Download word - Andrew L. Diamond

Andrew L. Diamond
4170 Pilon Point
San Diego, CA 92130
858-509-3115
[email protected]
www.andydiamond.com
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Algorithm Development & Analysis
Machine Learning
 Machine Vision
Analysis, Quantification, Modeling
 Automation of R&D, products
PROFESSIONAL EXPERIENCE
Rapiscan Labs, Sunnyvale, CA
Staff Engineer
2012-2013
Machine Learning– Classifier design and analysis for multiple projects, mainly, using own implementation
of Boosted Stochastic Gradient Trees providing a robust classification and automatic quantification of feature
importance. Implementation includes a module that translates trained classifier into stand alone C code.
Developed classifier based technique to analyze whether the holdout and training data were compatible (i.e.
drawn from the same distribution as might not be the case depending upon changes in data collection) .
Analysis – Built automated systems to analyze algorithm performance to create error budgets to determine
ranked causes of errors. Used bootstrapping of the classifiers to provide confidence level ROC curves to
show robustness of classification for different threat types. Performed further analysis to determine data and
algorithm causes of misclassification. Ported customer defined grading from Excel to Matlab (and
incorporated such in to a customer error model for the classification)
Image Processing and tools – Segmentation and registration of luggage for factory acceptance testing
GUI/tool. Created GUIs for ground truth annotation of volumes and 2d images for multiple projects
including multiple visualization and analysis modes (e.g. edge enhancement, wavelet decomposition,
dynamic histogram equalization). Created topological hole-filling algorithm for volume annotation (filling
convex hull after basic morphological operations).
Profiled and recoded portions of a 3rd party suite of Matlab image processing detection algorithms by 40%.
Pacific Biosciences, Menlo Park, CA
Senior Staff Algorithm
Engineer
2008-2011
Promotions: Staff , Senior Staff Engineer
4 “Rock Star” awards
Created algorithms and software to process and analyze continuous and discrete data including images, prebase calling 1-d signals, and base called data.
Automated Chip Quality Inspection Pipeline – Conceived, designed, and implemented all machine
learning and image processing modules, including a gridder to register the image to the chip layout spec, and
pipeline process as well as various analytic modules. In addition to facilitating chip quality improvement, it
saved millions of dollars by increased yield and decreased manual inspection labor. Used chip feature
statistics to predict read length, dead ZMWs, and the likeliness of the instrument to be able to focus and align
the chips. Developed a generic framework/API to create feature vectors, suitable for machine learning, from
the 1500+ chip quality metrics computed by the image processing modules. Developed an easily extensible
generic model-running application to run chip quality analytic models, including the machine learning
grading and other models as developed by myself and other team members. Implemented custom Boosted
Regression Tree module that allowed the quantified ranking of predictive features, custom error functions,
etc.
Automated SEM image inspection pipeline – Conceived, designed, and implemented the continuously
operational SEM image inspection pipeline to obtain CD and other metrics. Easily configurable and
extensible system downloaded multiple SEM image types from multiple image vendors from respective FTP
sites and processed them outputting various results to a DB and disk.
Techniques employed included deformable templates operating on multi-resolution gradients, morphological
processing, integro-differential operators, and other various signal/image processing techniques.
Template optimization – Optimized the design of a sequence template that would be optimally robust to
noisy data. This problem has lots of local minima and so a global optimization method is required. A genetic
algorithm was employed. The cost function employed simulations of reads with noise aligned against
multiple points of the template and for various lengths of the template to minimize for a template that had the
least ambiguity, at various scales, as well as minimal repeats.
Various other assorted tools and algorithms
 SMRTFire – A GUI tool for investigating the various alignment results for movies on a per movie
and per trace basis with respect to hundreds of signal metrics.
 PA – Perturbation Analysis - An efficient implementation of a stochastic alignment sensitivity
analysis algorithm. This showed areas of the template that were particularly sensitive to minor
changes as well as the most likely alignment.
 A drift tracker to measure the drift of the chip in the machine through time. Helped track down the
source of significant vibration.
 Invented dynamic programming algorithm to predict ideal alignment areas of a read. Also used
HMM and CRF.
 Many others.
EnVision Systems, LLC, San Diego, CA
Consultant/Owner
1995-2008
2013 -
Image Restoration – Design and implemented algorithms and analysis for color image restoration on a
novel lens system including deconvolution, mitigation of chromatic and geometric distortion, and other
issues. Algorithms required to adjust for on-the-fly variables. Analysis for amounts and effects of noise,
focusing issues, lighting conditions, etc.
