One year ago, a team of five faculty members, including Assistant Professor Benjamin D. Leibowicz from the Operations Research and Industrial Engineering (ORIE) program in the Cockrell School of Engineering, received a $3 million grant from the National Science Foundation (NSF) to establish a new NSF Research Traineeship (NRT) program at The University of Texas at Austin. NRT programs combine cutting-edge, interdisciplinary research with bold and transformative models for STEM graduate education and training. The theme of this new NRT program at UT Austin is food-energy-water systems (FEWS). Specifically, the research team will investigate how renewable energy can be leveraged to expand unconventional water sources for agriculture, and how energy-containing resources can be harvested from agricultural wastewater.

Professor Peter Stone has been named a 2018 IEEE Fellow. He is being recognized for his contributions to reinforcement learning, multiagent systems and robotics. Each year, IEEE, or the Institute of Electrical and Electronics Engineers, chooses from among nominated IEEE members from around the world for the distinction of Fellow Grade. Out of IEEE’s over 423,000 members, less than 10,000 are fellows.

Professor Jonathan Bard and PhD student Yutian Yang received the Best Application Paper Award for their article “Internal Mail Transport at Processing and Distribution Centers” published in IISE Transactions on Design and Manufacturing. The award was given out at the annual Institute of Industrial & Systems Engineering conference in Orlando, FL in May.

Four researchers in the Cockrell School of Engineering at The University of Texas at Austin have been selected by the National Science Foundation (NSF) to aid in the development and implementation of bold, new, potentially transformative models for STEM graduate education training. The National Science Foundation Research Traineeship (NRT) award will grant nearly $3 million to the university. The research will focus on reducing energy barriers for novel water supply use in Sustainable Agriculture. 

A Texas Engineer has developed a new data-driven solution scheme for two-stage decision-making problems under uncertainty. The proposed scheme is amenable to standard off-the-shelf optimization solvers and yields high quality solutions with attractive out-of-sample performance guarantees.