Every year a group of undergraduate students work on a research project led by a faculty mentor. Below is an archive of past projects.
2016-2017
Project: Applied Functional Data Analysis (Professor Hans-Georg Müller)
Project: Network Data Visualization with Linear Algebra (Professor James Sharpnack)
Project: Processing and analyzing data from the Human Connectome Project (Professor Jie Peng and Professor Debashis Paul)
Project: Wildfires (Professor James Sharpnack)
Project: Where do we get data from and what can we do with it? (Professor Christiana Drake)
Project: Exploration of classification methods: SVM, kNN, and KDE (Professor Xiaodong Li)
Project: Analysis and visualization of data from a social website for sharing music and memories (Professor Petr Janata)
2015-2016
Project: Applied Functional Data Analysis (H.-G. Müller)
Project: Quantifying Patterns of Survival and Reproduction for Cohorts of Flies (H.-G. Müller)
Project: Spatio-temporal covariance models for use in solar energy research (J. Patrick)
Project: Exploration of geometry of data in high dimensions and its effect on classification (W. Polonik)
Project: Manifold learning with outliers (T. Lee)
2014-2015
Project: Developing a model-free approach for bias correction when measuring object sizes in images. (pdf file) -- Thomas Lee (Statistics)
Project: Developing models for cherry fly survival and reproduction in dependence on hatching. -- Hans-Georg Mueller (Statistics) and James Carey (Entomology)
Project: Analyzing functional variance process for modeling longitudinal biological trajectories -- Hans-Georg Mueller (Statistics)
Project: Sonification of sensor network data, in particular underwater temperature measurements made via an array of thermometers at Lake Tahoe at various depths. -- Naoki Saito (Mathematics)
Project: Developing a statistical methodology for extracting diffusion tensor from diffusion-weighted MRI data. -- Debashis Paul (Statistics) and Jie Peng (Statistics)
Project: Developing a new method for detrending solar irradiance time series data using a nonlinear least squares approach. -- Joshua Patrick (Statistics)
Project: Analysis of solar irradiance time series using various methods including artificial neural networks, ARIMA models, and nonlinear AR models. -- Joshua Patrick (Statistics)
Project: Estimating nonlinear additive vector AR model. -- Joshua Patrick (Statistics)
Project: Estimating and forecasting of nonlinear AR models fit to solar irradiance data. -- Joshua Patrick (Statistics)
2013-14
Project: The sounds of complexity in aquatic ecosystems, Mentors: Naoki Saito (Applied Math), Geoff Schladow (Civil & Environmental Engineering), Sam Nichols (Music)
Project: Removing noise from tensor-valued neuroimaging data, Mentors: Owen Carmichael (Neuroscience), Debashis Paul (Statistics) and Jie Peng (Statistics)
Project: Quantification of brain connectivity from neuroimaging time series data, Mentors: Mentors: Owen Carmichael (Neuroscience) and Hans-Georg Müller (Statistics)
Project: Splitting Task Oriented Social Networks into a Task Related Layer and the Rest, Mentor: Vladimir Filkov (Computer Science)
2012-13
Project: Protein Structures, Mentor: Nelson Max (Computer Science)
Project: Interactive data visualization on large-scale displays, Mentor: Kwan-Liu Ma (Computer Science)
Project: Extracting dynamics of affect from dyads over time, Mentor: Emilio Ferrer (Psychology)
Project: The cryptic invasion of California by tropical fruit flies, Mentor: James Carey (Entomology)
Project: Filling in the Void in Social Networks: the disappearance of hubs and emergence of new ones in their wake, Mentor: Vladimir Filkov (Computer Science)