Khanna, A. K., Kinoshita, T., Natarajan, A., Schwager, E., Linn, D. D., Dong, J., ... & Maheshwari, K. (2023). Association of systolic, diastolic, mean, and pulse pressure with morbidity and mortality in septic ICU patients: a nationwide observational study. Annals of Intensive Care, 13(1), 1-13.
Natarajan, A., Lam, G., Liu, J., Beam, A. L., Beam, K. S., & Levin, J. C. (2023). Prediction of extubation failure among low birthweight neonates using machine learning. Journal of Perinatology, 43(2), 209-214.
Rahman, A., Chang, Y., Dong, J., Conroy, B., Natarajan, A., Kinoshita, T., Vicario, F., Frassica, J., Xu-Wilson, M (2021). Early Prediction of Hemodynamic Interventions in the Intensive Care Unit using Machine Learning. Critical Care
Natarajan, A., Boverman, G., Chang, Y., Antonescu, C., Rubin, J (2021). Convolution-Free Waveform Transformers for Multi-Lead ECG Classification. In 2021 Computing in Cardiology (CinC). IEEE.
Natarajan, A., Chang, Y., Mariani, S., Rahman, A., Boverman, G., Vij, S., & Rubin, J. A (2020). Wide & Deep Transformer Neural Network for 12-Lead ECG Classification. In 2020 Computing in Cardiology (CinC). IEEE.
Chang, Y., Rubin, J., Boverman, G., Vij, S., Rahman, A., Natarajan, A., & Parvaneh, S. (2019). A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series. In 2019 Computing in Cardiology (CinC). IEEE.
Natarajan, A., Ganesan, D., & Marlin, B. M. (2019). Hierarchical Active Learning for Model Personalization in the Presence of Label Scarcity. In 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (pp. 1-4). IEEE.
Natarajan, A., & Laftchiev, E. (2019). A Transfer Active Learning Framework to Predict Thermal Comfort. International Journal of Prognostics and Health Management.
Gullapalli, B. T., Natarajan, A., Angarita, G. A., Malison, R. T., Ganesan, D., & Rahman, T. (2019). On-body Sensing of Cocaine Craving, Euphoria and Drug-Seeking Behavior Using Cardiac and Respiratory Signals. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 3(2), 46.
Natarajan, A., Angarita, G., Gaiser, E., Malison, R., Ganesan, D., & Marlin, B. (2016). Domain Adaptation Methods for Improving Lab-to-field Generalization of Cocaine Detection using Wearable ECG. Proceedings of the ACM international joint conference on Pervasive and ubiquitous computing.
Natarajan, A., Xu, K., & Eriksson, B (2016). Detecting Divisions of the Autonomic Nervous System Using Wearables. Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
Nguyen, T.*, Adams, R.*, Natarajan, A.*, & Marlin, B. (2016). Parsing Wireless Electrocardiogram Signals with Context Free Grammar Conditional Random Fields. Proceedings of the ACM conference on Wireless Health.
Natarajan, A., Gaiser, E., Angarita, G., Malison, R., Ganesan, D., & Marlin, B. (2014). Conditional Random Fields for Morphological Analysis of Wireless ECG Signals. Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics.
Natarajan, A., Parate, A., Gaiser, E., Angarita, G., Malison, R., Marlin, B., & Ganesan, D. (2013). Detecting Cocaine Use with Wearable Electrocardiogram Sensors. Proceedings of the ACM international joint conference on Pervasive and ubiquitous computing. Honorable mention.
Detre, G. J.*, Natarajan, A.*, Gershman, S. J., & Norman, K. A. (2013). Moderate levels of activation lead to forgetting in the think/no-think paradigm. Neuropsychologia.
Anderson, C., Forney, E., Hains, D., & Natarajan, A. (2011). Reliable identification of mental tasks using time-embedded EEG and sequential evidence accumulation, Journal of Neural Engineering.
* equal contribution
Natarajan, A., Ganesan, G., Marlin, B., Machine Learning Methods for Detecting Cocaine Use with Wearable ECG Sensors. Poster presented at Amazon Graduate Research Symposium, Seattle, (January 2017). PDF
G. A. Angarita, A. Nararajan, E. Gaiser, A. Parate, B. Marlin, R. R. Gueorguieva, R. Lampert, D. Ganesan, R. T. Malison, A Remote Wireless Sensor Network (RWSN) / Electrocardiographic (ECG) Approach to Discriminating Cocaine Use. Poster presented at the Annual Meeting of the College on Problems of Drug Dependence, Puerto Rico, (June, 2014). PDF
Natarajan, A., Parate, P., Gaiser, E., Angarita, G., Malison, R., Marlin, B., & Ganesan, D., Detecting Signatures of Cocaine Using On-Body Sensors. Poster presented at the Annual Meeting of the American Medical Informatics Association, Washington D.C. (Nov, 2013). PDF
Detre, G.J., Natarajan, A. & Norman, K.A. Moderate Memory Activation Leads to Forgetting in the Think-No Think Paradigm. Poster presented at the Annual Meeting of the Society for Neuroscience, San Diego (Nov, 2010). PDF
Natarajan, A., & Anderson, C. (2009). Estimating Sparse Inverse Covariance matrices for Brain Computer Interface applications. Poster presented at the Molecular, Cellular and Integrative Neurosciences spring poster symposium, Colorado State University, Fort Collins (Mar, 2009). PDF
Natarajan, A. (2018), Machine Learning Methods for Personalized Health Monitoring Using Wearable Sensors, PhD Dissertation, College of Information and Computer Sciences, University of Massachusetts Amherst, MA.
Natarajan, A. (2009), Estimating Sparse Inverse Covariance matrices for Brain Computer Interface applications, Masters Thesis, Department of Computer Science, Colorado State University, Fort Collins, CO.
Probabilistic Curve Induction and Testing Toolbox, Matlab, (P-CIT)