@article{gonzalez_angus_tetteh_bello_padmanabhan_pendse_srinivas_yu_semazzi_kumar_et al._2015, title={On the data-driven inference of modulatory networks in climate science: an application to West African rainfall}, volume={22}, ISSN={["1607-7946"]}, DOI={10.5194/npg-22-33-2015}, abstractNote={Abstract. Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.
                    }, number={1}, journal={NONLINEAR PROCESSES IN GEOPHYSICS}, author={Gonzalez, D. L., II and Angus, M. P. and Tetteh, I. K. and Bello, G. A. and Padmanabhan, K. and Pendse, S. V. and Srinivas, S. and Yu, J. and Semazzi, F. and Kumar, V. and et al.}, year={2015}, pages={33–46} }
 @article{gonzalez_pendse_padmanabhan_angus_tetteh_srinivas_villanes_semazzi_kumar_samatova_2013, title={Coupled Heterogeneous Association Rule Mining (CHARM): Application toward Inference of Modulatory Climate Relationships}, ISSN={["1550-4786"]}, DOI={10.1109/icdm.2013.142}, abstractNote={The complex dynamic climate system often exhibits hierarchical modularity of its organization and function. Scientists have spent decades trying to discover and understand the driving mechanisms behind western African Sahel summer rainfall variability, mostly via hypothesis-driven and/or first-principles based research. Their work has furthered theory regarding the connections between various climate patterns, but the key relationships are still not fully understood. We present Coupled Heterogeneous Association Rule Mining (CHARM), a computationally efficient methodology that mines higher-order relationships between these subsystems' anomalous temporal phases with respect to their effect on the system's response. We apply this to climate science data, aiming to infer putative pathways/cascades of modulating events and the modulating signs that collectively define the network of pathways for the rainfall anomaly in the Sahel. Experimental results are consistent with fundamental theories of phenomena in climate science, especially physical processes that best describe sub-regional climate.}, journal={2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM)}, author={Gonzalez, Doel L., II and Pendse, Saurabh V. and Padmanabhan, Kanchana and Angus, Michael P. and Tetteh, Isaac K. and Srinivas, Shashank and Villanes, Andrea and Semazzi, Fredrick and Kumar, Vipin and Samatova, Nagiza F.}, year={2013}, pages={1055–1060} }
 @inproceedings{srinivas_george_lazzi_2008, title={Finite difference formulation to calculate the induced current density profile inside the retina by a microcoil array}, ISBN={978-1-4244-2041-4}, booktitle={2008 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting}, publisher={[Piscataway, NJ]: IEEE}, author={Srinivas, S. and George, J. S. and Lazzi, G.}, year={2008}, pages={3074–3077} }