I am currently an Professor within the Department of Electrical Engineering & Computer Science at SD Mines where I direct the Mines Machine Learning and Intelligent Systems Lab (MMLIS - L), and coordinate the Ph.D. program in Data Science & Engineering.  I received my Bachelor's degree in Electrical Engineering and Master's degree in Measurement & Control Engineering from Idaho State University in 2002 and 2005 respectively under the supervision of Dr. Subbaram Naidu.  I received the Ph.D. degree in Electrical Engineering from Colorado State University in 2009 under the supervision of Dr. Anthony A. Maciejewski.

My primary research interests revolve around machine learning, data analysis, and intelligent systems.  We're currently working at the intersection of multilinear subspace learning, dynamic graph theory, and time-series forecasting.

• 01/01/2024: Our NSF REU site entitled "Collaboration to Combat Crime" was selected for award.  We have open positions for undergraduate students in interested in pursuing research in data science to understand, dissrupt, and dissmantle criminal networks.   More information on the REU site can be found here.

• 12/01/2024: Our paper entitled "TSGCN: A Framework for Hierarchical Graph Representation Learning" has been accepted to the IEEE Transactions on Network Science and Engineering (TNSE)

• 09/04/2024: Our paper entitled "Evading VBA Malware Classification using Model Extraction Attacks and Stochastic Search Methods" has been accepted for publication in the IEEE Cyber Awareness and Research Symposium (CARS).

• 04/01/2024: Our paper entitled "Tensor Discriminant Analysis on Grassman Manifolds with Application to Human Action Recognition" has been accepted to the Springer Journal of Machine Learning and Cybernetics.

• 03/01/2024: Our proposal entitled "High spatial-temporal resolution soil moisture retrieval using deep learning fusion of multimodal satellite streams" has been selected for award through NASA (Collaboration with SDM, SDSU, and OLC).

• 08/21/2023: Dr. Hoover is currently on sabbatical for the Fall 2023 semester.

• 08/15/2023: Our Data Science Ph.D. student Cagri Ozdemir successfully defended his dissertation on "Multilinear Subspace Learning via Invertable Transforms and Grassman Manifold Analysis", he's now a postdoctoral scholar at University of North Texas.

• 09/2022: Our paper entitled "Anomaly Detection from Multilinear Observations via Time-Series Analysis and 3DTPCA" has been accepted for publication at the IEEE/ACM International Conference on Machine Learning and Applications.

• 09/2022: Our paper entitled "Kernelization of Tensor Discriminant Analysis with Application to Image Recognition" has been accepted for publication at the IEEE/ACM International Conference on Machine Learning and Applications.

• 06/2022: Our proposal entitled "Intelligent Automation through dynamic Networks and Multilinear Time-Series Analysis" has been selected for funding through the Naval Surface Warfare Center - Dahlgren Division (PI: Hoover, Co-PI: Caudle) 

• 05/2022: I was promoted from Associate Professor to Full Professor within the Computer Science and Engineering Department

• 5/2022: A new Ph.D. student (Jackson Cates) joined our group

• 5/2022: Our new Ph.D. program in Data Science & Engineering was approved.

• 09/2021: Our paper entitled "Fast Tensor Singular Value Decomposition Using the Low-Resolution Features of Tensors" has been accepted for publication at the IEEE/ACM International Conference on Machine Learning and Applications.

• 09/2021: Our paper entitled "Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting" has been accepted for publication at the IEEE/ACM International Conference on Machine Learning and Applications.

• 06/2021: Our proposal entitled "Governor’s Center for Understanding and Disrupting the Illicit Economy" has been selected for funding through the South Dakota's Governor's Office of Economic Development (SDM Team: PI: Jon Kellar, Co-PIs: Hoover and Crawford) 

• 05/2021: Our paper entitled "2DTPCA: A New Appraoch to Multilinear Principle Component Analysis" has been accepted for publication at the IEEE International Conference on Image Processing.

