Publications

Foss, A., Shakamuri, M., Martin, S., Acharya, T.N., & Acharya, T.N. (2023). Detecting Anomalous Event Timings in Cybersecurity Logs [Conference Presenation]. 10.2172/2430763

Martin, S., Sielicki, M., Letter, M., Gittinger, J.M., Hunt, W.L., Crossno, P.J., & Crossno, P.J. (2022). Mesh Distance for Dimension Reduction and Visualization of Numerical Simulation Data [Conference Presenation]. 10.2172/2432195

Hu, C., Martin, S., Dingreville, R., & Dingreville, R. (2022). Accelerating phase-field predictions via recurrent neural networks learning the microstructure evolution in latent space. Computer Methods in Applied Mechanics and Engineering, 397. https://doi.org/10.1016/j.cma.2022.115128

Martin, S., Sielicki, M., Letter, M., Gittinger, J.M., Hunt, W.L., Crossno, P., & Crossno, P. (2022). Mesh Distance for Dimension Reduction and Visualization of Numerical Simulation Data [Conference Paper]. 10.2352/EI.2023.35.1.VDA-392

Hu, C., de Zapiain, D.M., Martin, S., Stewart, J.A., Dingreville, R., & Dingreville, R. (2022). Accelerating Phase-field Predictions
Via Surrogate Models Trained By
Machine Learning Methods [Conference Presenation]. 10.2172/2001792

Jalving, J.H., Ghouse, J., Knueven, B., Martin, S., Cortez, N., Xian, G., Siirola, J.D., Miller, D., Dowling, A., & Dowling, A. (2021). Toward Future Energy Generation Systems: Multi-Scale Optimization with Market Interactions [Conference Presenation]. 10.2172/1899469

Crossno, P.J., Gittinger, J.M., Hunt, W.L., Letter, M., Martin, S., Sielicki, M., & Sielicki, M. (2021). Slycat? Ensemble Analytics [Presentation]. https://www.osti.gov/biblio/1882478

Goodman, E., Ingram, J., Martin, S., Grunwald, D., & Grunwald, D. (2020). Using Bipartite Anomaly Features to Predict Spam [Conference Poster]. https://www.osti.gov/biblio/1831051

Multari, R., Co, C., Cummings, P.G., Ferrizz, R., Martin, S., Miller, L., Patel, N., Walla, L.A., Ray, J., & Ray, J. (2020). Automated algorithms for predicting trends and identifying subpopulations in neutron generator (NG) production data [Presentation]. https://www.osti.gov/biblio/1811805

Crossno, P.J., Gittinger, J.M., Hunt, W.L., Letter, M., Martin, S., Sielicki, M., & Sielicki, M. (2020). Dial-A-Cluster User Manual. 10.2172/1635595

Bandlow, A., Bauer, T.L., Crossno, P.J., Garcia, R.J., Astuto Gribble, L., Hernandez, P.M., Martin, S., McClain, J.T., Patrizi, L., & Patrizi, L. (2020). Rapid Response Data Science for COVID-19. 10.2172/1763559

Crossno, P.J., Gittinger, J.M., Hunt, W.L., Letter, M., Martin, S., Sielicki, M., & Sielicki, M. (2020). Slycat? Ensemble Analytics [Conference Poster]. https://www.osti.gov/biblio/1778153

Multari, R., Ray, J., Miller, L., Ferrizz, R., Cummings, P., Co, C., Walla, L.A., Martin, S., & Martin, S. (2020). Automated algorithms for predicting trends and identifying subpopulations in neutron generator (NG) production data [Conference Poster]. https://www.osti.gov/biblio/1766727

Martin, S., Sielicki, M., Gittinger, J.M., Letter, M., Hunt, W.L., Crossno, P.J., & Crossno, P.J. (2019). VideoSwarm: Analyzing video ensembles [Conference Poster]. IS and T International Symposium on Electronic Imaging Science and Technology. 10.2352/ISSN.2470-1173.2019.1.VDA-685

