Tom serves as a Partner and the Chief Data Officer at Jackson Lewis. In this capacity, he provides guidance to clients in eDiscovery, data science, digital legal transformation, information governance and data privacy. He is considered one of the leading experts in the legal industry in artificial intelligence, machine learning and data analytics. An experienced litigator, he also frequently serves as a consulting and testifying expert in some of the largest litigation, regulatory and enforcement actions in the nation. Tom previously served as Chief, Data Science, Analysis & Investigation at Paul Hastings where he founded and led a team of data scientists, consultants and project managers in developing and implementing advanced AI and machine learning solutions in litigation, investigations, contract analysis and compliance. This widely recognized group and its proprietary AI technology was acquired by the third largest private equity company in the world. At Paul Hastings, Tom also served in the Office of General Counsel where he focused on data privacy and security, compliance and related solution design. He was a member of the firm’s Data Security and Privacy practice group where he advised global clients and the firm on international data privacy and compliance matters. Previously, in his role as Special Counsel at Sullivan & Cromwell, Tom founded and led the eDiscovery and Compliance team, the first such group of its kind at a premier global law firm. As an industry innovator and entrepreneur, Tom has built industry-leading companies, teams and practice groups and created and implemented new service and product offerings; he led a multi-country R&D effort that designed and brought to market one of the industry’s first supervised machine learning (predictive coding) legal review solutions. Tom was the founding member and senior executive in charge of the eDiscovery division of the largest business process outsourcing company in Asia. This company was an innovator in the area of complex analytical and conceptual data processing as well as predictive and iterative document review technology. Tom’s academic white papers on data analytics and machine learning are cited numerous times throughout the landmark 2012 Rand study, “Where the Money Goes: Understanding Litigant Expenditures for Producing Electronic Discovery.”