Faculty Research

2020

Devlin, S. & Uminsky, D. (2020). Identifying group contributions in NBA lineups with spectral analysis. To Appear in Journal of Sports Analytics.

Devlin, S., Treloar, T., Creagar, M. (undergraduate), & Cassels, S. (undergraduate) (2020). An iterative Markov rating method. To appear in Journal of Quantitative Analysis in Sports.

Wilson, J.D., Baybay, M., Sankar, R., and Stillman, P. (2020). Analysis of Population Functional Connectivity Data via Multilayer Network Embeddings. In Press, Network Science.

Lee, J., Li, G., & Wilson, J.D. (2020). Varying-coefficient models for dynamic networks. In Press, Computational Statistics and Data Analysis.

Houghton, I.A., & Wilson, J.D. (2020). El Nino detection via unsupervised clustering of Argo temperature profiles. In Press, Journal of Geophysical Research - Oceans.

Kent, D., Cranmer, S., & Wilson, J.D. (2020). A permutation-based changepoint technique for monitoring effect sizes. In Press, Political Analysis.

Siegel, S.R., True, L., Pfeiffer, K.A., Wilson, J.D., Martin, E.M., Branta, C.F., Pacewicz, R., & Battista, R.A. (2020). Recalled age at menarche: A follow-up to the Michigan State University Motor Performance Study. In Press, Measurement in Physical Education and Exercise Science.

Wilson, J.D., Cranmer, S.J., & Lu, Z.-L. (2020). A hierarchical latent space network model for population studies of functional connectivity. In Press, Computational Brain and Behavior.

Nano, T., Lafrenière, M., Ziemer, B., Witztum, A., Barrios, J., Upadhaya, T., Vallières, M., Interian, Y., Valdes, G., and Morin, O. (2020). Artificial Intelligence in Radiation Oncology. (Chapter 8 of the 4th edition of the book “The Modern Technology of Radiation Oncology" editor Jacob Van Dyk) In Press.

Reichmann, L.G., Valdes, G., Pirracchio, R. and Interian, Y. (2020). Multitask learning from clinical text and acute physiological conditions differentially improve the prediction of mortality and diagnosis at the ICU. In Press: (Preprint)

Valdes, G., Interian, Y., Gennatas, E., Van der Laan, M.J. (2020). Conditional Super Learner. In Press: (Preprint)

Calvo, M., Interian, Y., Solberg T., Valdes, G. (2020). Targeted transfer learning to improve performance in small medical physics datasets. In Press, Medical Physics 2020.

Gennatas E.D., Friedman J.H., Ungar L.H., Pirracchio R., Eaton E., Reichman L.G., Interian, Y., Simone C.B., Auerbach A., Delgado E., Van der Laan M.J., Solberg T.D., Valdes G. (2020). Expert-Augmented Machine Learning. PNAS March 3, 2020 117 (9) 4571-4577.

Turgutlu K.C., Barrios Ginart, J., Ziemer, B.P., Nano, T., Gleason, T., Ibrahim, A., Interian, Y., Dalal, A., Sandor, R., Howard, J., Leseur, J., Vallières, M., Upadhaya, T., Braunstein, S., Ma, L., Kearny, V., Valdes, G., Solberg, T., McDermott, M., Villanueva-Meyer, J. & Morin, O. (2020). Weakly Supervised Transfer Learning for Multi-Modality Brain and Ventricle Segmentation. Submitted to Radiology: Artificial Intelligence 2020.

Immanni, R., Valdes, G., Interian, Y. (2020). Designing a Simple CNN Model in Terms of Size and Computational Complexity to Perform Classification Task On Medical Images. Oral at AAPM—COMP 2020.

Cluceru, J., Alcaide-Leon, P.,Pedoia, V., Phillips, J.J., Nair, D., Interian, Y., Luks, T., Villanueva-Meyer, J.E., Chang, S.M., Molinaro, A.M., Berger, M., Lupo, J.M. (2020). Using anatomic and diffusion MRI with deep convolutional neural networks to distinguish treatment-induced injury from recurrent glioblastoma. Accepted oral at ISMRM 2020.

