bootstrap website templates
Mobirise




About Me

I am currently an Associate Professor within the Department of Computer Science & Computer 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 robotic systems.  I have developed different approaches to dimensionality reduction, multi-linear subspace learning, and vision-based control of collaborative UAV and UGV swarms.

News

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).