Applied mathematician and computer vision researcher with experience in deep learning, convolutional neural networks, machine learning, and developing and implementing advanced algorithms. I currently work on problems related to multi-label image classification and feature extraction. Highly motivated, detailed, and resourceful.Areas of Expertise:Deep Learning, Computer Vision, Machine Learning, Numerical Analysis of PDEs, Inverse Problems, Imaging/Image Processing, OptimizationProgramming: Python, MXNet, PyTorch, Numpy, Scipy, Scikit-Learn, Pandas, Boto3, Docker, C++, Cython, Matlab, MPI, OpenMP, Keras, TensorFlowAWS Cloud Infrastructure: AWS Batch, EC2, Lambda, SageMaker, Rekognition, DynamoDB, Redshift, S3, Elastic Container RepositoryMachine Learning: Nonlinear/Linear Optimization Algorithms, L1/L2/TV Regularized Least Squares, ADMM, Logistic Regression, PCA, Clustering, Neural NetworksStatistics: Hidden Markov Monte Carlos, Expectation Maximization AlgorithmMy previous academic research deals with computational inverse problems related to the recovery of unknown parameter functions inside a medium from boundary measurements. The areas of medical and seismic imaging are a driving force behind the research in this area, among other fields.As such, I am well-versed in the implementation of numerical algorithms for solving PDEs, advanced linear algebra, application of optimization schemes, design of computational experiments, and scientific visualization.