Cluceru, J., Interian, Y., Lupo, J.M., Bove, R., Butte, A.J., Crane, J.C. (2020). Automatic Classification of MR Image Contrast. Accepted poster to ISMRM 2020.

Cluceru, J., Interian, Y., Phillips, J.J., Nair, D., Alcaide-Leon, P., Chang, S.M., Villanueva-Meyer, J.E., Lupo, J.M. (2020). Automatic stratification of gliomas into WHO 2016 molecular subtypes using diffusion-weighted imaging and a pre-trained deep neural network. Accepted oral to ISMRM 2020.

Ibrahim, K., Savage, D.A., Schnirel, A., Intrevado, P. & Interian, Y. (2020). ContamiNet: Detecting Contamination in Municipal Solid Waste. ICMLA 2020: International Conference on Machine Learning and Applications. Copenhagen, Denmark 2020.

Parr, T.Wilson, J.D., & Hamrick, J. (2020). Nonparametric Feature Impact and Importance. (Preprint)

2019

Stillman, P.E., Wilson, J.D., Denny, M.J., Desmarais, B.A., Cranmer, S.J., & Lu, Z.-L. (2019). A consistent organizational structure across multiple functional subnetworks of the human brain. NeuroImage, 197, 24 - 36.

Wilson, J.D., Stevens, N.T., & Woodall, W.H. (2019). Modeling and detecting change in temporal networks via the degree corrected stochastic block model. Quality and Reliability Engineering International, 35(5):1363-1378.

Sparks, R. & Wilson, J.D. (2019). Monitoring communication outbreaks among an unknown team of actors in dynamic networks. Journal of Quality Technology: 51(4), 353-374.

Wilson, J.D. (2019). Discussion on “Real-time monitoring of events applied to syndromic surveillance". Quality Engineering: 31(1), 91-96.

Morin, O., Chen, W.C., Nassiri, F., Susko, M., Magill, S.T., Vasudevan, H.N., Wu, A., Vallieres, M., Gennatas, E.D., Valdes, G., Pekmezci, M., Alcaide-Leon, P., Choudhury, A., Interian, Y., Mortezavi, S., Turgutlu, K.C., Oberheim Bush, N.A., Solberg, T.D., Braunstein, S.E., Sneed, P.K., Perry, A., Zadeh, G. McDermott, M.W., Villanueva-Meyer, J.E., & Raleigh, D.R. (2019). Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure and overall survival. Neuro-Oncology Advances, Volume 1, Issue 1, May-December 2019.

Parr, T.Wilson, J.D. (2019). Partial Dependence through Stratification. (Preprint)

2018

Devlin, S. & Treloar, T. (2018). A network diffusion ranking family that includes the methods of Markov, Massey, and Colley. Journal of Quantitative Analysis in Sports, 14(3), pp. 91-101.

Jeske, D. R., Stevens, N. T., Tartakovsky, A. G., & Wilson, J.D. (2018). Statistical methods for network surveillance. Applied Stochastic Models in Business and Industry, 34(4):425 - 445.

Gennatas, E.D., Interian, Y., Solberg, T.D., Van der Laan, M.J., Valdes, G. (2018). Conditionally Interpretable Super Learner. LatinX in AI Workshop at NeurIPS 2018.

Parr, T. & Howard, J. (2018). The Matrix Calculus You Need For Deep Learning. (Preprint)

Valdes, G., Chang, A.J., Interian, Y., Owen, K., Jensen, S.T., Ungar, L.H., Cunnan, A., Solberg, T.D., Hsu, I. (2018). HDR salvage brachytherapy: Multiple hypothesis testing vs. machine learning analysis. International Journal of Radiation Oncology Biology Physics: https://doi.org/10.1016/j.ijrobp.2018.03.001.

Valdes, G., Interian, Y. (2018). Comment on 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study'. Physics in Medicine & Biology, 63(6), http://iopscience.iop.org/article/10.1088/1361-6560/aaae23/meta.

