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Lisa Chang, Praxis Engineering
Lisa Chang is a Data Scientist and Software Engineer at Praxis Engineering, where she teaches a Data Science course and searches for hard problems where Data Science and Machine Learning techniques may be useful. Since 2005, she has been designing and implementing solutions to Natural Language, recommender, and classification problems. Lisa graduated with a BS in Chemical Engineering from Cornell University and a MS in Computer Science from Rice University. She has been known to randomly and loudly proclaim her love of Jupyter Notebooks in conversation.
MEET THE PANEL
David Etter is a Principal Machine Learning Scientist with Etter Solutions. He has over 24 years of experience researching and developing large scale solutions for government and industry. His research interests include Computer Vision, Natural Language Processing (NLP), and Large Scale Retrieval. David graduated from George Mason University in 2015, with a PhD in Computer Science, where his dissertation focused on multimedia search and ranking. He is currently collaborating with researchers at the Johns Hopkins University Human Language Technology Center of Excellence (JHU HLTCOE) to develop solutions for the problem of optical character recognition (OCR) in unconstrained video and image.
Marc Mason works for Tetra Concepts as a Natural Language Engineer and has been working in the intelligence community for 30 years. He has focused on Artificial Intelligence, Knowledge Representation and Natural Language Processing with a desire to see question answering come to the place it has now with digital assistants as well as applying these techniques to Big Data problems. He has designed and implemented numerous mission-critical systems in his time in the Intelligence Community. He has a Masters degree from Johns Hopkins University with a concentration in Artificial Intelligence. He lives with his wife and 2 sons in Maryland.
Donald Miner is founder of the data science consulting firm Miner & Kasch and specializes in large-scale data analysis and applying machine learning to real-world problems. Donald is author of the O’Reilly book "MapReduce Design Patterns", and the O’Reilly reports “Hadoop with Python” and “What You Need To Know About Hadoop". He has architected and implemented dozens of mission-critical and large-scale data analysis systems within the U.S. Government and Fortune 500 companies. He has applied machine learning techniques to analyze data across several verticals, including financial, retail, telecommunications, healthcare, government intelligence, and entertainment. His PhD is from the University of Maryland, Baltimore County, where he focused on artificial intelligence and multi-agent systems. He lives in Maryland with his wife and three young sons.