Verified Expert in Engineering
Machine Learning Developer
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.
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.
Principal Software Development Engineer, Artificial Intelligence
- 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.
Senior Machine Learning Engineer
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.
Senior Data Scientist
- 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.
Senior Research Scientist I
- 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.
Neural Network and Bioinformatic designs for Predicting HIV-1 Protease Inhibitor Resistance
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.
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
TensorFlow, OpenCV, Keras, Scikit-learn, MLlib, PyTorch
PyCharm, Git, Trello, MATLAB
MacOS, Unix, Amazon Web Services (AWS), Amazon EC2, Linux, AWS Cloud Computing Services
Spark, Flask, RStudio Shiny
Amazon S3 (AWS S3), JSON
Ph.D. in Cognitive and Neural Systems
Boston University - Boston, MA, USA
Bachelor's Degree in Physics and Mathematics
University of Michigan - Ann Arbor, MI, USA