Eric P. Lam, Ph.D.




Ph.D. in Computer Engineering

University of California, Santa Cruz2001


M.S. in Electrical Engineering (Signal and Image Processing emphasis)

University of Southern California1998


M.S. in Electrical Engineering (Communications emphasis)

California State Polytechnic University, Pomona1997


B.S. in Electrical Engineering

California State Polytechnic University, Pomona1995


Professional Experience

TASC, an Engility company

San Bernardino, CA

June 2016- present

Systems Engineer

Modification of 6DOF simulation written in C++ and FORTRAN for V&V of SpaceX Falcon program.  Independent Verification and Validation using MATLAB, and Simulink of SpaceX Falcon program.



Torrance, CA

June 2012- June 2016

Product Trainer

Trained customers to use tools of MathWorks, which include MATLAB and Simulink.  Traveled to customer-sites (corporations and U.S. military sites) and public training facilities on other domain knowledge involving specific skillsets such as signal processing, image processing, Object-Oriented MATLAB (with comparison with C++ examples) and automatic C code generation with MATLAB.  Other training also model-based design, algorithm development, signal processing, C code generation, and HDL code generation using Simulink.  Developed functionality equivalent to STK Connector (a product of AGI to interface MATLAB and STK) for use in Simulink via use of Level 2 function block.  Developed new course content for computer vision (to be released in 2015) based on previous Northrop Grumman experience with OpenCV/C++ and Intel IPP/IPL.  Examples in new course include feature extraction, segmentation (based on color space and shape/morphological operations or texture), alignment using Hough transform, and detection of edges.


EPLAM Systems

Diamond Bar, CA

August 2011 - Present

Founder and President

Consulting company aims to provide solutions for industry-focused services for the purpose of supporting engineering firms, contractors, and government agencies.  Company specializes in image processing, algorithm analysis and development, radar systems, and simulations.  Prepare Small Business Innovation Research (SBIR) proposals to Department of Defense, Department of Transportation, and National Science Foundation on topics ranging from radar simulations and image processing.  Recent consulting tasks include model-based design and implementation of remote sensing algorithm using Simulink using signal processing, phased array antennas, and embedded code generation.


California State Polytechnic University, Pomona

March 2011-January 2012


Prepared lecture material and taught course in Electrical Engineering.  Taught students how to use  MATLAB/Simulink for signal and systems lab.  Due to limited floating licenses of MATLAB/Simulink, we used Python as an alternative language.


Thales Raytheon Systems

Fullerton, CA

2005- August 2011

Senior Principal Systems Engineer


Worked on C program that simulates the performance of battlefield radar.  Code uses actual tactical code from radar signal processor (RSP).  Program creates an environment of targets (mortars and artillery shells) and other environmental variables to invoke operation on simulation.  Added higher fidelity model of radar cross section that is a function of range, Doppler rate, and radar frequency. This tool was used by various radar programs.


Implemented helicopter discrimination algorithm on TPQ-36 Firefinder weapon locating radar to reduce false locations.  Algorithm was developed in MATLAB, tested with data recordings, and finally ported back to C tactical code as part of a time and materials effort.


Lead team in Netted Battlefield Radar Sensors to fuse data with different battlefield radar systems.  This was demonstrated with simulation.  Using actual radars, we attempt to reduce false locations by fusing air defense radar data to be used with weapon locating radar.  This effort was awarded the Excellence in Engineering and Technology awards in 2009 at the NCS and corporate levels.  Used MATLAB, C, BASH scripting, and Python for implementation of demonstration without radars.  Second phase of demonstration used actual radars with UDP.  Wireshark used to troubleshooting network packets.


Worked as the radar simulation technical lead for new ground-based radar system.  Created a desktop simulation testbed that wrapped around radar tactical code to predict performance for various ballistic projectiles.  Used C++ for this testbed and radar cross section data from data generated with FEKO and Xpatch. Some algorithms written in MATLAB were manually ported to C/C++.  Some C++ routines were overloaded to accommodate different types of data available.


