Data Sciences and Machine Intelligence

Imaging Research Focuses on Registration Algorithms Embedded in a Dynamic, 3-D Model of the Patient's Brain.

New statistical approach classifies and generates more accurate predictions from big data

Amiridi aims to apply her algorithms to a variety of real-world health datasets and ultimately help improve patient outcomes.

Research Aims to Improve Algorithms that Rank Alternatives Based on Individual Preferences.

Data-driven methods play important role in wireless communications

Nikolaos Sidiropoulos’ pioneering paper is among IEEE's “Best Readings in Machine Learning in Communications.”

Gustavo Rohde is developing a new class of modeling tools

Gustavo Rohde has received a grant from the National Institutes of Health to devise a new class of modeling tools that are better adapted to exploring biomedical data than the...

Greg Medlock shares his experience

Greg Medlock honed his collaborative abilities during his two years as a participant in a National Institutes of Health training grant led by his doctoral thesis advisor, BME...

Aidong Zhang adds machine learning expertise to biomedical data sciences at UVA

One measure of the success of UVA’s campaign to take its place as a national leader in the data sciences is its ability to attract highly regarded researchers to join the faculty...

Health IT Analytics features a publication by researchers supported by the Center for Engineering in Medicine: Machine learning algorithms can rapidly analyze biopsy images and reduce the time it takes to diagnose gut diseases in children, revealed a study published in JAMA Network Open.

Three UVA Ph.D. students are using new data science tools to better understand what makes a job interview successful for candidates and recruiters – and how companies can mitigate bias.

Mohamad Alipour’s research brings machine learning, visual recognition and civil engineering together to make the task of inspecting infrastructure better and safer.