Mohak Shah is an analytics leader and a data science expert with significant experience in organization formation, strategy, and end-to-end data science engagements. He has participated in functional and strategic capacity in developing high-performing organizations in the analytics space and regularly consults senior leadership at various organizations on the topics. As a scientist, Mohak has developed novel machine learning and statistical algorithms, with high impact applications in IoT domains, healthcare, bioinformatics and neurosciences. He is co-author of “Evaluating Learning Algorithms: A Classification Perspective” (Cambridge), and has authored more than 45 articles in top conferences and journals in the analytics space. He was the general chair of ACM SIGKDD 2016 conference.