Brian D. Bue: [News] [Bio] [CV] [Publications] [Software] [Teaching]
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Email: brian.bue@gmail.com Site updated: April 29, 2016 |
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News
Added my code to my github profile.
May 21, 2015: Fixed bug in continuum-curve generation in LINCR code. Thanks to Xiaojun Qiao for catching the error.
March 8, 2014: Moved site from http://www.ece.rice.edu/~bdb1/ to http://disambiguate.info.
March 6, 2014: Added missing cr.c file to LINCR package.
June 21, 2013: Posted new versions of RelTrans, MARTIAL and MCMTL toolkits.
June 3, 2013: HiiHAT ENVI/IDL toolkit open-sourced by JPL, now available on Sourceforge.
Bio
I am a research technologist in the Machine Learning and Instrument Autonomy Group at the NASA Jet Propulsion Laboratory.
I received my Ph.D. from the Electrical and Computer Engineering department, George R. Brown School of Engineering, Rice University in April 2013. My advisor was Erzsébet Merényi of the Department of Statistics.
From 2007 to 2010, I was a NASA Graduate Student Researchers Program fellow working on "Automatic Labeling of High Dimensional Remotely Sensed Imagery via Semantic Modeling." My primary advisor was Prof. Merényi and my NASA technical advisor was Kiri Wagstaff of Jet Propulsion Laboratory.
I was the primary developer (Nov. 2010-Oct. 2011) of the Hyperspectral Image Interpretation and Holistic Analysis Toolkit (Hii-HAT), originally designed by David Thompson (PI) and Lukas Mandrake.
Prior to joining JPL, I worked with Tomasz Stepinski, then of the Lunar and Planetary Institute, now at the Department of Geography, University of Cincinnati, on automated landform classification and crater detection from Mars Orbiter Laser Altimeter (MOLA) data.
I received a M.S. from the Purdue University Computer Science department in 2006, a B.S. in Computer Science and a B.A. in Mathematics from Augsburg College in Minneapolis, MN in 2003.
Professional bio sketch (last updated: April 29, 2016).
Curriculum Vitae
CV (pdf) (last updated: July 18, 2022).
Publications
Also see: Google scholar and Researchgate.
Ph.D. Thesis
- B. Bue, "Adaptive Similarity Measures for Material Identification in Hyperspectral Imagery," Ph.D. thesis, Rice University, April 2013 (defense slides, 40MB)
Journal
- B. Bue, "Low-rank Mahalanobis Metric Learning for Hyperspectral Image Classification: A Comparative Survey," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing - Special Issue on Machine Learning for Remote Sensing Data Processing, 2013 (in preparation).
- D. Thompson, B. Bornstein, S. Chien, S. Schaffer, D. Tran, B. Bue, Rebecca Castaño, D. Gleeson, and A. Noell, "Autonomous Spectral Discovery and Mapping Onboard the EO-1 Spacecraft," IEEE Transactions on Geoscience and Remote Sensing, to appear.
- B. Bue and E. Merényi, "An Adaptive Similarity Measure for Classification of Hyperspectral Signatures," IEEE Geoscience and Remote Sensing Letters, v. 10, iss. 2, p.381-385, Mar. 2013 (preprint, code)
- B. Bue, E. Merényi and B. Csathó, "Automated Labeling of Materials in Hyperspectral Imagery," IEEE Transactions on Geoscience and Remote Sensing, v. 48, iss. 11, p. 4059-4070, Nov. 2010. (preprint).
- T.F. Stepinski, M.P. Mendenhall and B. Bue, "Machine Cataloging of Impact Craters on Mars," Icarus, v. 203, iss. 1. p. 77-87, Sept. 2009.
- B. Bue and T.F. Stepinski, "Machine Detection of Martian Impact Craters From Digital Topography Data," IEEE Transactions on Geoscience and Remote Sensing, v. 45, iss. 1, p. 265-274, Jan. 2007.
- J. Huang, B. Bue, A. Pattath, D. Ebert and K. Thomas, "Interactive Illustrative Rendering on Mobile Devices," IEEE Computer Graphics and Applications. v. 27, iss 3, p. 48-56, May 2007.
- B. Bue and T.F. Stepinski, "Automated Classification of Landforms on Mars," Computers and Geosciences, v. 32, iss. 5, p. 604-614. Nov., 2005.