Stem Cell Colony Detection – Used Discrete Wavelet Frames as a basis to discriminate the different
textures of differentiated and un-differentiated colonies of simulated stem cells. Classification
methodologies used included Decision Trees, Support Vector Machines, and Neural Networks on energy
statistics. (See website, “Texture Classification”.) Proposal included the use of gray scale morphological
image processing methods to delineate colonies from resulting pixel classification images followed by
quantification.
Gene Expression Microarrays image gridding & analysis - Designed, implemented, and helped integrate
several Gene Expression Microarray automatic gridding and quantification algorithms to yield grids of
coordinates and measurements of “features” as presented in multi-spectral images. Helped biologists and
other scientists with statistical analysis of results and R&D.
Microarrays included non-rectangular and rectangular types; some with random curvature. Gridding systems
were composed of multiple novel redundant automatic fail-over gridding algorithms for maximum
robustness. Gridding algorithms overcame grid irregularity, signal issues, etc. Fielded product had 0% error
rate. Gridder also included a novel Neural Network centroid refinement algorithm and a bi-spectral Neural
Network fiducial detector in the context of multi-spectral registration.
Responsibilities also included developing R&D algorithms, tools, and analysis for images that did not meet
product spec. and so required the use of a novel Minimum Spanning Tree gridding algorithm. These
automated algorithms were instrumental in increasing the rate of product development.
Electrophoretic Image Gel Lane Tracking - Designed, implemented, an Electrophoretic Gel Lane
Tracking software module for both Sequence and Fragment analysis on multi-spectral imagery. The tracker
employed Simulated Annealing on splines to model the lanes and a Neural Network algorithm to detect
bands. It achieved 97% accuracy on an acknowledged intractable problem thereby saving hours of manual
processing. The system received the Bioinformatics 2001 & 2002 Readers’ Choice Award Winner:
Sequencing Analysis Software.
Textile Inspection – Designed and implemented a textile inspection software module. The system inspected
fabric for detects as it moved on a roll. The system communicated the position of the defects so that the
“cutter” would know where the defects were located and appropriate action taken.
Database Mining/Analysis – Developed software and methods to process and analyze databases and internet
data related to identity verification and theft using freeware tools R and Perl on Windows and Linux. IRC
data logs were automatically processed to obtain identification information from posted stolen credit card
data. Created a technique which increased the search speed of the 400 Million record criminal database 50
fold. Statistical software was developed to ensure that the periodic updates of online databases were valid.
Evaluated the feasibility of the use of these tools for use on Windows and Linux for in-house and fielded
applications. Evaluated the feasibility of various data sets for use in subsequent pattern recognition
algorithms.
SNP genotyping - Helped design, implement and field a Maximum Likelihood SNP clustering algorithm that
yielded quantitative performance statistics and confidence values for each SNP as well as clusters. R&D
analysis pattern recognition algorithms included EM, Neural Networks, Bayesian Automatic Relevance
Determination, and ADABoost to help optimally detect, quantify, and parameterize signal, assist discriminate
analysis, and grade classification performance.
Blood Glucose Estimation - Created R&D GUI application to automatically determine and validate infrared
predictors of blood glucose levels. Included the creation and design of a modular GUI and algorithms that
facilitated the creation of arbitrary types of models, arbitrary features, automatic feature search, validation,
and statistical quantification.
Food Inspection - Designed a Windows hosted X-Ray image system for the inspection of potatoes. Tasks
included development of a proprietary neural network and image processing libraries optimized to meet real
time requirements.
Systems Engineering consulting - Helped reform the algorithm and testing departments so as to create a
Systems Engineering approach to algorithm and platform development so as to maximize product efficacy
while minimizing risk. This includes designing a “pipeline” so platform scientists/engineers could drop off
their large data sets for processing thereby yielding statistically significant results to be used for the
improvement of algorithm and platform developers alike. Also an “Automatic Test Machine” (ATM)
methodology for automating the test and annotation process required for quick turnaround. This facilitated
the creation of an error budget that quantified and disambiguated the sources of system error.
EWB, Inc, Carlsbad, CA
Software Manager
1994-1995
CD-Rom Compression – Managed 2 software developers in the creation of the front end of a Windows
software system to facilitate the creation of compressed CDs (CAPACD).
