Alexander Pollack

Background

About Alexander Pollack

Originally from the US, I am currently living and working in Vienna, Austria as an Associate Surveillance Systems Engineer at the International Atomic Energy Agency. Working to implement advanced traditional and deep learning-based tools primarily based in computer vision for nuclear safeguards and surveillance systems. I specialize in developing machine learning algorithms, specifically computer vision-based systems for various tasks, including object detection and tracking, advanced motion detection and analysis, image segmentation, generative image and video modeling, and forensic image analysis and verification. With experience in both the public and private sectors, I've worked to build out MLOps pipelines deployed on local systems, on the edge, and with various cloud infrastructures. Some of my additional have background experience in biometrics, image processing and analysis, natural language processing, and advanced numerical systems, all in various languages including but not limited to Python, C/C++, MATLAB, CUDA, and more. I pride myself having a strong background in machine learning and computer vision built on an extensive knowledge of advanced statistical and numerical analysis. From my years of experience in the world of computer vision, I am not only fully capable of capitalizing on various SOTA tools as they constantly change, but also have a wealth of deep knowledge of deep learning that allows me to developing custom models, create specialized algorithms to better utilize these models, and to curate new methods of evaluation that allow for enhanced understanding of deployed models in addition to the standard metrics that are common practice in the realm of ML. Previously a Computer Vision Engineer II at SimpliSafe focused on responsible computer vision and machine learning systems, video analytics, and firmware development. As a part of the camera firmware and AI research and development team, I was a part of publishing two patents, both focused on advanced methods for hybrid motion detection enhanced object detection inference systems. New York University Courant Institute alumnus with a MS in scientific computing, with specializations in high-performance machine learning and numerical optimization. Dual BS alumnus in Mathematics and Chemistry from Florida State University with a focus in computational linear algebra, numerical modeling and optimization, statistical mechanics, and physical chemistry.