Owen, S.J., Shead, T.M., Martin, S., & Martin, S. (2019). CAD DEFEATURING USING MACHINE LEARNING [Conference Poster]. Proceedings of the 28th International Meshing Roundtable, IMR 2019. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85160931346&origin=inward

Owen, S.J., Shead, T.M., Martin, S., & Martin, S. (2018). Machine Learning-based CAD Defeaturing for Tetrahedral Mesh Generation [Conference Poster]. https://www.osti.gov/biblio/1596411

Martin, S., Sielicki, M., Gittinger, J.M., Letter, M., Hunt, W.L., Crossno, P.J., & Crossno, P.J. (2018). VideoSwarm: Analyzing Video Ensembles [Conference Poster]. 10.2352/ISSN.2470-1173.2019.1.VDA-685

Owen, S.J., Shead, T.M., Martin, S., & Martin, S. (2018). Defeaturing using Machine Learning [Conference Poster]. https://www.osti.gov/biblio/1577044

Martin, S., Gandhi, A., Kelkar, M., Ingram, J.B., & Ingram, J.B. (2018). Analyzing Source Code with LSTM Sequence Embeddings [Conference Poster]. https://www.osti.gov/biblio/1572752

Owen, S.J., Shead, T.M., Martin, S., & Martin, S. (2018). Automated Simulation Model Preparation with Machine Learning [Conference Poster]. https://www.osti.gov/biblio/1806719

Gandhi, A., Kelkar, M., Ingram, J.B., Martin, S., & Martin, S. (2018). Sequence Embeddings using LSTM Networks: Applications to Cybersecurity [Presentation]. https://www.osti.gov/biblio/1806621

Gittinger, J.M., Martin, S., Sielicki, M., Letter, M., Hunt, W.L., Crossno, P.J., & Crossno, P.J. (2018). VideoSwarm: Interactive Visualization of Simulation Video Ensembles [Conference Poster]. https://www.osti.gov/biblio/1505024

Crossno, P.J., Gittinger, J.M., Hunt, W.L., Letter, M., Martin, S., Sielicki, M., & Sielicki, M. (2017). Slycat™ User Manual. 10.2172/1418737

Martin, S., Foulk, J.W., Anderson, T.M., & Anderson, T.M. (2017). Screening for High Conductivity/Low Viscosity Ionic Liquids Using Product Descriptors. Molecular Informatics, 36(7). 10.1002/minf.201600125

Barone, M.F., Fike, J., Chowdhary, K., Davis, W.L., Ling, J., Martin, S., & Martin, S. (2017). Machine Learning Models of Errors in LES Predictions of Surface Pressure Fluctuations [Conference Poster]. https://www.osti.gov/biblio/1458163

Barone, M.F., Fike, J., Chowdhary, K., Davis, W.L., Ling, J., Martin, S., & Martin, S. (2017). Machine learning models of errors in large eddy simulation predictions of surface pressure fluctuations [Conference Poster]. 47th AIAA Fluid Dynamics Conference, 2017. 10.2514/6.2017-3979

Martin, S., Westergaard, C.H., White, J.R., & White, J.R. (2016). Visualizing wind farm wakes using SCADA data. Whither Turbulence and Big Data in the 21st Century?. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030703245&origin=inward

Quach, T., Martin, S., & Martin, S. (2016). Interactive Visualization [Conference Poster]. https://www.osti.gov/biblio/1366884

Martin, S., Westergaard, C.H., White, J.R., Karlson, B., & Karlson, B. (2016). Visualizing Wind Farm Wakes Using SCADA Data. 10.2172/1561493

Westergaard, C., Martin, S., White, J.R., Karlson, B., & Karlson, B. (2016). Towards a more robust understanding of the uncertainty of wind farm reliability. https://www.osti.gov/biblio/1574645

Karlson, B., Carter, C., Martin, S., Westergaard, C., & Westergaard, C. (2016). Continuous Reliability Enhancement for Wind (CREW). Program Update. 10.2172/1761994

Westergaard, C., Martin, S., Karlson, B., Carter, C., White, J.R., & White, J.R. (2016). Progress on SCADA Data Based Wake Analysis [Conference Poster]. https://www.osti.gov/biblio/1346789