Developed an easily extensible explicitly loadable C++ DLLs for many CDR Writer vendor/OEM families to
facilitate the creation of compressed CD-Rs. Method allowed for multiple writers and for the addition of
new CD-R writers with minimal coding by virtue of previous CDR writer family C++ inheritance.
Hecht-Nielson Neurocomputer (HNC), Inc., San
Diego, CA
Staff Scientist
1989 - 1994
QualityPlus 3000 generic color image food inspection - Lead scientist/engineer responsible for the design
and implementation of QualityPlus 3000, a Microsoft Windows hosted system for industrial quality
inspection. The system analyzed color video images for quality control using image processing and neural
network technology. Highlighted in Fortune and various trade magazines. Worked with customers to
generate system requirements and specifications. Designed all software including image and neural network
pattern recognition algorithms, GUI. Participated in the implementation of the Windows and other system
software and implemented all image processing and neural network software.
Japanese Apple Inspection - Lead scientist/engineer on a real-time color video apple inspection system
created as a joint effort between HNC and Sumitomo Heavy Industries of Japan (SHI). Responsibilities
included working closely with SHI engineers in Japan and USA to create specifications, requirements, and
testing procedures. Designed and implemented all algorithms and software including PC interface, NTSC
frame grabber interface, image processing, neural networks and data transformation techniques. Successful
completion of the project formed the basis of the creation of QualityPlus 3000 systems as described above.
Loan and Credit Card Scoring – Neural network systems for predicting the probability of customer default.
Used databases of customer information with application information and previous outcomes to predict
future outcomes from sometimes incomplete new customer applications.
Other Industrial Image Inspection - Lead engineer of various commercial image inspection projects
including plastic bottles, dates, carrots, processed food, citrus fruit, etc.
Defense - Proposal writer, principal investigator for LADAR image SBIR contract using neural network
image analysis and understanding techniques. Worked on various other defense image processing contracts
including a multi-resolution saccadic vision algorithm.
Neural Network libraries - Developed and implemented neural network paradigm libraries and utilities.
Included the development of advanced techniques for non-linear perceptrons, radial basis functions, and
recurrent neural networks in particular as would be used for image pattern recognition.
Engineer – Artificial
Intelligence Group
General Dynamics, Electronics Division
San Diego, CA
1986 - 1989
Designed and implemented classified defense related embedded neural network image processing
applications for road finding and target acquisition on a Symbolics Lisp Machine. Neural networks included
Backpropagation, PNN, and SOM operating on Gabor Logon Jets as features.
Implemented and refined the Boundary Contour System, a sophisticated neural network model of the
mammalian pre-attentive vision system, on an Intel multi-vector processor hypercube.
Participated in the development of a traditional AI rule based heuristic intelligent map system. Developed
and implemented topology based algorithm which was the foundation of the system.
Education
UCSD Audit: 1) Statistical Learning II 2) COSMAL Graduate Seminar
UCSD Extension Classes: 1) Intro To Bioinformatics 2) Intro to Molecular Biology
M.S. Computer Science, Syracuse University 1986. GPA 4.0
B.S. Computer Science and Applied Mathematics, State University of New York at Albany 1984.
B.S Mathematics, State University of New York at Albany, 1984.
Computer Languages
Matlab, C, C++,SQL,R
Perl, Java, Lisp
Organizations
2006,2007 - Chair, IEEE San Diego Computational Intelligence Society
Association of Computing Machinery
 1989, 1990 - Co-Director Special Interest Group on Artificial Neural Systems (SIGANS), San Diego
chapter.
 1989,1990 - President, Special Interest Group on Artificial Intelligence (SIGART), San Diego chapter.
Member IEEE.
Member International Neural Network Society.
Publications
Andrew Diamond, David Holden, Electrophoretic Gel Image Tracking by the Simulated Annealing of Splines
Augmented by Local Error Estimates, Proceedings of the IASTED Int. Conf., SIP 1998. pp 638-643.
Diamond, A. & Holden, D. Implementing the Boundary Contour System on a Multi-Vector Processor iPSC/2
Hypercube. IEEE IJCNN 1989, Vol1, pp 135-143.
G.J. Hueter, and A.L. Diamond, Automated Inspection with Neural Networks, Proceedings of electronic
Imaging West ‘92, (Miller-Freemen 1992), pp 137-140.
G.J. Hueter, A. L. Diamond, c. Platt, and S.C. Quandt, Neural Network-Based Automated Food Inspection,
Proceedings of Food Processing Automation II, 1992, (ASAE:1992), p. 291.