I create Machine Learning algorithms to solve problems in computer vision, biomedical image understanding, and EHR (electronic health record) understanding, deployed locally or in the cloud (AWS). I'm always happy to enter into new domains, particularly where the data are well-structured. Deep neural networks (CNNs, RNNs, Autoencoders, etc.) are generally my tools of choice. I use PyTorch and Tensorflow/Keras for DL, and Python/PIL/OpenCV for general ML and CV. I also have extensive experience in software engineering (esp. C++) and have loved using it to create products and applications in ML, signal processing, data analysis and visualization. I also have substantial background in experimental and computational neuroscience, which provides good general conceptual tools to help attack my current research and engineering problems.

Some of my open-source software includes WaveSorter for sorting and classifying (neural) wavevforms, as well as an application for the convenient visualization of dynamical systems, DynaSys.