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NETS Team
Publications

Florida Institute of Technology

Home

Research
NETS Team
Publications

Florida Tech
Nets
NETS Team

NETS Team

NETS Team

The NETS Lab was established in 2021 and is led by Dr. Ryan T. White. The team consists of students at all levels!

Meet the Team

Dr. Ryan T. White
Director of the NETS Lab

Nehru Attzs
PhD Candidate

Mackenzie Meni
PhD Candidate

Trupti Mahendrakar
PhD Candidate

Dr. Ryan T. WhiteDirector of the NETS Lab

Assistant Professor, Department of Mathmematical Sciences

rwhite@fit.edu

Research: Deep learning, computer vision, edge computing, natural language processing, probability, stochastic analysis, and statistics. Projects have spanned astronautics, aerospace engineering, biomedical engineering, genetics, biology, ecology, glaciology.

Background: PhD Applied Mathematics (2015) at Florida Tech, AI/ML and algorithm development, stochastic analysis.

Recent Works: See Dr. White's Google Scholar profile

Nehru AttzsPhD Candidate

mattzs2012@my.fit.edu

Research: Efficient object tracking algorithms for edge hardware

Background: Aerospace engineering

Recent Works:

M. N. Attzs, T. Mahendrakar, M. Meni, R. T. White, and I. Silver (2023). A comparison of tracking-by-detection algorithms for real-time satellite component tracking. 37th Annual Small Satellite Conference. https://digitalcommons.usu.edu/smallsat/2023/all2023/225/

T. Mahendrakar, M. N. Attzs, J. M. Duarte, A. L. Tisaranni, R. T. White, and M. Wilde. Impact of intra-class variance on YOLOv5 model performance for autonomous navigation around non-cooperative targets. AIAA SCITECH 2023 Forum. https://arc.aiaa.org/doi/abs/10.2514/6.2023-2374

Mackenzie MeniPhD Candidate

mmeni2021@my.fit.edu

Research: Information theoretic analysis of neural models, explainable AI, detecting bias

Background: Software development at USGS, ML researcher at US Army Corps of Engineers, Data Scientist in private sector

Recent Works:

M. Mattei, M. J. Meni, R. Hillner, E. Christ, K. Chandra, V. Chivukula, and R. T. White (2024). Evaluating Performance of Physics-Informed Neural Networks for Predicting 3D Blood Flow Patterns. (Submitted)
M. J. Meni, R. T. White, M. L. Mayo, and K. Pilkiewicz (2024). Entropy-based Guidance of Deep Neural Networks for Accelerated Convergence and Improved Performance. Accepted at Information Sciences. Preprint: https://arxiv.org/abs/2308.14938
K. Taylor, M. J. Meni, and R. T. White (2024). PEEKing into the Universe. Conference for Undergraduate Women in Physics (CUWiP). Poster presentation.
M. J. Meni, T. Mahendrakar, R. T. White, M. L. Mayo, and K. Pilkiewicz (2024). Taking a PEEK into YOLOv5 for Satellite Component Recognition via Entropy-based Visual Explanations. AIAA SCITECH Forum 2024. https://arc.aiaa.org/doi/abs/10.2514/6.2024-2766
M. J. Meni and R. T. White. Information-Informed Neural Networks: Probabilistically Interpretable Neural Decisionmaking. Invited talk at Frontiers in Geoscience Seminar, Earth and Environmental Sciences (EES) division and the Center for Space and Earth Science (CSES), Los Alamos National Lab, Los Alamos, NM, Aug 13, 2023.
M. J. Meni, K. Daust, T. Jia, and R. T. White (2023). Wind Forecasting with Recurrent Neural Networks. PIMS Workshop on Forecasting and Mathematical Modeling for Renewable Energy. (Poster presentation).
M. N. Attzs, T. Mahendrakar, M. J. Meni, R. T. White, and I. Silver (2023). A comparison of tracking-by-detection algorithms for real-time satellite component tracking. 37th Annual Small Satellite Conference. https://digitalcommons.usu.edu/smallsat/2023/all2023/225/

Trupti MahendrakarPhD Candidate

(Major collaborator with primary affiliation with the Autonomy Lab)

tmahendrakar2020@my.fit.edu

Research: On-orbit servicing, autonomous proximity operations, guidance and navigation

Background: Aerospace Engineering at NASA Jet Propulsion Laboratory, Collins Aerospace, and Delta Air Lines

Recent Works:

T. Mahendrakar, R. T. White, M. Wilde, and M. Tiwari (2024). Real-time, On-board Spacecraft Feature Detection with Lightweight CNNs. Submitted.
V. M. Nguyen, E. Sandidge, T. Mahendrakar, and R. T. White (2024). Characterizing Satellite Geometry via Accelerated 3D Gaussian Splatting. Submitted. https://arxiv.org/abs/2401.02588
M. J. Meni, T. Mahendrakar, R. T. White, M. L. Mayo, and K. Pilkiewicz (2024). Taking a PEEK into YOLOv5 for Satellite Component Recognition via Entropy-based Visual Explanations. AIAA SCITECH Forum 2024. https://arc.aiaa.org/doi/abs/10.2514/6.2024-2766
M. N. Attzs, T. Mahendrakar, M. Meni, R. T. White, and I. Silver (2023). A comparison of tracking-by-detection algorithms for real-time satellite component tracking. 37th Annual Small Satellite Conference. https://digitalcommons.usu.edu/smallsat/2023/all2023/225/
T. Mahendrakar, R. T. White, M. Wilde, and M. Tiwari. SpaceYOLO: A Human-Inspired Model for Real-time, On-board Spacecraft Feature Detection. IEEE Aerospace Conference 2023. https://arxiv.org/abs/2302.00824
A. Ekblad, T. Mahendrakar, R. T. White, M. Wilde, I. Silver, B. Wheeler. Resource-constrained FPGA Design for Satellite Component Feature Extraction. IEEE Aerospace Conference 2023. https://arxiv.org/abs/2301.09055
B. Caruso, T. Mahendrakar, V. M. Nguyen, R. T. White, Todd Steffen. 3D Reconstruction of Non-cooperative Resident Space Objects using Instant NGP-accelerated NeRF and D-NeRF. AAS/AIAA Spaceflight Mechanics Conference 2023. https://arxiv.org/abs/2301.09060
T. Mahendrakar, S. Holmberg, A. Ekblad, E. Conti, R. T. White, M. Wilde, and I. Silver. Autonomous Rendezvous with Non-cooperative Target Objects with Swarm Chasers and Observers. AAS/AIAA Spaceflight Mechanics Conference 2023. https://arxiv.org/abs/2301.09059
T. Mahendrakar, M. N. Attzs, J. M. Duarte, A. L. Tisaranni, R. T. White, and M. Wilde. Impact of Intra-class Variance on YOLOv5 Model Performance for Autonomous Navigation around Non-Cooperative Targets. AIAA SCITECH Forum 2023. https://doi.org/10.2514/6.2023-2374
T. Mahendrakar, A. Ekblad, N. Fischer, M. Wilde, R. T. White, B. Kish, and I. Silver. Performance Study of YOLO V5 and Faster RCNN for Autonomous Navigation around Non-Cooperative Targets. IEEE Aerospace Conference 2022. https://doi.org/10.1109/AERO53065.2022.9843537

T. Mahendrakar, R. T. White, M. Wilde, A. Rivikin, J. Cutler, K. Watkins, A. Ekblad, and N. Fischer. Use of artificial intelligence for feature recognition and flightpath planning around non-cooperative resident space objects. AIAA ASCEND 2021. https://arc.aiaa.org/doi/abs/10.2514/6.2021-4123

T. Mahendrakar, R. T. White, and M. Wilde (2021). Real-time satellite component recognition YOLO V5. 35th Annual Small Satellite Conference. https://digitalcommons.usu.edu/smallsat/2021/all2021/51/

Arianna Issitt
PhD Student

Emily Happy
PhD Student

Abhishek Chothani
MS Student

Lizzy Crist
Undergraduate Researcher

Arianna IssittPhD Student

Research: computer vision and edge computing for 3D reconstruction of satellites on orbit, Physics guided neural networks for bloodflow modeling.

Background: Object detection, edge hardware, swarms; Summer Graduate Student with Air Force Research LAboratory Space Vehicles Directorate

Emily HappyPhD Student

Finishing as an MS Student, University of Edinburgh

Research: Computer vision, spacecraft feature detection, glacier tracking, GIS

Experience: Computer vision contractor with a defense contractor

Abhishek ChothaniMS Student

Research: multi-view, 3D object detection; robotics with low-cost materials

Lizzy CristUndergraduate Researcher

Research: Bloodflow modeling

Lamine Deen
Undergraduate Researcher

Annika Leiseth
Undergraduate Researcher

Blake Gisclair
Undergraduate Researcher

Alex Merino
Undergraduate Researcher

Lamine DeenUndergraduate Researcher

Annika LeisethUndergraduate Researcher

Research: Analysis of inflation dependence of global development data

Blake GisclairUndergraduate Researcher

Research: geophysical signals processing

Alex MerinoUndergraduate Researcher

Research: geophysical signals processing

Former Students

Gone but not forgotten! :)

