15 Running Court, Baltimore, MD 21221

Phone: (410) 780-0768

E-mail: dheinz1@gl.umbc.edu

URL: www.gl.umbc.edu/~dheinz1

CAREER GOAL A research and development position in the signal processing and communications industry.

EDUCATION

University of Maryland, Baltimore County, Ph.D. Candidate, Electrical Engineering.

Ph.D. Thesis: Detection, Classification and Quantification of Subpixel Spectral Signatures in Hyperspectral and Multispectral Images. (Expected Graduation: May, 2001)

Thesis can be completed at home while working for industry full time.

Loyola College, M.E.S, Electrical Engineering, May 1994.

State University of New York at Buffalo, B.S., Electrical Engineering, February 1991.

May 2000 - Present

Electro Optics System Engineer, Northrop Grumman, Baltimore, MD

• Currently developing detection, tracking and resolution enhancement algorithms for a real-time infrared distributed aperture system. Verifying system performance through detailed data simulations using MATLAB.

January 2000 – May 2000, June 1999 - August 1999 and January 1997 - January 1998,

Research Assistant, Remote Sensing Signal and Image Processing Laboratory

• Developed algorithms for supervised and unsupervised detection and quantification of targets in hyperspectral and multispectral imagery (HYDICE, AVIRIS, SPOT, Landsat) for HYMSMO program.
• Filed two disclosures of invention based on algorithms developed. The first invention provides an efficient algorithm for generating the required constrained least squares solution. The second invention uses the first invention for automatic target detection and quantification, data compression and noise estimation.

September 1999 – December 1999, Instructor, University of Maryland, Baltimore County

• Course: CMSC 104 Problem Solving and Computer Programming.
• Projects were performed using the C language running under a UNIX operating system.

January 1998 – June 1999, Teaching Assistant, University of Maryland, Baltimore County

• Course: CMSC 201 Computer Science I.
• Course material included functions, recursion, arrays, strings, pointers, records and files.
• Projects were performed using the C language running under a UNIX operating system.

February 1996 – January 1997, Engineer III, Tracor Applied Sciences, Inc., California, MD

• Led a distance learning project using video teleconferencing technologies.
• Analyzed the technical difficulties involved in replacing an analog space division switch with a commercial off-the-shelf digital time division switch.

May 1991 - February 1996, Electronics Engineer, United States Army Chemical and Biological Defense Command, Aberdeen Proving Ground, MD

• Responsible for reviewing, testing, and evaluating the design and documentation of an Automatic Chemical Agent Alarm (ACADA).
• Provided detailed analysis of the ACADA’s communication interface, real-time software, Application Specific Integrated Circuits (ASICs), high voltage power supply, direct current (DC) to DC converter, power supply, battery assembly, and horn circuit designs.
• Provided detailed knowledge of the ACADA’s detection algorithm and digital filter design.
• Planned, coordinated, and executed the full Electromagnetic Interference (EMI) test and evaluation of the ACADA system.

Phi Kappa Phi – Honor Society

The Institute of Electrical and Electronics Engineers

The International Society for Optical Engineering

FE/EIT Exam Passed October 1994.

Dean's List Fall 1990, Spring 1990, and Fall 1989.

Dr. Chein-I Chang, Associate Professor, UMBC, (410) 455-3502

Dr. Mark Althouse, Technical Director, Department of Defense (443) 421-1337

Sue Bogar, Lecturer, UMBC, (410) 455-3964

• Daniel Heinz and Chein-I Chang, Methods and Apparatus for Constraint Least Squares Linear Spectral Mixture Analysis for Hyperspectral and Multispectral Image Analysis.

1. Heinz, D. C. and Chang, C.-I, An Efficient Algorithm for Solving Constrained Optimization Problems, May 1999.
2. Heinz, D. C. and Chang, C.-I, Constrained Least Squares Linear Spectral Mixture Analysis Methods for Material Abundance Estimation, Discrimination, Detection, Classification, Identification, Recognition and Quantification, Data Compression and Noise Estimation in Hyperspectral and Multispectral Imagery, Feb. 2000.

1. C.-I Chang and D. Heinz, "Subpixel spectral detection for remotely sensed images," IEEE Trans. on Geoscience and Remote Sensing, vol. 38, no. 3, 1144-1159, May 2000.
2. D. C. Heinz and C.-I Chang, "Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery," IEEE Trans. on Geoscience and Remote Sensing. (accepted)
3. D. C. Heinz and C.-I Chang, "Unsupervised Constrained Least Squares-Based Quantification of Materials in Multispectral Imagery," IEEE Trans. on Systems, Man and Cybernetics. (submitted)
4. Du, Q., C-I. Chang, D.C. Heinz, M.L.G. Althouse and I.W. Ginsberg "Hyperspectral Image Compression for Target Detection and Classification," IEEE Trans. on Geoscience and Remote Sensing. (submitted)

1. Daniel Heinz, Chein-I Chang and M.L.G. Althouse, "Fully constrained least-squares based linear unmixing," International Geoscience and Remote Sensing Symposium, Hamburg, Germany, 28 June – 2 July, 1999.
2. C.-I Chang and D. C. Heinz, "Constrained subpixel target detection for hyperspectral imagery," SPIE's 14th Annual International Symposium on AeroSense, Orlando, Florida, 24-28 April, 2000.
3. D. C. Heinz and C.-I Chang, "Constrained least squares linear spectral mixture analysis for detection and quantification in multispectral imagery," International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 24- 28 July, 2000.
4. Du, Q., C-I. Chang, D.C. Heinz, M.L.G. Althouse and I.W. Ginsberg "Hyperspectral Image Compression for Target Detection and Classification," International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 24- 28 July, 2000.