News

Undergraduate Emma Klinkhamer of the Chemical Engineering (ChE) Department dreamed up her ideal job and published it in the July 28 edition of Chemical & Engineering News: http://cen.acs.org/articles/92/i30/Chemistry-Students-Describe-Dream-Jobs.html. Her utopian job was included in a section called "Chemistry Students Describe Their Dream Jobs." Among other comments, she noted that “My education has taught me that the sky’s the limit when it comes to chemistry. It just takes creative thought and persistence to develop a material or mechanism. In my lab, I would strive to use the fundamentals of chemistry and cutting-edge engineering to create desirable products." Currently she works in the research laboratory of ChE faculty member Jessica Schiffman.

The University of Massachusetts Amherst Foundation has established an endowment fund to be known as the Armstrong/Siadat Endowed Professorship in Materials Science with a cash gift of $750,000 from John and Elizabeth Armstrong and a $750,000 pledge from Barry and Afsaneh Siadat. The endowed professorship will be awarded to a researcher in the area of materials science in the UMass Amherst chemical engineering department. Barry Siadat says, “The endowed professorship will attract an outstanding leader who will be a bit like a magnet, building a world-class program that will improve the quality of life.” John Armstrong says he hopes the professorship will be the center of a cluster of renowned scientists working to solve problems and create new materials.

A new report written by Eric Gonzales, a faculty member in the Civil and Environmental Engineering Department, and his colleagues looks at how to manage taxi markets by using Global Positioning System receivers. The report was released by the Mineta Transportation Institute and was covered in the media by WFSB-TV 3, TickerTech.com, and Securities Technology Monitor, among others. The report was entitled “Modeling Taxi Demand with GPS Data from Taxis and Transit.”  As Gonzales wrote,Our primary objective was to identify factors that drive taxi demand and to understand how this varies by location and time of day. The models generated by the study can help to estimate taxi demand and provide many other useful insights.”