Minh Nguyen, PhD
AI Engineer III, UF-NVIDIA Technology Center

Andrew Ekblad, MS
FPGA Engineer, L3Harris

Emma Sandidge
PhD Student, Florida International Univeresity

Anthony Garcia Romano

Minh Nguyen, PhDAI Engineer III, UF-NVIDIA Technology Center

PhD, Operations Research '24

https://www.linkedin.com/in/minhnguyen251/

Research: Generative AI: synthetic electronic health record generation, computer vision, NLP, 3D rendering

Background: Medical data analytics at Truveta, NLP engineer with CSE department

Recent Works:

V. M. Nguyen, E. Sandidge, T. Mahendrakar, and R. T. White (2024). SatSplatYOLO: 3D Gaussian Splatting-based Virtual Object Detection Ensembles for Satellite Feature Recognition. 4th Space Imaging Workshop. https://arxiv.org/abs/2406.02533
V. M. Nguyen, E. Sandidge, T. Mahendrakar, and R. T. White. Characterizing Satellite Geometry via Accelerated 3D Gaussian Splatting. Aerospace 11(3), 183. https://doi.org/10.3390/aerospace11030183
B. Nagda, V. M. Nguyen, and R. T. White. Hard Pattern Mining and Ensemble Learning for Detecting DNA Promoter Sequences. IEEE/ACM Transactions on Computational Biology and Bioinformatics. https://ieeexplore.ieee.org/abstract/document/10342761
A. Tikayat Ray, A. P. Bhat, R. T. White, V. M. Nguyen, O. J. Pinon Fischer, D. and N. Mavris (2023). Examining the Potential of Generative Language Models for Aviation Safety Analysis: Case Study and Insights Using the Aviation Safety Reporting System (ASRS). Aerospace 10 (9), 770. https://doi.org/10.3390/aerospace10090770

B. Caruso, T. Mahendrakar, V. M. Nguyen, R. T. White, and T. Steffen (2023). 3D reconstruction of noncooperative resident space object using Instant NeRF and D-NeRF. 33rd AAS/AIAA Space Flight Mechanics Meeting. https://arxiv.org/abs/2301.09060

J. H. Dshalalow, V. M. Nguyen, R. R. Sinden, and R. T. White (2022). Determination of Mutation Rates with Two Symmetric and Asymmetric Mutation Types. Symmetry, 14(8):1701. https://www.mdpi.com/2073-8994/14/8/1701

Andrew Ekblad, MSFPGA Engineer, L3Harris

aekblad2019@my.fit.edu

Research: Computer vision, FPGAs

Recent Works:

A. Ekblad, T. Mahendrakar, R. T. White, M. Wilde, I. Silver, B. Wheeler. Resource-constrained FPGA Design for Satellite Component Feature Extraction. To appear at IEEE Aerospace Conference 2023. https://arxiv.org/abs/2301.09055

T. Mahendrakar, S. Holmberg, A. Ekblad, E. Conti, R. T. White, M. Wilde, and I. Silver. Autonomous Rendezvous with Non-cooperative Target Objects with Swarm Chasers and Observers. AAS/AIAA Spaceflight Mechanics Conference 2023. https://arxiv.org/abs/2301.09059

T. Mahendrakar, A. Ekblad, N. Fischer, M. Wilde, R. T. White, B. Kish, and I. Silver. Performance Study of YOLO V5 and Faster RCNN for Autonomous Navigation around Non-Cooperative Targets. IEEE Aerospace Conference 2022. https://doi.org/10.1109/AERO53065.2022.9843537

T. Mahendrakar, A. Rivikin, J. Cutler, K. Watkins, A. Ekblad, N. Fischer, R. T. White, and M. Wilde. Use of artificial intelligence for feature recognition and flightpath planning around non-cooperative resident space objects. AIAA ASCEND 2021. https://arc.aiaa.org/doi/abs/10.2514/6.2021-4123

Emma SandidgePhD Student, Florida International Univeresity

Recent Works:

V. M. Nguyen, E. Sandidge, T. Mahendrakar, and R. T. White (2024). SatSplatYOLO: 3D Gaussian Splatting-based Virtual Object Detection Ensembles for Satellite Feature Recognition. 4th Space Imaging Workshop. https://arxiv.org/abs/2406.02533
V. M. Nguyen, E. Sandidge, T. Mahendrakar, and R. T. White. Characterizing Satellite Geometry via Accelerated 3D Gaussian Splatting. Aerospace 11(3), 183. https://doi.org/10.3390/aerospace11030183

Anthony Garcia Romano

Research: glacier tracking, satellite component recognition

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