Faculty & Programs

As a kid growing up in Amman, Jordan, Karmel Shehadeh knew she wanted to one day be a professor and a researcher. Today, she is both. And at the end of her faculty profile, she includes an unusual line. It’s not a sentiment you typically come across in such writeups, but it’s targeted toward a special group of students. In this episode, you’ll find out why she makes a point of including that sentence not only in her profile, but in the acknowledgement section of her research papers.

Rick Blum, the Robert W. Wieseman Professor of Electrical and Computer Engineering at Lehigh University, seeks to bring efficiency to distributed learning techniques emerging as crucial to modern artificial intelligence (AI) and machine learning (ML).

The United States has the capacity to generate 7200 terawatt-hours per year from offshore wind. “That’s twice the total electricity use in the U.S. in 2020,” says Muhannad Suleiman, a professor of civil and environmental engineering (CEE) who specializes in geotechnical engineering. “But right now, the U.S. produces only approximately 40 megawatts, which is the equivalent of about 7 wind turbines.”

In March 2022, MechE Prof.

Dan M. Frangopol, Lehigh’s inaugural Fazlur R. Khan Endowed Chair of Structural Engineering and Architecture, has been ranked 95th in the world and 45th nationally by Research.com in a list of leading scientists in the area of engineering and technology.

Arup K. SenGupta’s wide-ranging contributions to water science and technology and expanding access to safe drinking water will be recognized next week at the Spring 2022 meeting of the American Chemical Society (ACS) through a three-day symposium on “Ion Exchange, Sustainable Separations, & Humanitarian Engineering.” 

In machine learning, “optimization algorithms are becoming more and more important, for two reasons,” says Sihong Xie, an assistant professor of computer science and engineering. “One is that, as the data sets become larger and larger, you cannot process all the data at the same time; and the second reason is that we can formulate an optimization problem that will analyze why the machine learning algorithm makes a particular decision.”

Lehigh Engineering researchers are invested now in making the ML smarter, faster, and more trustworthy