Matthew Woods, Developer in San Jose, CA, United States
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Matthew Woods

Verified Expert  in Engineering

Machine Learning Developer

Location
San Jose, CA, United States
Toptal Member Since
December 21, 2020

For the past 12 years, Matthew has been creating applied machine learning and data-driven engineering projects in multiple industrial sectors, including agriculture, biotechnology, cybersecurity, and automotive. He is passionate about developing technologies that exploit his knowledge and experience with machine learning.

Portfolio

Traptic
Computer Vision, Deep Learning, Python, Machine Learning, Algorithms...
SAIC Innovation Center
Amazon Web Services (AWS), OpenCV, TensorFlow, Python, Computer Vision, PyTorch...
Venafi
MLlib, Linux, Unix, Amazon EC2, Amazon S3 (AWS S3), RStudio Shiny, R, Flask...

Experience

Availability

Full-time

Preferred Environment

Git, Python, Artificial Intelligence (AI), Linux, AWS Cloud Computing Services

The most amazing...

...thing I've developed is a machine learning software that produced the 1st place winning models in the MAQC competition.

Work Experience

Principal Software Development Engineer, Artificial Intelligence

2021 - 2021
Traptic
  • Led the development of the robot's visual system software using deep learning and computer vision, including coding in Python and Bash for training, tuning, and deploying to the production of customized convolutional neural network architectures.
  • Contributed to the architectural modifications and custom loss functions for the neural networks that allowed the inference of multiple targets from images with semi-supervised training.
  • Championed the delivery of a mathematical model of harvest yield that allowed tuning aspects of the visual and robotics systems to maximize the robot's strawberry picking rate.
Technologies: Computer Vision, Deep Learning, Python, Machine Learning, Algorithms, Artificial Intelligence (AI), Convolutional Neural Networks, Linux, Amazon EC2, AWS Cloud Computing Services, Amazon S3 (AWS S3), Sensor Data, Keras, TensorFlow

Senior Machine Learning Engineer

2017 - 2019
SAIC Innovation Center
  • Developed a driver monitoring system fusing video and biometric streams.
  • Built a system to predict a driver's intended destination.
  • Developed a system to anticipate drivers' environmental control preferences.
Technologies: Amazon Web Services (AWS), OpenCV, TensorFlow, Python, Computer Vision, PyTorch, Deep Learning, Algorithms, JSON, Artificial Intelligence (AI), Convolutional Neural Networks, Mathematics, Linux, Amazon EC2, AWS Cloud Computing Services, Amazon S3 (AWS S3), Scikit-learn, Sensor Data, Signal Processing, Time Series, Keras

Senior Data Scientist

2015 - 2017
Venafi
  • Developed an anomaly detection system for PKI certificates using Spark and Python.
  • Developed software to organize customers' internal PKI certificates into functionally meaningful groups with hierarchical clustering and a customized domain name similarity metric. Built a stand-alone REST API for this back end using Flask.
  • Developed a system to assign a score to certificates on the basis of revocation likelihood as estimated with machine learning.
Technologies: MLlib, Linux, Unix, Amazon EC2, Amazon S3 (AWS S3), RStudio Shiny, R, Flask, Scikit-learn, Spark, Python, Deep Learning, Algorithms, JSON, Artificial Intelligence (AI), Convolutional Neural Networks, Mathematics, AWS Cloud Computing Services, Signal Processing, Time Series, Keras, TensorFlow

Senior Research Scientist I

2008 - 2010
Pfizer
  • Developed a machine learning system for the prediction of antibody thermal and acidic stability on the basis of primary sequence with the aim of identifying stability improving inducible mutations.
  • Identified common biological activity among a large panel of compounds with unsupervised learning and computer vision applied to digital microscopy.
  • Performed text mining and natural language processing of a large corpus of miRNA-related publications.
Technologies: MATLAB, R, Statistics, Machine Learning, Algorithms, Artificial Intelligence (AI), Science, Mathematics, Linux, Amazon EC2, AWS Cloud Computing Services, Amazon S3 (AWS S3), Signal Processing, Time Series, Differential Equations

Neural Network and Bioinformatic designs for Predicting HIV-1 Protease Inhibitor Resistance

Doctoral work.

I created a new machine learning method for online-learning of continuous-valued multi-dimensional to multi-dimensional maps, a novel feature selection method, and a general-purpose protein-encoding scheme for ML applications. These methods are used to personalize the treatment of HIV-positive patients.

Languages

Python, R

Other

Machine Learning, Science, Statistics, Simulations, Supervised Learning, Unsupervised Learning, Time Series, Signal Processing, Mathematics, Algorithms, Modeling, Artificial Intelligence (AI), Differential Equations, Software Development, Sensor Fusion, Sensor Data, Deep Learning, Convolutional Neural Networks, Computer Vision

Libraries/APIs

TensorFlow, OpenCV, Keras, Scikit-learn, MLlib, PyTorch

Tools

PyCharm, Git, Trello, MATLAB

Platforms

MacOS, Unix, Amazon Web Services (AWS), Amazon EC2, Linux, AWS Cloud Computing Services

Frameworks

Spark, Flask, RStudio Shiny

Storage

Amazon S3 (AWS S3), JSON

2001 - 2007

Ph.D. in Cognitive and Neural Systems

Boston University - Boston, MA, USA

1992 - 1996

Bachelor's Degree in Physics and Mathematics

University of Michigan - Ann Arbor, MI, USA