Prof. Judy Fox
Judy Fox is an associate professor of School of Data Science at University of Virginia. She is specialized in Big Data Analytics and Computer Systems. She provides innovative solutions for the Scaling Challenges of Big Data Analytics and Real-Time Machine Learning for interdisciplinary applications including biomedical science, graph and network science, automotive vehicles and sports analytics.
She led an Intel Parallel Computing Center (IPCC) site. She offered an online course CloudMOOC as part of the Data Science Program. Her research has been funded by NSF, NIH, Intel, Microsoft, and Google.
She graduated from Syracuse University with an Outstanding Graduate Student Award, completing her Ph.D. in Computer Science in 2005. She is the recipient of a NSF CAREER Award in 2012. Trustess Award for Teaching Excellence 2013-2014. Outstand Junior Faculty Award 2014-2015. Most recently, she serves as Director of Graduate Studies of Data Science at Indiana University.
Contact Information:
Associate Professor
School of Data Science
University of Virginia
Tel (434)297-5916
News & Events
April 28, 2022
Data Collaborative for Reconstruction various local historical society collections and by local Clerks of the Court.
May 20, 2021
Jiayu Li will give a presentation at the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS) main conference on May 20, 2021.
Covid-19 Forecasting with Time-Series Deep Learning
May 24, 2022
Understanding County Level Covid-19 Infection and Feature Sensitivity with Deep Learning on.
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December 10, 2019
Selahattin Akkas has worked on streaming inference benchmarks of video image detection using TensorFlow Mobile Networks.
April 28, 2022
Time Series Evolution Operator focuses on nowcasting future earthquakes based on previous earthquake time series data.
Recent Projects
IndyCar
Real-time anomaly detection from edge to HPC-cloud in collaboration with Indycar and Intel.
Harp
High Performance Machine Learning tools for achieving your goals faster.
Twister
Iterative MapReduce programming model for parallel and scientific computing.
Educational Projects
EAGER
Computational Science curricula and research using Cloud Computing Technologies for Minority Serving institutions (MSI's)
Cloud MOOC
Funded by Google, we have developed a Cloud Computing online course (CloudMOOC) using their Course Builder technology.
REU
Computational Science curricula and research using Cloud Computing Technologies for Minority Serving institutions (MSI's)
Contact Information
School of Data Science
Office:
Tel (434)297-5916
Dell Building 1
31 Bonnycastle Drive
P.O. Box 400249
Charlottesville, IN 22904