I am an assistant professor in both the Graduate Program in Operations Research and Industrial Engineering (ORIE) and the Department of Petroleum and Geosystems Engineering (PGE) at The University of Texas at Austin. The ORIE program is an graduate program within the Department of Mechanical Engineering. In addition to these appointments, I am a fellow in the Center for International Energy and Environmental Policy (CIEEP) and the Center for Petroleum Asset Risk Management (CPARM).

My research has been featured in the New York Times, the Wall Street Journal, the Financial Times, Bloomberg, National Public Radio, and in dozens of local and regional media sources. In addition, this work is featured in the new documentary Cool It. This work was part of the Copenhagen Consensus on Climate Project. You can learn more here.

My research and teaching interests are broadly focused in the area of decision making under uncertainty. My primary application area is in the energy arena. My research has been funded by the NSF, DOE, NETL, and private companies. In 2009 I was fortunate enough to be awarded an NSF CAREER grant.

I hold MS and PhD degrees in Engineering-Economic Systems from Stanford University and a BS in Mechanical Engineering with a minor in Economics from New Mexico State University. Before joining the UT faculty, I was an assistant professor at Texas A&M University. Before that, I was a senior engagement manager and co-director of client education for Strategic Decisions Group.

What is decision analysis? Watch this video!

Watch this Stanford/UT webinar featuring my presentation of decision quality.

Do you watch The Weather Channel and wonder how accurate their precipitation forecasts are? This paper summarizes my study of over 13 million precipitation forecasts. You can use the tables I include below to convert The Weather Channel's precipitation forecasts into observed frequencies. To use the tables you simply look up the forecasted probability of precipitation (PoP) given by The Weather Channel on the horizontal axis and then read down the rows to adjust for the length of forecast. For example, a 5-day lead-time is a forecast for 5 days from today.

Central (KY, IL, IN, MO, OH, TN, and WV): Table
East North Central (IA, MI, MN, and WI): Table
Northeast (CT, DE, ME, MD, MA, NH, NJ, and NY): Table
South (AK, LA, KS, MS, OK, and TX): Table
Southeast (AL, FL, GA, NC, SC, and VA): Table
Southwest (AZ, CO, NM, and UT): Table
West (CA and NV): Table
West North Central (MT, NE, ND, SD, and WY): Table

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