Draft:Jiajie Zhang

Jiajie Zhang is an American scientist with more than 30 years of research, education, and application experience in cognitive science, health informatics, human-computer interaction, and medical decision-making. Zhang received his PhD in cognitive science from the University of California, San Diego.

Zhang is an academic leader serving as dean and professor of McWilliams School of Biomedical Informatics (MSBMI) at UTHealth Houston University of Texas Health Science Center at Houston, where he holds The Glassell Family Foundation Distinguished Chair in Informatics Excellence ; in addition, he is director of the National Center for Cognitive Informatics and Decision Making in Healthcare (NCCD) and a professor at The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences. Zhang is perhaps best known for his work associated with distributed cognition, electronic health record (EHR) usability, and medical decision-making.

Among other honors accorded Zhang over the course of his career, he is an elected fellow of the American College of Medical Informatics (FACMI), American Medical Informatics Association (FAMIA), and International Academy of Health Sciences Informatics (FIAHSI). He is a recipient of the UTHealth John P. McGovern Outstanding Teacher Award, and was honored in 2015 by the Asian Pacific American Heritage Association (APAHA) with the George H.W. Bush Award for his contributions to the United States as an Asian-American.

Zhang resides in Houston, Texas.

Background and Education
Jiajie Zhang was born in Nanjing, China. He began his undergraduate education in 1979, as a student in the Special Class for Gifted Young (now, the School of Gifted Young ) at the University of Science and Technology of China (USTC) ; there, he obtained a BS in the biological sciences (1983). Zhang came to the United States in 1986 to pursue advanced studies at the University of California, San Diego (UCSD), where he earned a PhD in cognitive science —the world's first doctorate in this area of study —in 1992. Donald A. Norman was Zhang's mentor and doctoral advisor while he attended UCSD ; his thesis was entitled, Distributed representation: The interaction between internal and external information. Edwin Hutchins, one of the pioneers of distributed cognition, was on Zhang's dissertation committee. While at UCSD in the 1980s, Zhang served as a UCSD teaching assistant at the time seminal work on neural networks was being conducted by the PDP group, when David Rumelhart, Geoffrey Hinton, and Ronald J. Williams developed the backpropagation algorithm—an important mathematical tool that improves the accuracy of predictions in data mining and machine learning—which was foundational to the emergence of the deep learning revolution in artificial intelligence that occurred during the 2010s.

After receiving a doctorate from UCSD, Zhang launched his academic career as an assistant professor of psychology at Ohio State University in 1992, where he continued until 1998, when he moved to Houston, Texas to join The University of Texas Health Science Center at Houston (UTHealth Houston) School of Biomedical Informatics (SBMI)—now, McWilliams School of Biomedical Informatics at UTHealth Houston—as an associate professor.

Zhang was promoted to the position of associate dean for research at SBMI in 2002, and was advanced to the status of professor in 2005. In 2012, he was named SBMI's interim dean and, subsequent to a national search, he was appointed dean in 2013. His current focus is on strategic thinking and initiatives centered on improving healthcare and advancing biomedical discovery through health data science and artificial intelligence, clinical and health informatics, and bioinformatics and systems medicine.

Research
Jiajie Zhang has co-authored 200+ research articles, and has been the principal investigator, co-principal investigator, or co-investigator of numerous grants and contracts from The Office of the National Coordinator for Health Information Technology (ONC), National Institutes of Health (NIH), Agency for Healthcare Research and Quality (AHRQ), NASA, Office of Naval Research, United States Army, and the State of Texas, among other U.S. funding agencies.

Zhang has made a significant number of research contributions, including but not limited to, the following:

1.	Distributed Knowledge Representations. One of Zhang's major contributions is his work on distributed knowledge representations and their effects on decision-making, problem solving, and human-computer interaction. The idea of distributed knowledge representation is that the information needed for most complex information processing tasks (e.g., making a diagnosis or reviewing a patient chart) is distributed across the external technology (e.g., electronic health records) and the internal mind (e.g., expert knowledge of a medical domain). External and internal information have different processing mechanisms that can fundamentally determine the representational efficiencies, task complexities, problem difficulties, information flows, and behavioral outcomes of tasks. The result of this research is the theory of distributed representations for distributed cognition, which has been applied to the design of efficient information systems in many domains, including Electronic Health Records (EHR), medical devices, aviation systems, consumer products, education technology, etc. The theory of distributed knowledge representation is also the foundation of the TURF framework of EHR usability.

2.	EHR Usability and Workflow. Zhang's second major contribution is his research on usability and workflow in EHR (Electronic Health Records) systems. One major product from this line of research is a unified framework called TURF, which stands for Task, User, Representation, and Function, the four major components of EHR usability. TURF is a theory for defining, describing, explaining, and predicting usability; a method for evaluating, measuring, and designing usability; and a software tool suite for automating usability evaluation and conducting user testing. TURF has been applied to a wide variety of domains in healthcare, including EHR, medical devices, emergency care workflow, medical error taxonomy, etc.