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