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Project 25: Modeling Non-Stationary Processes

Suitable Majors

Applied Mathematics, Computer Science, Electrical Engineering, Mathematics

Research Area

Signal Processing, Machine Learning, Time Series, Computing

Internship Description

To develop models and methods that characterize and capture changes in high dimensional signals.
Methodology: Signal processing methods, time series models, optimization and computing​

Prerequisites

Computing (in Python, R, matlab), signal processing methods, machine learning methods

Deliverables/Expectations

Working (beta-version) toolbox for computing, poster, paper draft​

Other Comments

​Internship dates: 19 May to 26 July or 23 June to 29 August or 7 July to 14 September​

Division

Computer, Electrical and Mathematical Sciences and Engineering

Faculty Name

Hernando Ombao