Interian, Y., Rideout, V., Keanery, V.P., Efstathios, G., Morin, O., Cheung, J., Solberg, T., and Valdes, G. (2018). Deep nets vs expert-designed features in medical physics: An IMRT QA case study. Forthcoming from Medical Physics.

Ma, J., Ovalle, A., Woodbridge, D.M. (2018). Medication adherence monitoring using machine learning. IEEE International Conference on Biomedical and Health Informatics (BHI), Las Vegas.

2017

Chen, L., Li, R., Liu, Y., Zhang, R., & Woodbridge, D.M. (2017). Machine learning-based product recommendation using Apache Spark. IEEE UIC International Workshop on Data Science and Computational Intelligence (DSCI), San Francisco.

Goodkind, A., Guy Brizan, D., and Rosenberg, A. (2017). Utilizing overt and latent linguistic structure to improve keystroke-based authentication. Image and Vision Computing, 58, 230–238.

Wilson, J.D., Desmarais, B., Cranmer, S., Denny, M., and Bhamidi, S. (2017). Stochastic weighted graphs: Flexible model specification and simulation. Social Networks, 49, 37–47.

Wilson, J.D., Palowitch, J., Bhamidi, S., and Nobel, A.B. (2017). Community extraction in multilayer networks with heterogeneous community structure. Journal of Machine Learning Research, 18.

Woodall, W.H., Zhao, M., Paynabar, K., Sparks, R., and Wilson, J.D.. (2017). An overview and perspective on social network monitoring. IISE Transactions, 49:3, 354–365.

Stillman, P.E., Wilson, J.D., Denny, M.J., Desmarais, B., Bhamidi, S., Cranmer, S., and Lu, Z.L. (2017). Statistical modeling of the default mode brain network reveals a segregated highway structure. Scientific Reports, 7(1), 11694.

2016

Parr, T. and Vinju, J. (2016). Towards a universal code formatter through machine learning. In Proceedings of The 9th ACM SIGPLAN International Conference on Software Language Engineering. (Awarded The Distinguished Paper)

Wilson, J.D., Desmarais, B., Cranmer, S., Denny, M. and Bhamidi, S. (2016). Stochastic weighted graphs: flexible model specification and simulation. Social Networks, 49.

Guy Brizan, D., Gallagher, K., Jahangir, A., and Brown, T. (2016). Predicting citation patterns: Defining and determining influence. Scientometrics 108 (1), 183-200.

2014-2015

Parker, K.S., Wilson, J.D., Marschall, J., Mucha, P.J., and Henderson, J.P. (2015). Network analysis reveals sex and antibiotic resistance associated antivirulence targets in clinical uropathogens. American Chemical Society: Infectious Diseases, 1(11), 523–532.

Szekely, E., Pappa, I., Wilson, J.D., Bhamidi, S., Jaddoe, V., Verhulst, H.T., and Shaw, P. (2015). Childhood peer network characteristics: Genetic influences and links with early mental health trajectories. Journal of Child Psychology and Psychiatry. DOI: 10.1111/jcpp.12493

Brost, R., Phillips, C., Robinson, D., Stracuzzi, D., Wilson, A. and Woodbridge, D.M. (2015). Computing quality scores and uncertainty for approximate pattern matching in geospatial semantic graphs. Statistical Analysis and Data Mining (SADM), 8(5-6), 340–352.

Woodbridge, D.M., Wilson, A.T., Rintoul, M.D., and Goldstein, R.H. (2015). Time series discord detection in medical data using a parallel relational database. IEEE International Conference on Bioinformatics and Biomedicine, Washington, DC.

Goodkind, A., Guy Brizan, D., and Rosenberg, A. (2015). Improvements to keystroke-based authentication by adding linguistic context. International Conference on Biometrics: Theory, Applications and Systems, Arlington, Virginia.

An, G., Guy Brizan, D., Ma, M., Morales, M., Raza Syed, A., and Rosenberg, A. (2015). Automatic recognition of unified Parkinson’s disease rating from speech with acoustic, i-Vector and phonotactic features. Interspeech Conference, Dresden, Germany.