DoD Secret Inactive



Raytheon Space and Airborne Systems

El Segundo, CA


Senior Systems Engineer 2


Worked on image resolution improvement algorithms from sequence of low resolution images to create higher resolution image.  Investigated deinterlacing algorithms and measurement of correct deinterlace.  Investigate sub-pixel image registration for possible improvements.


Worked on algorithms in radar jammer mitigation for various types of electronic attacks.  Adaptive signal processing and singular value decomposition (SVD) were some of the techniques.  Parallelized simulations on a multi-node commercial-off-the-shelve network of workstations.





Northrop Grumman Missions Systems (formerly TRW)

Redondo Beach and Carson, CA


Senior Systems Engineer


Worked on image processing algorithms.  Improved floating-point operations on the discrete cosine transform.  Wrote white papers involving object detection, wavelet image compression, change detection, image mosaic creation using moving image sequences with Intel IPL and C++.  Python was used as an alternative to MATLAB (which was not available due to cost).


Wrote C code to interface HP network analyzer and GPS receiver using HPIB (IEEE 488) to collect antenna radiation pattern from an SUV. Collected data (time, location, and antenna information) were analyzed offline using MATLAB.


Built a testbed with S-Band RF hardware (combiners/splitters/switches/attenuators) and TTL logic to simulate effects of path loss attenuation (due to free space and other sources of attenuation). Attenuation was controlled with Windows PC's parallel port and variable voltage-controlled attenuators (VVAs). C code was written to control parallel port which was connected to TTL logic. TTL logic controls the VVAs. Attenuators can be selectively controlled with command word and value of attenuation at any time via look-up table versus time.




Microsim Corporation

Irvine, CA

Summer 1996

Engineering Intern

Developed and tested semiconductor models for company’s PSpice software.


Relevant Skills

C, C++, C#, Git source control, MATLAB (expert level), converting MATLAB code to C by hand, Simulink, Linux, Mac OSX, signal processing (wavelets, image processing and compression), Perl, linear regression models, Python


Relevant Coursework and Work Experience

Signal processing, image processing, pattern recognition, linear algebra, neural networks, simulations (MATLAB, C/C++), regression modelling, BASH scripting

MOOC Course from “GPS: An Introduction to Satellite Navigation, with an interactive Worldwide Laboratory using Smartphones” completed Dec 21, 2014.


Other Computer Skills

Verilog, VHDL, Java, understanding of JPEG and MPEG, data compression, space-time adaptive processing (STAP), OpenCV, OpenGL, STK (certified by AGI), automatic C and HDL code generation via MATLAB/Simulink, Eclipse, Visual Studio




Eric P. Lam.  “Visualizing Wavelet Decomposition Strengths for Pattern Recognition Supervised Training.” IASTED Computer Graphics and Imaging, August 13-16, 2001: Honolulu, Hawaii, USA


Eric P. Lam.  “Parallelizing the Discrete Wavelet Transform with a SIMD Architecture.” IASTED Parallel and Distributed Computing and Systems, August 21-24, 2001: Anaheim, California, USA


Alison Luo, Eric P. Lam and Ahmed Amer. “Texture Classification Using Wavelets and Vector Quantization.” Proceedings of the 1st IEEE International Symposium on Signal Processing and Information Technology. Cairo, Egypt: December 2001


Eric P. Lam, Christopher Leddy, Stephen Nash, and H. Alan Parks.  A No-Reference Quality Metric for Evaluating Deinterlaced Video Frames  Proceedings of SPIE Infrared Technology and Applications XXXII, April 17-21, 2006: Kissimmee, Florida, USA


Eric P. Lam, An Edge Directed Image Interpolation Technique Based on Wavelet Preprocessing. IEEE Medical Imaging Conference (MIC) 2006, October 29- November 4, 2006: San Diego, California, USA


Eric P. Lam, Wavelet-based Texture Classification Using Vector Quantization. SPIE Electronic Imaging Conference (EI) 2007, January 28-February 1, 2007: San Jose, California, USA


Eric P. Lam, Texture Classification Using Wavelet-Preprocessing and Vector Quantization. SPIE Defense and Security Symposium (DSS) 2007, April 9-13, 2007: Orlando, Florida, USA


