Gregory La Blanc

Lecturer in Finance, Strategy, & Law
Haas Finance Group
Haas Economic Analysis & Policy Group
Director of Data Science Initiative, IBI

At Haas, Greg LaBlanc teaches primarily in the areas of finance and strategy in the MBA and MFE programs and in Executive Education. LaBlanc has also worked in competitive intelligence and litigation consulting and has advised consulting teams in finance, marketing, and strategy. His research interests lie at the intersection of law, finance, and psychology, in the area of business strategy and risk management. LaBlanc is the recipient of teaching awards including the Earl F. Cheit Award for Outstanding Teaching, 2009; and the Haas EWMBA Graduate Instructor of the year, 2004-2005.

LaBlanc received a B.A. (History, Politics, Philosophy, and Economics) and a B.S. Economics (Business Administration) from the University of Pennsylvania, where he continued his education as a University Scholar and graduate fellow, studying in the schools of Arts and Sciences, Business, and Law. He later pursued a J.D. at the George Mason University and an L.L.M at Berkeley’s Boalt Hall. LaBlanc has taught undergraduate and graduate courses in all areas of business. Prior to arriving at the Haas School in 2005, LaBlanc taught at Wharton, Duke, and the University of Virginia.

Dean Abbott

      Dean Abbott Co-Founder & Chief Data Scientist at SmarterHQ   Applying data mining, data preparation, and data visualization methods to business and research problems since 1987. Data mining course instructor for wide variety of audiences,...

John Elder

      John Elder Founder, Elder Research, Inc.   Dr. John Elder founded and heads the US's most experienced data science consulting team, with offices in Charlottesville, Virginia, Washington DC, Baltimore MD, and Raleigh, NC....

Michael Housman

      Michael Housman Chief Scientific Officer, RapportBoost.ai   Human beings are poor decision makers. The field of behavioral economics has documented many cognitive biases - for example, over-confidence bias, loss aversion, outcome bias, hot...