Research Overview

Our research focuses on the development of novel data mining and machine learning algorithms for various types of data, including spatio-temporal, sequential, and network/graph data. Our research has been funded through external grants from various federal agencies including the National Science Foundation, Office of Naval Research, Army Research Office, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, and National Institutes of Health, as well as gifts from various companies such as Amazon, Cisco, Bosch Research, Hewlett Packard Labs, and Narus Corp.

---

Latest News

December 2021
Tyler Wilson succesffully defended his PhD dissertation

December 2021
Congratulations to Andrew McDonald for being named Marshall scholar

August 2021
New NIH grant with Dr Argyris Young and Dr Michael Stern to study social media impact on vaccine hesitancy

May 2021
Farzan successfully defended his PhD dissertation

March 2021
Teaching AI what's fair, article was featured on MSU Today

November 2020
Farzan presented his work on fairness perception in network data at ICDM 2020 conference

October 2020
Joint project with Lifeng Luo on Prediction and Characterization of Extreme Events in Spatio-Temporal Data was funded by NSF

August 2020
Ding successfully defended his PhD dissertation

August 2020
Ding presented his work on hurricane intensity prediction at the KDD Workshop on Fragile Earth: Data Science for a Sustainable Planet

April 2020
Tyler presented his paper on convolutional methods for predictive modeling of geospatial data at SDM 2020

February 2020
Farzan and Ding presented their papers at AAAI 2020

January 2020
Joint project with Abdol-Hossein Esfahanian on Fairness-Aware Network Analysis was funded by NSF