Publications

List of Research Papers

  • S. Muthiah, D. Datta, M. I. Raihan, P. Butler, N. Ramakrishnan, and A. Warren. ProtTox: Toxin Identification from Protein Sequences. In Machine Learning and Computational Biology (MLCB), 2019

  • N. Muralidhar, S. Muthiah, and N. Ramakrishnan. Dyat nets: Dynamic attention networks for state forecasting in cyber-physical systems. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19

  • M. R. Islam, S. Muthiah, et al. Nactseer: Predicting user actions in social network using graph augmented neural network. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM, 2019

  • M. R. Islam, S. Muthiah, and N. Ramakrishnan. RumorSleuth: Joint Detection of Rumor Veracityand User Stance. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019

  • N. Muralidhar, S. Muthiah, K. Nakayama, N. Ramakrishnan, and R. Sharma. Multivariate long-term state forecasting in cyber-physical systems: A sequence to sequence approach. Big Data, 2019

  • M. R. Islam, S. Muthiah, B. Adhikari, B. A. Prakash, and N. Ramakrishnan. Deepdiffuse: Predicting the ’who’ and ’when’ in cascades. In 2018 IEEE International Conference on Data Mining (ICDM), 2018

  • Y. Ning, S. Muthiah, N. Ramakrishnan, H. Rangwala, and D. Mares. When do crowds turn violent? uncovering triggers from media. In International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018

  • D. K. Gupta, S. Muthiah, D. Mares, and N. Ramakrishnan. Forecasting Civil Strife: An Emerging Methodology. In HUSO The Third International Conference on Human and Social Analytics, 2017

  • S. Muthiah, B. Huang, J. Arredondo, D. Mares, L. Getoor, G. Katz, and N. Ramakrishnan. Capturing planned protests from open source indicators. AI Magazine, 37(2), 2016

  • P. Chakraborty, S. Muthiah, R. Tandon, and N. Ramakrishnan. Hierarchical Quickest Change Detection via Surrogates. arXiv preprint arXiv:1603.09739, 2016

  • S. Muthiah, P. Butler, et al. Embers at 4 years: Experiences operating an open source indicators forecasting system. In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’16

  • Y. Ning, S. Muthiah, H. Rangwala, et al. Modeling precursors for event forecasting via nested multi-instance learning. In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’16

  • S. Muthiah, B. Huang, J. Arredondo, et al. Planned Protest Modeling in News and Social Media. In AAAI Conference on Artificial Intelligence, January 25-30, 2015, pages 3920–3927, 2015

  • J. Schlachter, A. Ruvinsky, L. A. Reynoso, S. Muthiah, and N. Ramakrishnan. Leveraging topic models to develop metrics for evaluating the quality of narrative threads extracted from news stories. Procedia Manufacturing, 3:4028–4035, 2015

  • Y. Ning, S. Muthiah, R. Tandon, and N. Ramakrishnan. Uncovering news-twitter reciprocity via interaction patterns. In Advances in Social Networks Analysis and Mining (ASONAM), 2015 IEEE/ACM International Conference on, 2015

  • N. Ramakrishnan, P. Butler, S. Muthiah, N. Self, et al. ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators. In International Conference on Knowledge Discovery and Data Mining, KDD, 2014

  • A. Doyle, G. Katz, K. Summers, C. Ackermann, I. Zavorin, Z. Lim, S. Muthiah, P. Butler, N. Self, L. Zhao, et al. Forecasting significant societal events using the embers streaming predictive analytics system. Big Data, 2(4):185–195, 2014