Guy Brizan, D., Goodkind, A., Koch, P., Balagani, K., Phoha, V.V., and Rosenberg, A. (2015). Utilizing linguistically-enhanced keystroke dynamics to predict typist cognition and demographics. International Journal of Human-Computer Studies.

Locklear, H., Govindarajan, S., Sitova, Z., Goodkind, A., Guy Brizan, D., Rosenberg, A., Phoha, V., Gasti, P., and Balagani, K.S. (2014). Continuous authentication with cognition-centric text production and revision features. International Joint Conference on Biometrics (IJCB), Clearwater, Florida.

Katerenchuk, D., Guy Brizan, D., and Rosenberg, A. (2014). “Was that your mother on the phone?”: Classifying interpersonal relationships between dialog participants with lexical and acoustic properties. Interspeech Conference, Singapore.

Brost, R.C., McLendon, W.C., III, Parekh, O., Rintoul, M.D., Strip, D.R., and Woodbridge, D.M. (2014). A computational framework for ontologically storing and analyzing very large overhead image sets. Presented at ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, Dallas.

Lindsay, S. and Woodbridge, D.M. (2014). Spacecraft state-of-health (SOH) analysis via Data Mining. AIAA International Conference on Space Operations (SpaceOps), Pasadena, CA.

Parr, T., Harwell, S., and Fisher, K. (2014). Adaptive LL(*) parsing: The power of dynamic analysis. OOPSLA. Portland, OR.

Ramgopal, S., Thome-Souza, S., Jackson, M., Kadish, N.E., Sanchez Fernandez, I., Klehm, J., Bosl, W., Reinsberger, C., Schachter, S., and Loddenkemper, T. (2014). Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy. Epilepsy Behavior, 37C, 291–307.

Wilson, J.D., Wang, S., Mucha, P.J., Bhamidi, S., and Nobel, A.B. (2014). A testing based extraction algorithm for identifying significant communities in networks. Annals of Applied Statistics, 8(3), 1853–1891.

2012-2013

Broxton, T., Interian, Y., Vaver, J.V., & Wattenhofer, M. (2013). Catching a viral video. Journal of Intelligent Information Systems, 40(2), 241–259.

Engle, S., and Gates, C. (2013). Reflecting on visualization for cyber security. Proceedings of the 2013 IEEE International Conference on Intelligence and Security Informatics (ISI), from the Evaluating Security Visualizations Workshop, Seattle, Washington, 275–277.

Parr, T. (2013). The definitive ANTLR 4 reference. Dallas, TX: Pragmatic Bookshelf.

Wilson, J.D., Bhamidi, S., and Nobel, A.B. (2013). Measuring the statistical significance of local connections in directed networks. Neural Information Processing Systems Workshop on Frontiers of Network Analysis: Methods, Models and Applications.

Serwadda, A., Wang, Z., Koch, P., Govindarajan, S., Pokala, R., Goodkind, A., Guy Brizan, D., Rosenberg, A., Phoha, V.V., and Balagani, K.S. (2013). Scan-based evaluation of continuous keystroke authentication systems. IT Professional, 15(4): 20–23.

An, G., Guy Brizan, D., and Rosenberg, A. (2013). Detecting laughter and filled pauses using syllable-based features. Interspeech, Lyon, France.

Suh, M., Lan, M., Samy, L., Alshurafa, N., Ghasemzadeh, H., Sarrafzadeh, M. and Macabasco-O'Connell, A. (2012). WANDA: An end-to-end remote health monitoring and analytics system for heart failure patients. Presented at Wireless Health Conference, San Diego.

Suh, M., Nahapetian, A., Woodbridge, J., Rofouei, M. and Sarrafzadeh, M. (2012). Machine learning-based adaptive wireless interval training guidance system. Mobile Networks and Applications, 17(2), 163-177.

Suh, M., Woodbridge, J., Moin, T., Lan, M., Alshurafa, N., Samy, L., Mortazavi, B., Ghasemzadeh, H., Bui, A., Ahmadi, S. and Sarrafzadeh, M. (2012). Dynamic task optimization in remote diabetes monitoring systems. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB), San Jose.

