John Reisel

John Reisel is a Professor in the Department of Mechanical Engineering at the University of Wisconsin-Milwaukee (UWM), College of Engineering and Applied Science. His research bridges engineering education and sustainable energy systems, focusing on improving student success and developing environmentally conscious engineering solutions.

His educational background includes:

• PhD in Mechanical Engineering from Purdue University (1994)
• MS in Mechanical Engineering from Purdue University (1991)
• BME from Villanova University (1989)

Reisel's research spans Engineering Education and Energy/Environmental Systems. In education, he pioneers peer-led learning and bridge programs to boost retention. In energy, he develops neural network models for demand forecasting, solar thermal integration in biofuel production, and wastewater treatment technologies for textile dyes. His work directly impacts curriculum design and sustainable industrial practices.

His publication history reveals a strategic dual focus: approximately half address educational interventions for engineering students, while the other half tackle energy modeling and environmental applications. This interdisciplinary approach connects pedagogical innovation with real-world sustainability challenges, particularly in biofuel production and industrial wastewater treatment.

His scientific recognition includes:

• ASEE paper awards across multiple divisions (2010-2020)
• UWM's Distinguished Undergraduate Teaching Award (2005)
• CEAS Top 10 Research Expenditures ranking (2009-10)
• SAE Ralph R. Teetor Educational Award (1998)

Reisel mentors students through research-intensive educational programs and serves as UWM's Secretary of the University. His grant-funded work demonstrates significant research impact, particularly in educational intervention studies and energy modeling projects. Community engagement includes board membership with Big Brothers/Big Sisters of Milwaukee and St. Hyacinth Emergency Food Pantry.

His collaborations span environmental engineering (wastewater treatment), computer science (neural networks), and community organizations, reflecting a commitment to both academic excellence and societal impact.