Yannet is an assistant professor in the Master’s in Data Science program, and her research interests lie in the application of machine learning and deep learning to medical data. She holds a PhD in applied mathematics from Cornell University and a BS in mathematics from the University of Havana, Cuba. After a postdoctoral fellowship at UC Berkeley, she worked for five years as a data scientist at Google. Yannet co-founded Akualab, a start-up that helped organizations develop data-driven products using machine intelligence and has designed data science courses for both UC Berkeley and USF.
- PhD, Applied Mathematics, Cornell University
- Selected Publications
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.
Sundar Dorai-Raj, Yannet Interian, Igor Naverniouk and Dan Zigmond. Adapting Online Advertising Techniques to Television. Online Multimedia Advertising: Techniques and Technologies, Information Science Reference, Hershey PA, 2011, pp. 148- 165 (Book Chapter)
Adrian Ulges, Yannet Interian, Luciano Sbaiz. Predictive Modeling of User Behavior on YouTube. (2011)
Catching a viral video Tom Broxton, Yannet Interian, Jon Vaver Vaver, Miriam Wattenhofer Catching a viral video. Journal of Intelligent Information Systems volume 40, issue 2, year 2013, pp. 241 - 259 (Shorter version IEEE SIASP@ICDM 2010)
H De Arazoza, R Lounes, T Hoang, Y Interian. Modeling HIV epidemic under contact tracing – the Cuban case. Computational and Mathematical Methods in Medicine 2 (4), 267-274, 2010
Sundar Dorai-Raj, Yannet Interian, Dan Zigmond. Evaluating TV Ad Campaigns Using Set-Top Box Data. Re:Think 2010
Yannet Interian, Sundar Dorai-Raj, Igor Naverniouk, P. J. Opalinski, Kaustuv, Dan Zigmond. Ad Quality On TV: Predicting Television Audience Retention. Proceedings of International workshop on Data Mining and Audience Intelligence for Advertising (ADKDD), 2009
Dan Zigmond, Sundar Dorai-Raj, Yannet Interian, Igor Naverniouk. Measuring Advertising Quality on Television: Deriving Meaningful Metrics from Audience Retention Data. Journal of Advertising Research, vol. 49, 2009, pp. 419-428
Yannet Interian, Kaustuv, Igor Naverniouk, P. J. Opalinski, Sundar Dorai-Raj, Dan Zigmond. Do Viewers Care? Understanding the impact of ad creatives on TV viewing behavior . Re:Think 2009
Dan Zigmond, Yannet Interian, Steve Lanning, John Hawkins, Raimundo Mirisola, Simone Rowe, Yaroslav Volovich. When Viewers Control the Schedule: Measuring the Impact of Digital Video Recording on TV Viewership. Key Issues Forums at ARF Audience Measurement Conference, 2009
Richard Durrett , Yannet Interian. Genomic Midpoints: Computation and Evolutionary Implications. (2006)
Yacine Boufkhad, Olivier Dubois, Yannet Interian, Bart Selman. Regular Random k-SAT: Properties of Balanced Formulas. J. Autom. Reasoning 35(1-3): 181-200, 2005
Yannet Interian. Approximation Algorithm for Random MAX-kSAT. In International Conference on Theory and Applications of Satisfiability Testing SAT 2004. Full version in Springer-Verlag Lecture Notes in Computer Science, 173-182, 2004
Hubie Chen, Yannet Interian. A Model for Generating Random Quantified Boolean Formulas. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), 66-71, 2005
Yannet Interian. Backdoor Sets for random 3-SAT. In International Conference on Theory and Applications of Satisfiability Testing SAT 2003