Bashir Morshed

Dr. Bashir I. Morshed is an Associate Professor at the Department of Computer Science (CS), Texas Tech University, Lubbock TX USA. Previously, he was an Associate Professor at Electrical and Computer Engineering (EECE), University of Memphis, Memphis TN USA. He has received the B.Sc. degree in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET) in 2001. Afterwards, he completed the M.A.Sc. degree in Electrical and Computer Engineering from University of Windsor, Windsor ON Canada, in 2004 and earned the Ph.D. degree in Electrical and Computer Engineering from Electronics department of Carleton University, Ottawa ON Canada, in 2010. He was a post-doctoral fellow at Medical Devices Innovation Institute, University of Ottawa, Ottawa ON Canada, prior to his joining EECE department at the University of Memphis in 2011.

Dr. Morshed is a recipient of the prestigious Canadian Commonwealth Fellowship (2002-2004), Indira Gandhi Memorial Fellowship (2004 and 2006), Ontario Graduate Scholarship (2007), and Ontario Graduate Scholarship in Science and Technology (2008). He also received 2018 MHTI Scholar award by NIH mHealth Summer Training Institute at UCLA. He was awarded Faudree Professorship (2019-2020) and Faculty Research Award of Herff College of Engineering (2020) at the University of Memphis.

Dr. Morshed, a Senior Member of IEEE, has published 30+ journal articles and 100+ referred conference papers and posters, one of which has received the best paper award in an international conference (IEEE EIT 2018). He has been issued 2 patents (USPTO), while 3 patent applications are pending. He has received multiple federal research grants from National Science Foundation (NSF) as a Principal Investigator (PI). He also received several other extramural and internals funds as a PI, CoPI, CoI, or Senior Personnel. His research interest focuses on cyber-physical systems (CPS) development using inkjet-printed body-worn and wearable flexible electronic biomedical devices and sensors for real-life health monitoring towards smart and connected community. Furthermore, he explores real-time artificially intelligent algorithms implemented with smartphone enabled edge-computing for future generation mobile health (mHealth).