Suh, M., Moin, T., Woodbridge, J., Lan, M., Ghasemzadeh, H., Ahmadi, S., Bui, A., and Sarrafzadeh, M. (2012). Dynamic self-adaptive remote health monitoring system for diabetics. International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego.

Bishop, M., Engle, S., Howard, D., & Whalen, S. (2012). A taxonomy of buffer overflow characteristics. IEEE Transactions on Dependable and Secure Computing (TDSC), Volume 9, Issue 3, 305–317.

Bishop, M., Engle, S., Peisert, S., D., & Whalen, S. (2012). Network-theoretic classification of parallel computation patterns. International Journal of High Performance Computing Applications (IJHPCA), Volume 26, Number 2, 159–169.

Bosl, W. (2012). Neurotechnology and psychiatric biomarkers. In D. Ghista, (ed), Biomedical Engineering – Book 3. InTech Publishers.

Devlin, S., & Treloar, T. (2012). Network-based criterion for the success of cooperation in an evolutionary prisoner's dilemma. Devlin, S., & Treloar, T. (2012). Phys. Rev. E 86, 26-113.

Engle, S. & Whalen, S. (2012). Visualizing distributed memory computations with hive plots. Proceedings of the Ninth International Symposium on Visualization for Cyber Security (VizSec), Seattle, Washington, 56–63, October 2012.

Hamrick, J., Russ, J., Bu, K., & Cizdziel, J. (2012). Laser ablation - Inductively coupled plasma-mass spectometry analysis of lower Pecos rock paints and possible pigment sources. Collaborative Endeavors in the Chemical Analysis of Art and Cultural Heritage Materials. Washington, D.C.: American Chemical Society.

2010-2011

Bosl, W., Tager-Flusberg, H., Tierney, A., & Nelson, C.A. (2011). EEG complexity as a biomarker for autism spectrum disorder risk. BMC Medicine, 9:18.

Suh, M., Chen, C.A., Woodbridge, J., Tu, M.K., Kim, J.I., Nahapetian, A., Evangelista, L.S. and Sarrafzadeh, M. (2011). "A Remote Patient Monitoring System for Congestive Heart Failure." Journal of Medical Systems, 35(5), 1165-1179.

Suh, M., Woodbridge, J., Lan, M., Bui, A., Evangelista, L.S. and Sarrafzadeh, M. (2011). Missing Data Imputation for Remote CHF Patient Monitoring. Presented at International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Boston.

Dorai-Raj, S., Interian, Y., Naverniouk, I., & Zigmond, D. (2011). Adapting online advertising techniques to television. Online Multimedia Advertising: Techniques and Technologies (pp. 148-165). Hershey, PA: Information Science Reference.

Hamrick, J., Taqqu, M.S., & Pecatti, G. (2011). Practical implementation using Mathematica. Appendix A, Wiener chaos: Moments, cumulants, and diagrams. Milan, Italy: Bocconi-Springer.

Hamrick, J. (2011). Using local correlation to explain success in baseball. Journal of Quantitative Analysis in Sports, Volume 7: Issue 4.

Hamrick, J., Kardaras, K., Taqqu, M.S., & Huang, Y. (2011). Maximum penalized quasi-likelihood estimation of the diffusion function. Quantitative Finance, 11:11.

Hamrick, J., & Rasp, J. (2011). Using local correlation to explain success in baseball. Journal of Quantitative Analysis in Sports. Volume 7, Issue 4.

Hamrick, J., & Rasp, J. (2011). The connection between race and called strikes and balls. Journal of Sports Economics, 00(0), 1-21.

Parr, T., Fisher, K. (2011). The foundation of the ANTLR parser generator. Programming language design and implementation (PLDI), San Jose, CA.

Devlin, S., & Treloar, T. (2010). Reply to comment on cooperation in an evolutionary prisoners dilemma on networks with degree-degree correlations. Phys Rev. E. 82, 038-102.

Dorai-Raj, S., Interian, Y., & Zigmond, D. (2010). Evaluating TV ad campaigns using set-top box data. Re:Think 2010.

