Brief bio
I am currently a 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 my Ph.D. 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, data‑driven dynamic systems, and time‑series forecasting.
Latest updates
Grants, papers, defenses, and new group members — roughly chronological, most recent first.
- Aug 2026
Our proposal entitled “Data‑Driven Discovery of Governing Equations for Multidimensional Engineering Systems” has been selected for funding by the National Science Foundation — CMMI‑DCSD program (PI: Hoover, Co‑PIs: May & Zhao).
- Aug 2026
Our proposal entitled “South Dakota Center for Advanced Research in Materials, Operations, and Resilience (SD‑ARMOR)” has been selected for funding through the South Dakota Board of Regents and Governor's Office of Economic Development, Governor's Research Center of Excellence (PI/Director: Hoover, Co‑PIs span five BOR institutions — SDSU, DSU, USD, & BHSU). More information about the center can be found at sdarmor.org.
- Aug 21, 2026
We welcome our new Ph.D. student Hari Priya Telidevara to the Mines Machine Learning and Intelligent Systems Lab.
- Jul 15, 2026
Congratulations to Jacob James (Ph.D. student in MMLIS‑L) on his paper “Smooth Latent Adaptive Trajectory Estimator (SLATE)” accepted to the IEEE/ACM International Conference on Machine Learning & Applications.
- Jul 15, 2026
Our paper “Koopman Operator Identification of Model Parameter Trajectories for Temporal Domain Generalization (KOMET)” accepted to the IEEE/ACM International Conference on Machine Learning & Applications.
- Feb 27, 2026
Congratulations to Sherwyn Braganza (Ph.D. student in MMLIS‑L) on his paper “An Optimized and Integrated Robust Tool for Pangenome Generation” accepted in the Springer Journal on Functional & Integrated Genomics.
- Aug 20, 2025
We welcome our new Ph.D. student Kazi Mehrab Rashid to the Mines Machine Learning and Intelligent Systems Lab.
- Aug 20, 2025
We welcome our new M.S. student Braydon Jones to the Mines Machine Learning and Intelligent Systems Lab.
- Aug 20, 2025
We welcome our new M.S. student John Miller to the Mines Machine Learning and Intelligent Systems Lab.
- Mar 20, 2025
Our Data Science Ph.D. student Jackson Cates successfully defended his dissertation on “Multilinear Methods for Graph Forecasting and Analysis.” He's now a Data Scientist in Fort Collins, CO.
Show earlier news (2018 – 2024) ▾
- May 7, 2025
Our Computer Science M.S. student Jacob James successfully completed his degree and is now pursuing a Ph.D. in Data Science and Engineering at SD Mines.
- Sep 9, 2024
Our Data Science Ph.D. student Brian Fehrman (co‑advised with Dr. Francis Akowuah) successfully defended his dissertation on “Investigating Machine Learning VBA Macro Analysis using Machine Learning in a Constrained Environment.” He's currently working for Black Hills Information Security.
- Jan 1, 2024
Our NSF REU site entitled “Collaboration to Combat Crime” was selected for award. We have open positions for undergraduate students interested in pursuing research in data science to understand, disrupt, and dismantle criminal networks. More information on the REU site can be found here.
- Dec 1, 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).
- Sep 4, 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).
- Apr 1, 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.
- Mar 1, 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 SD Mines, SDSU, and OLC).
- Aug 21, 2023
Dr. Hoover is currently on sabbatical for the Fall 2023 semester.
- Aug 15, 2023
Our Data Science Ph.D. student Cagri Ozdemir successfully defended his dissertation on “Multilinear Subspace Learning via Invertible Transforms and Grassman Manifold Analysis.” He's now a postdoctoral scholar at the University of North Texas.
- Sep 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.
- Sep 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.
- Jun 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).
- May 2022
I was promoted from Associate Professor to Full Professor within the Computer Science and Engineering Department.
- May 2022
A new Ph.D. student, Jackson Cates, joined our group.
- May 2022
Our new Ph.D. program in Data Science & Engineering was approved.
- Sep 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.
- Sep 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.
- Jun 2021
Our proposal entitled “Governor's Center for Understanding and Disrupting the Illicit Economy” has been selected for funding through South Dakota's Governor's Office of Economic Development (SD Mines team — PI: Jon Kellar, Co‑PIs: Hoover and Crawford).
- May 2021
Our paper entitled “2DTPCA: A New Approach to Multilinear Principal Component Analysis” has been accepted for publication at the IEEE International Conference on Image Processing.
- Jan 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.
- Jul 2020
Our proposal entitled “Multilinear Subspace Methods for Learning and Recovery using Tensor‑Tensor Decompositions” has been selected for funding through the National Science Foundation — CISE‑RI program (PI: Hoover, Co‑PIs: Caudle & Braman). We had an opening for a Ph.D. student starting Fall 2020.
- Feb 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.
- Feb 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.
- Feb 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.
- Jan 2020
Received a 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).
- Sep 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).
- Jun 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.
- May 2019
Our paper “Underwater Navigation Using Geomagnetic Field Variations” was accepted for publication/presentation at the IEEE International Conference on Electro/Information Technology (EIT).
- Apr 2019
Congratulations to Kavitha Konduru for successfully defending her thesis, “Application of Image Segmentation to Analyze Biofilm Images.” Kavitha accepted a permanent position with Regional Health on their programming team.
- Mar 2019
Received a 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).
- Mar 2019
Received a new NASA seed grant from the SD Space Grant Consortium to support the “NASA Apollo 50th — Apollo Next Giant Leap Student Challenge” (PI: Jason Ash).
- Feb 2019
Received a 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).
- Jan 2019
Received a 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).
- Nov 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).
- Nov 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).
- Nov 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).
- Sep 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).
Randy C. Hoover