• 01/2021: Our paper entitled “Autonomous Multi-agent Systems Using SVGS Camera Sensor for Lunar Surface Mobility Applications”,has been accepted for publication at the IEEE Aerospace Conference, 2021

• 07/2020:  Our proposal entitled "Multilinear Subspace Methods for Learning and Recovory using Tensor-Tensor Decompositions" has been selected for funding through the National Science Foundation - CISE - RI program. (PI:  Hoover, Co-PIs:  Caudle & Braman) - we will have opening for a PhD student starting Fall 2020.

• 02/2020:  Our paper “Mobile Fiducial-Based Collaborative Localization and Mapping (CLAM): Preliminary Results and Future Directions” was accepted for publication at the USCToMM Symposium on Mechanical Systems and Robotics.

• 02/2020: Our paper “Validation of Vision-based State Estimation for Localization of Agents and Swarm Formation” was accepted for publication at the USCToMM Symposium on Mechanical Systems and Robotics.

• 02/2020: Our paper "A Review of Flow Field Forecasting: A High Dimensional Forecasting Procedure" was accepted for publication in the WIRES Journal on Computational Statistics.

• 01/2020: Received new Naval Surface Warfare Center - Keyport grant to support our research on "Swarm Localization and Intelligent Mapping (SLIM) for Unmanned Underwater Vehicle Swarms" (PI: Hadi Fekrmandi)

• 09/2019:  Our paper "Advanced Decision Making and Interpretability through Neural Shrubs" was accepted for publication/presentation at the 18th IEEE International Conference on Machine Learning and Applications (ICMLA).

• 06/2019: Our paper "Vision-based Guidance and Navigation for Swarm of Small Satellites in a Formation Flying Mission" was accepted for publication/presentation at the 32nd Florida Conference for Recent Advances in Robotics.

• 05/2019: Our paper "Underwater navigation using geomagnetic field variations" was accepted for publication/presentation at the IEEE International Conference on Electro/Information Technology (EIT).

• 04/2019: Congradulations Kavitha Konduru for successfully defending your thesis "Applicaiton of Image Segmentation to Analyze Biofilm Images".  Kavitha has accepted a permenent position with Regional Health on their programming team.

• 03/2019: Received new NASA seed grant from the SD Space Grant Consortium to support our research on "Cross Comparison of Virtual Reality Systems for Education and Research Suitability" (PI: Lisa Rebenitsch)

• 03/2019: Received new NASA seed grant from the SD Space Grant Consortium grant to support the "NASA Apollo 50th - Apollo Next Giant Leap Student Challenge" (PI: Jason Ash)

• 02/2019:  Received new Naval Surface Warfare Center - Dahlgren grant to support our research on "Dimensionality Reduction of Streaming Big Data for Clustering, Classification and Visualization via Incremental Multi-Linear Subspace Learning" (Co-PI: Kyle Caudle)

• 01/2019:  Received new NASA seed grant to support our research on "Developing Small Satellite Formation Flying Capability by Distributed State Estimation and Intelligent Control of Swarm using Vision-based Guidance" (PI: Hadi Fekrmandi, Co-PI: Zhen Ni (SDSU))

• 11/2018: Our paper "Examining Intermediate Data Reduction Algorithms for use with t-SNE" was accepted for publication/presentation at the 3rd International Conference on Compute and Data Analysis (ICCDA).

• 11/2018: Our paper "Building a Better Decision Tree by Delaying the Split Decision" was accepted for publication/presentation at the 3rd International Conference on Compute and Data Analysis (ICCDA).

• 11/2018:  Our paper "Flow Field Forecasting with Many Predictors" was accepted for publication/presentation at the 3rd International Conference on Compute and Data Analysis (ICCDA).

• 09/2018:  Our paper "Multi-Linear Discriminant Analysis through Tensor-Tensor Decompositions" was accepted for publication/presentation at the 17th IEEE International Conference on Machine Learning and Applications (ICMLA).