Eric P. Lam, Image Quality Measure Using a Quadtree Homogeneity Analysis. SPIE Defense and Security Symposium (DSS) 2007, April 9-13, 2007: Orlando, Florida, USA


Eric P. Lam, Christopher A Leddy, and Stephen R. Nash, An Image Sharpness Metric for Image Processing Applications Using Feedback . SPIE Defense and Security Symposium (DSS) 2007, April 9-13, 2007: Orlando, Florida, USA


Eric P. Lam and Kenny C. Loo, An Image Similarity Measure Using Homogeneity Regions and Structure. SPIE Electronic Imaging Conference (EI) 2008, January 28-February 1, 2008: San Jose, California, USA


Boris Abramov, H. Walker Birrell and Eric P. Lam, A simulation program for the Firefinder radar. SPIE Defense and Security Symposium (DSS) 2008, Mar 16-20, 2008: Orlando, Florida, USA


Eric P. Lam, An Improved Image Scene Registration Using Wavelets. SPIE Defense and Security Symposium (DSS) 2008, Mar 16-20, 2008: Orlando, Florida, USA


Eric P. Lam, A structure-based image similarity measure using homogeneity regions. SPIE Defense and Security Symposium (DSS) 2008, Mar 16-20, 2008: Orlando, Florida, USA


Eric P. Lam, Texture Classification Using Wavelet Decomposition. IEEE Systems of Systems Engineering (SOSE) 2008, June 2-4, 2008: Monterey, CA, USA.


Eric P. Lam, Using Wavelet Analysis for Image Scene Registration. IEEE Systems of Systems Engineering (SOSE) 2008, June 2-4, 2008: Monterey, CA, USA.


Eric P. Lam, An improved image scene registration with wavelet preprocessing. SPIE Symposium on Optical Engineering + Applications 2008, Aug 10-14, 2008: San Diego, CA, USA.


Eric P. Lam, Using wavelets for edge directed image interpolation. SPIE Symposium on Optical Engineering + Applications 2008, Aug 10-14, 2008: San Diego, CA, USA.


Eric P. Lam, A sharpness metric implementation for image processing applications with feedback. SPIE Symposium on Optical Engineering + Applications 2008, Aug 10-14, 2008: San Diego, CA, USA.


Eric P. Lam and Patrick E. Mantey, Acoustic Signature Recognition with Wavelet Analysis.  IASTED Signal and Image Processing 2008 (SIP08), August 18-20, 2008: Kailua-Kona, Hawaii, USA. 


Eric P. Lam, “An image similarity metric based on quadtree homogeneity analysis”.  SPIE Electronic Imaging 2009, January 18-22, 2009: San Jose, CA, USA.


Eric P. Lam, “A structure-based image similarity measure using homogeneity regions”.  SPIE DSS 2009, April 12-16, 2009: Orlando, FL, USA.


Eric P. Lam and H. Walker Birrell, “A simulation program for the Firefinder weapon locating radar”.  SPIE DSS 2009, April 12-16, 2009: Orlando, FL, USA. 


Eric P. Lam ,H. Walker Birrell and Julianna Magallon, “System performance prediction of Firefinder radar “.  IEEE International Systems Conference, April 5-8, 2010: San Diego, CA, USA. 


Eric P. Lam, H. Walker Birrell and Julianna Magallon, “Performance prediction of Firefinder radar using high fidelity simulation.  IEEE Radar 2010, May 10-14, 2010: Washington D.C, USA.


Erin L. Kashiwada and Eric P. Lam, “The Use of FEKO in Providing High Fidelity Radar Simulation”,   ACES 2011, March 27-31, 2011: Williamsburg, VA, USA.


Eric P. Lam, “Use of Model-Based Design for Propulsion Simulation”, AIAA Space Forum, September 12-14, 2017: Orlando, FL, USA.




Image Processing System with Horizontal Line Registration for Improved Imaging with Scene Motion (US Patent Number 7,697,073)


System and Method for Image Registration Based on Variable Region of Interest (US Patent Number 8,160,364)


Integrating Image Frames (US Patent Number 8,374,453)



Available upon request