Mohak Shah is an analytics leader with over 15 years of experience in organization formation, strategy, and end-to-end data science engagements. He has led analytics and IoT engagements in domains including automotive, aviation, energy, and healthcare, managing diverse teams from research, software, and businesses. As a scientist, Mohak has developed novel machine learning and statistical algorithms with high-impact business applications. He is the author of "Evaluating Learning Algorithms: A Classification Perspective" (Cambridge), and has published more than 45 research articles in top conferences and journals in the analytics space, and patented technologies. He was the general chair of the ACM SIGKDD 2016 conference and holds an adjunct position with the University of Illinois at Chicago. He regularly participates in scientific, business, and investment communities as expert speaker, advisor, and consultant.