Hongwu Wang Assistant Professor
Dr. Wang is currently a Research Assistant Professor in the Department of Rehabilitation Science and Technology (RST) at the University of Pittsburgh. He received his Bachelor and Master’s Degree in Biomedical Engineering from Xi'an Jiaotong Univeristy, Xi'an, China, in 2003 and 2005 respectively, with a concentration in medical imaging and image processing. Dr. Wang defended his dissertation at RST on “Development and Evaluation of an Advanced Real-Time Electrical Powered Wheelchair Controller” in December 2011. Dr. Wang developed a series of advanced control algorithms such as anti-rollover control and traction control for electric-powered wheelchairs during his PhD pursuit. He also published several papers in prestigious journals and conference proceedings for his doctoral work and won the best student paper awards in both 2008 and 2009 at the Annual Conference of Rehabilitation Engineering and Assistive Technology Society of North America. Dr. Wang started his post-doctoral work at the Human Engineering Research Laboratories, University of Pittsburgh. He received the Craig Neilsen Foundation Postdoctoral Fellowship award for his proposal on the development of a reliable and valid clinical assessment tool for assistive robotic manipulator. He was also part of a project funded by the Telemedicine and Advanced Technology Research Center focused on terrain dependent mobile platform using laser line stripper and cameras. Dr. Wang is leading the development of a mobile platform for powered mobility devices, which is is a hybrid system powered by both batteries and pneumatics. He is also actively involved with the development and evaluation of a wheelchair mounted robotic transfer device, design and development of a sensorized anthropomorphic model to assess commercial wheelchair cushions. Dr. Wang has authored and co-authored 20 journal papers and more than 30 conference papers. Dr. Wang has 2 issued patents, 2 pending patents and 3 invention disclosures. His research interests are rehabilitation engineering and assistive technology, in particular through the development of mobility and manipulation assistive robotics and innovative evidence-based outcome measurement tools for technologies application at complex interaction of personal and contextual factors that impact functional performance and heath service delivery.