About

Andeep Toor is an experienced researcher and engineer with over 12 years of experience in the fields of machine learning, computer vision, pattern recognition, and natural language processing. He is currently working as an ML Software Engineer at Google, where he specializes in computer vision, machine learning, and natural language processing. Andeep has worked with various technologies and programming languages, including Matlab, Python, Keras, TensorFlow, Caffe, and OpenCV. He has experience in test-driven development, agile development/methodology, continuous integration, and paired programming. In his previous role as a Researcher/Software Engineer at IBM, Andeep researched and implemented novel methods for document deduplication, experimented with novel extensions of existing deep learning algorithms, and researched, created, and compared several deep learning models to classify the degree of causality in a health-related document. He also improved text-chatbot intent classification, researched scalable methods for text-entailment/text-similarity, and designed and implemented machine learning models to extract information from electronic health records. As an Artificial Intelligence Software Engineer at SRC, Andeep was responsible for the design and implementation of an expert system for examining different courses of action for an intelligent AI agent. He also researched novel computational argumentation and logic programming techniques. Andeep holds a Ph.D. in Computer Science from George Mason University, where he specialized in artificial intelligence, and an M.S. in Computer Science/Artificial Intelligence from the same university. He also holds a B.S. in Information Systems from Virginia Tech - Pamplin College of Business. Andeep's technical skills include ML, software engineering, Python, NLP, computer vision, Keras, research science, deep learning, CNN, TensorFlow, CI/CD, supervised learning, test, integration, OpenCV, Scikit, and AI. He is a skilled communicator and has experience teaching machine learning, NLP, and computer vision concepts to junior researchers to improve team understanding and collaboration.