Michael S.

Machine learning scientist/engineer with hands-on expertise in deep learning, computer vision, time series, data analysis, computational science, mathematical modeling, computer simulations, algorithm development, and software development. ML -- computer vision: segmentation, classification, object detection, e.g., ViT, R-CNN, unet, yolo ML -- time-series: recurrent neural networks, convolutional neural networks, e.g., LSTM, GRU, CNN ML -- general: classification, regression, prediction Development of end-to-end ML pipelines: pre-processing, model development, post-processing, model evaluation, hyper-parameter turning, model deployment Applications: Medical imaging and devices, biofluids, fluid dynamics, combustion, renewable energy, computational engineering. Technical/non-technical writing: Patents, proposals, white papers, peer-reviewed papers, presentations. Education: PhD -- Applied Math (Cornell), Postdoctoral Fellow -- Chemical Engineering (MIT) Programming: Python, C++, Java, Matlab Machine Learning: Keras, Pytorch, Scikit-learn, TensorFlow NLP: NLTK, OpenNLP Computer Vision: OpenCV, Pillow, Pydicom, SimpleITK Data Science: Matplotlib, Numpy, Pandas, Scipy, Seaborn CAD/CFD: Ansys, Gmsh, OpenCascade, OpenFOAM, Overture, Rhino3D Misc: Amazon/Google cloud, DICOM, Git, Jira, UNIX tools/admin