Imaging and Data Science Lab - Prof. Gustavo Rohde
We build intelligent systems based on mathematical modeling of signal and image data, with applications in biomedicine, mobile and remote sensing. We specialize on objective and quantitative modeling of data from imaging and other types of sensors by incorporating knowledge from multiple disciplines including applied mathematics, signal processing, machine learning and statistics. Past and current work includes inverse...
Information Processing and Storage Lab (IPS) - Prof. Farzad Farnoud Hassanzadeh
Our interests include information theory, bioinformatics/computational biology, and machine learning. The research in our lab gravitate towards problems that lie in the intersections of these areas, such as stochastic and information-theoretic modeling of DNA mutations, compression of biological sequences, and rank aggregation and its application to computational biology.
Virginia Image and Video Analysis Lab (VIVA) - Prof. Scott Acton
We concentrate on image analysis problems (tracking, segmentation, retrieval), with an emphasis on biological and biomedical image analysis. Check out our stuff!
Data Mining and Knowledge Discovery Lab - Prof. Jundong Li
Our research is mainly focused on data mining, machine learning, and causal inference, and social computing. In particular, we are interested in developing innovative algorithms to glean actionable patterns from big, noisy, dynamic, heterogeneous, and networked data for decision making, and strive to address the pressing challenges in various high-impact domains, including social media, healthcare, online education, and industrial manufacturing.
Laboratory for Intelligent Communication and Networking (LICAN) - Prof. Cong Shen
LICAN focuses on interdisciplinary research that spans wireless communications, wireless networking, machine learning, and statistical information processing. In particular, Our recent interests are on advancing future communication and networking systems that are designed by, and support for, edge intelligence and machine learning.
Signal and Tensor Analytics Research (STAR) Lab - Prof. Nikos Sidiropoulos
The STAR lab focuses on research at the confluence of signal processing, optimization, (multi-)linear algebra, and statistics. The lab is a hub of tensor and matrix factorization research, with applications in communications, machine learning, and probability. Lab alumni work in academia (e.g., U. Florida-Gainesville), industry (e.g., Qualcommn, Ericsson, Amazon Research), and government research labs (e.g., NREL).
Optical Multiuser/Multichannel Communications Lab - Prof. Maite Brandt-Pearce
Our society has come to depend on massive information on demand, and the transfer of this information is accomplished today using optical communications. The appeal of the optical medium for communications, its tremendous bandwidth, is only fully exploitable through multiplexing of many signals, in time, wavelength, or other domain. Our research explores the use of signal processing, communication theory, and optical techniques in designing high capacity optical multiuser/multichannel systems and networks. Current research topics include optical wireless and visible light communications, advanced modulation and coding for optical communication systems, and cross-layer design and optimization of optical networks.
Medical Image Analysis and Optimization - Prof. Miaomiao Zhang
Our lab focuses on developing computational models of image and shape analysis, with particular interests in medical and biological imaging. Beyond working at the interface of statistics, mathematics, and computer engineering to look for scientific solutions, we are taking the challenge to optimize such solutions in real clinical settings to maximally benefit human health.