Martin, S., Quach, T., & Quach, T. (2016). Interactive visualization of multivariate time series data [Conference Poster]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-319-39952-2_31

Reyes, A., Jimenez, E.S., Martin, S., & Martin, S. (2015). A Hybrid Approach to Multivariate Time-Series Clustering for Failure Analysis [Presentation]. https://www.osti.gov/biblio/1340130

Westergaard, C., Karlson, B., Martin, S., White, J.R., & White, J.R. (2015). Big Data: Anaslysis Improved Performance and Benchmarking [Conference Poster]. https://www.osti.gov/biblio/1251130

Martin, S., Westergaard, C., Karlson, B., White, J.R., & White, J.R. (2015). New Wake Effects Identified Using SCADA Data Analysis and Visualization [Presentation]. https://www.osti.gov/biblio/1245927

White, J.R., Karlson, B., Martin, S., Westergaard, C., & Westergaard, C. (2014). Towards a more robust understanding of the uncertainty of wind farm reliability [Conference Poster]. https://www.osti.gov/biblio/1244873

White, J.R., Martin, S., Westergaard, C., & Westergaard, C. (2014). Visualizing Wind Farm Wake Losses using SCADA Data [Conference Poster]. https://www.osti.gov/biblio/1319765

Martin, S., Westergaard, C., White, J.R., Karlson, B., & Karlson, B. (2014). New Wake Effects Identified Using SCADA Data Analysis and Visualization [Conference Poster]. https://www.osti.gov/biblio/1315398

Rintoul, M.D., Watson, J., McLendon, W., Parekh, O.D., Martin, S., & Martin, S. (2014). Encoding and Analyzing Aerial Imagery Using Geospatial Semantic Graphs. 10.2172/1204099

Martin, S., Watson, J., & Watson, J. (2009). Non-manifold surface reconstruction from high dimensional point cloud data. Proposed for publication in Computational Geometry: Theory and Applications.. https://www.osti.gov/biblio/958390

Martin, S., McKenna, S.A., & McKenna, S.A. (2007). Predicting building contamination using machine learning [Conference]. Proceedings - 6th International Conference on Machine Learning and Applications, ICMLA 2007. https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=47349083666&origin=inward

Chandler, G.A., Renzi, R.F., Derzon, M.S., Martin, S., & Martin, S. (2007). Innovative high pressure gas MEM's based neutron detector for ICF and active SNM detection. 10.2172/934580

Joo, J., Plimpton, S.J., Martin, S., Swiler, L.P., Faulon, J.M., & Faulon, J.M. (2007). Sensitivity Analysis of NF-?B signaling network. The Annals of New York Academy of Sciences. https://www.osti.gov/biblio/1147524

Martin, S. (2007). An Approximate Version of Kernel PCA [Conference]. 10.1109/ICMLA.2006.13

Martin, S., Zhang, Z., Martino, A., Faulon, J.M., & Faulon, J.M. (2007). Online Supplement for Boolean dynamics of genetic regulatory networks inferred from microarray time series data. Bioinformatics, 23(7). 10.1093/bioinformatics/btm021

Martin, S., Zhang, Z., Martino, A., Faulon, J.M., & Faulon, J.M. (2007). Boolean dynamics of genetic regulatory networks inferred from microarray time series data. Bioinformatics, 23(7), pp. 866-874. 10.1093/bioinformatics/btm021

Roe, D.C., Sale, K.L., Faulon, J.M., Martin, S., & Martin, S. (2005). Developing algorithms for predicting protein-protein interactions of homology modeled proteins. 10.2172/883467

Faulon, J.M., Zhang, Z., Martino, A., Timlin, J.A., Haaland, D.M., Martin, S., Davidson, G.S., May, E., Slepoy, A., & Slepoy, A. (2005). Reverse engineering biological networks :applications in immune responses to bio-toxins. 10.2172/877733

Martin, S., Backer, A., & Backer, A. (2004). Estimating image manifold dimension by inversion [Conference]. https://www.osti.gov/biblio/947362