Conference
- B. Bue and C. Jermaine "Multiclass Domain Adaptation with Iterative Manifold Alignment," IEEE WHISPERS 2013, Gainesville, FL, June 2013. (code, slides)
- B. Bue, E. Merényi and J. Killian "Classification and Diagnosis of Myopathy from EMG Signals," 2nd Workshop on Data Mining for Medicine and Healthcare (DMMH), Austin, TX, May 2013. (slides)
- B. Bue and D. Thompson, "Multiclass Continuous Correspondence Learning," NIPS 2011 Domain Adaptation Workshop. Granada, ES., Dec. 2011. (poster)
- B. Bue, E. Merényi and B. Csathó, "An Evaluation of Class Knowledge Transfer from Synthetic to Real Hyperspectral Imagery," IEEE WHISPERS 2011. Lisbon, PT., June 2011. (code, slides)
- B. Bue, D. Thompson, M. Gilmore and R. Castaño, "Metric Learning for Hyperspectral Image Segmentation," IEEE WHISPERS 2011. Lisbon, PT., June 2011. (slides)
- B. Bornstein, D. Thompson, D. Tran, B. Bue, S. Chien and R. Castaño, "Efficient Spectral Endmember Detection Onboard the EO-1 Spacecraft," IEEE WHISPERS 2011. Lisbon, PT., June 2011. (slides)
- B. Bue and E. Merényi, "Using Spatial Correspondences for Hyperspectral Class Knowledge Transfer: Evaluation on Synthetic Data (updated version)," IEEE WHISPERS 2010. Reykjavik, IS., June 2010. (code, slides)
- B. Bue, E. Merényi and B. Csathó, "Automated Labeling of Segmented Hyperspectral Imagery via Spectral Matching," IEEE WHISPERS 2009. Grenoble, FR., Aug. 2009. (poster)
- J.L. Rich, B. Csathó, E. Merényi, B. Bue, C-L. Ping, and L. Everett, "Characterizing Polar Landscapes from Multi- And Hyperspectral Imagery," 9th International Conference on Permafrost, Fairbanks, AK., July 2008.
- B. Bornstein, B. Bue, S. Lee, and L. Mandrake, "Autonomous Identification and Quantification of Chemical Species with the Vehicle Cabin Atmosphere Monitor (VCAM) for use Onboard the International Space Station (ISS)," IEEE Aerospace Conference, Big Sky, MT., Mar. 2008.
- L. Mandrake, B. Bue, S. Lee, and B. Bornstein, "Lessons Learned from Reverse Engineering and Porting the NIST AMDIS COTS Algorithm to Flight Software," IEEE Aerospace Conference, Big Sky, MT., Mar. 2008.
- R. Castaño, T. Estlin, D. Gaines, B. Bornstein, R. C. Anderson, B. Bue, C. Chouinard, and M. Judd, "Experiments in Onboard Rover Traverse Science," IEEE Aerospace Conference, Big Sky, MT., Mar. 2008.
- R. Castaño, K. Wagstaff, D. Gleeson, R. Pappalardo, S. Chien, D. Tran, L. Scharenbroich, B. Tang, B. Bue, T. Doggett, "Onboard Detection of Active Canadian Sulfur Springs: A Europa Analogue," 9th International Symposium on Artificial Intelligence, Robotics and Automation for Space, Universal City, CA., Feb. 2008.
Technical Reports
- B. Bue, E. Merényi and K. Wagstaff, "Automatic Labeling of Hyperspectral Imagery via Semantic Modeling," NASA Graduate Student Researchers Program final report, CL#11-0785 (available by request).
Software
Note: for the latest updates to the packages below, see my github profile.
- Hyperspectral Image Interpretation and Holistic Analysis Toolkit (HiiHAT) - ENVI/IDL plugin to help analysts efficiently browse, summarize, and search hyperspectral images: project info, open-source implementation available on Sourceforge.
- MAnifold Reconciliation Through Iterative ALignment (MARTIAL) algorithm - extension to RelTrans framework which uses the Multiclass Continuous Correspondence Learning (MCCL) algorithm combined with a modified version of the TRiplet-based Iterative ALignment (TRIAL) manifold alignment algorithm of Venkateswaran et al.: MATLAB (README) (requires RelTrans framework, updated: June 21, 2013)
- Relational Class Knowledge Transfer (RelTrans) framework - multiclass, similarity-based domain adaptation framework that computes a cross-domain mapping based upon pairs of canonical pivot samples representing similar classes shared between the domains: MATLAB (README) (updated: June 21, 2013)
- MultiClass MultiTask Learning (MCMTL) decomposition - decomposes a multiclass multitask/domain-adaptation problem into multiple (1vsRest or 1vs1) binary multitask/domain-adaptation problems. Includes example learning/prediction functions for the MALSAR toolkit: MATLAB (README) (updated: June 17, 2013)
- Hybrid LDA - hybrid metric learning using regularized Linear Discriminant Analysis: Python, Matlab (README) (updated: May 14, 2012)
- LINCR - library for piecewise LINear Continuum Removal: C (standalone), Python (README) (updated: May 21, 2015)
- image_annotate.py - simple python image annotation tool: Python (README) (updated: June 02, 2012)
Teaching
For each Fall semester from 2008 to 2010, I assisted Prof. Devika Subramanian with her course "Introduction to Computational Thinking."
During Spring semester 2009, I was a teaching assistant for both ELEC502: Artificial Neural Networks with Prof. Merényi and COMP540: Machine Learning, also with Prof. Devika Subramanian.
While at Purdue, I was a teaching assistant for Systems Programming Laboratory (C), and Compilers: Principles and Practice, both with Dennis Brylow (now with the Dept. of Computer Science, Marquette University ).