Project Archive

Click on link to find out more about the projects.  


Project 1: Applied Functional Data Analysis (Professor Hans-Georg Müller)

Project 2: Network Data Visualization with Linear Algebra (Professor James Sharpnack)

Project 3: Processing and analyzing data from the Human Connectome Project (Professor Jie Peng and Professor Debashis Paul)

Project 4: Where do we get data from and what can we do with it? (Professor Christiana Drake)

Project 5:  Exploration of classification methods: SVM, kNN, and KDE (Professor Xiaodong Li)

Project 6: Analysis and visualization of data from a social website for sharing music and memories (Professor Petr Janata)


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)


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)


ProjectThe sounds of complexity in aquatic ecosystems, Mentors: Naoki Saito (Applied Math), Geoff Schladow (Civil & Environmental Engineering), Sam Nichols (Music) 

ProjectRemoving noise from tensor-valued neuroimaging data, Mentors: Owen Carmichael (Neuroscience), Debashis Paul (Statistics) and Jie Peng (Statistics) 

ProjectQuantification of brain connectivity from neuroimaging time series data, Mentors: Mentors: Owen Carmichael (Neuroscience) and Hans-Georg Müller (Statistics)

ProjectSplitting Task Oriented Social Networks into a Task Related Layer and the Rest, Mentor: Vladimir Filkov (Computer Science) 


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)

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