Conference of the Production and Operations Management Society (POMS), no. 1610, 2013. PDF
  14. Yang Yang, Nitesh V. Chawla, Xiaohui Lu, and Sibel Adal. “Prominence in Networks: A Co-evolving Process.” Proceedings of the 2nd IEEE International Network Science Workshop (NSW), pp. 58–65, 2013. PDF
  15. Rachael Purta, Saurabh Nagrecha, and Gregory Madey. “Multi-hop Communications in a Swarm of UAVs.” Proceedings of the Agent-Directed Simulation Symposium (ADSS), no. 5, 2013. PDF
  16. Cheng Wang, Omar Lizardo, David Hachen, Anthony Strathman, Zoltán Toroczkai, and Nitesh V. Chawla. “A Dyadic Reciprocity Index for Repeated Interaction Networks.” Network Science, 1(01):31–48, 2013. PDF
  17. Nathan Regola and Nitesh V. Chawla. “Storing and Using Health Data in a Virtual Private Cloud.” Journal of Medical Internet Research (JMIR), 15(3):e63, 2013. PDF SUPPYang Yang, Yizhou Sun, Saurav Pandit, Nitesh V. Chawla, and Jiawei Han. “Perspective on Measurement Metrics for Community Detection Algorithms.” Mining Social Networks and Security Informatics, pp. 227–242, 2013. PDF
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