Simidchieva, B.I., Engle, S., Clifford, M., Jones, A.C., Peisert, S., Bishop, M., Clarke, L.A., & Osterweil, L.J. (2010). Modeling and analyzing faults to improve election process robustness. In the Proceedings of the USENIX Electronic Voting Technology Workshop/Workshop on Trustworthy Elections (EVT/WOTE).

Suh, M., Evangelista, L.S., Chen, C.A., Han, K., Kang, J., Tu, M.K., Chen, V., Nahapetian, A. and Sarrafzadeh, M. (2010). An Automated Vital Sign Monitoring System for Congestive Heart Failure Patients. Presented at ACM SIGHIT International Health Informatics Symposium (IHI), Miami.

Suh, M., Evangelista, L.S., Chen, V., Hong, W.S., Macbeth, J., Nahapetian, A., Figueras, F.J. and Sarrafzadeh, M. (2010). WANDA B.: Weight and Activity with Blood Pressure Monitoring System for Heart Failure Patients. Presented at The Second International IEEE WoWMoM Workshop on Interdisciplinary Research on E-Health Services and Systems (IREHSS), Lucca, Italy.

2009 and earlier

Devlin, S., & Treloar, T. (2009). Cooperation in an evolutionary prisoners dilemma game on networks with degree-degree correlations. Phys. Rev. E 80, 26-105.

Devlin, S., & Treloar, T. (2009). Evolution of cooperation through the heterogeneity of random networks. Phys. Rev. E 79, 16-107.

Interian, Y., Dorai-Raj, S., Naverniouk, I., Opalinski, P. J., Kaustuv, & Zigmond, D. (2009). Ad quality on TV: Predicting television audience retention. Proceedings of International workshop on Data Mining and Audience Intelligence for Advertising (ADKDD).

Interian, Y., Dorai-Raj, S., Naverniouk, I., Opalinski, P. J., Kaustuv, & Zigmond, D. (2009). Do Viewers Care? Understanding the impact of ad creatives on TV viewing behavior. Re:Think 2009 .

Zigmond, D., Interian, Y., Lanning, S., Hawkins, J., Mirisola, R., Rowe, S., & Volovich, Y. (2009). When viewers control the schedule: Measuring the impact of digital video recording on TV viewership. Key Issues Forums at ARF Audience Measurement Conference, 2009.

Parr, T. (2009). Language Implementation Patterns. Dallas, TX: Pragmatic Bookshelf.

Suh, M., Lee, K., Heu, A., Nahapetian, A. and Sarrafzadeh, M. (2009). Bayesian Networks-Based Interval Training Guidance System for Cancer Rehabilitation. Presented at Conference on Mobile Computing, Applications, and Services (MobiCASE), San Diego.

Suh, M., Dorman, K., Yahyanejad, M., Nahapetian, A., Sarrafzadeh, M., McCarthy, W. and Kaiser, W. (2009). Nutrition Monitor: A Food Purchase and Consumption Monitoring Mobile System. Presented at Conference on Mobile Computing, Applications, and Services (MobiCASE), San Diego.

Suh, M., Lee, K., Nahapetian, A. and Sarrafzadeh, M. (2009). Interval Training Guidance System with Music and Wireless Group Exercise Motivations. Presented at IEEE Symposium on Industrial Embedded Systems (SIES), Lausanne, Switzerland.

Suh, M., Rofouei, M., Nahapetian, A., Kaiser, W.J. and Sarrafzadeh, M. (2009). Optimizing Interval Training Protocols Using Data Mining Decision Trees. Presented at Body Sensor Networks (BSN).

Bosl, W. (2007). Systems biology by the rules: Hybrid intelligent systems for pathway discovery and analysis. BMC Systems Biology, 1:13.

Guy Brizan, D., and Uz Tansel, A. (2006). A survey of entity resolution and record linkage methodologies. Communications of the IIMA. 6(3).

Guy Brizan, D. (2006). Evaluation of Equivalence of French/English Idiomatic Pairs. Technical Report. San Francisco State University.