Cognition

Vignesh Subbian is an Assistant Professor of Biomedical Engineering, Systems and Industrial Engineering, member of the BIO5 Institute, and a Distinguished Fellow of the Center for University Education Scholarship (CUES) at the University of Arizona (UA). His professional areas of interest include medical informatics, healthcare systems engineering, and broadening participation in engineering and computing. Dr. Subbian leads the Computational Medicine and INformatics (COM-IN) Collaboratory at the UA, with a focus on transforming human health and healthcare and health through engineering-driven and integrative research as well as training next-generation scientists, engineers, clinicians, and leaders through personalized mentorship and true multidisciplinary immersion. Funded through the National Science Foundation (NSF) and the Agency for Healthcare Research and Quality (AHRQ), research efforts in the COM-IN Collaboratory leverage systems engineering and computational methods including machine learning for clinical and healthcare applications. Current patient populations of interest include cardiovascular diseases, traumatic brain injury, and mental health disorders. Dr. Subbian is the principal investigator on an NSF Smart and Connected Health award to develop advanced computational models and tools for critical care medicine, particularly traumatic brain injury prognosis. Dr. Subbian’s educational research is focused on ethical decision-making and formation of identities in engineering. His work in ethics education has been featured in the National Academy of Engineering (NAE) Exemplars in Engineering Ethics Education, an effort aimed to improve students’ understanding of ethical practice and research in engineering. He served as the co-chair of the NSF-funded Southwest STEM in Hispanic-serving Institutions (HSI) Conference (2017), and currently co-leads the STEM in HSI working group at the UA. He also leads the Collaborative for Engineering Education Research and Outreach (CEERO), a cross-college, interdisciplinary network of faculty, staff, and students to promote engineering education at all levels.

Fabian-Xosé Fernandez, PhD, Departments of Psychology and Neurology, McKnight Brain InstituteCircadian timekeeping is fundamental to human health. Unfortunately, under many clinical circumstances, the temporal organization of our minds and bodies can stray slowly from the Universal Time (UT) that is set with the Earth’s rotation. This disorganization has been linked to progression of several age-related and psychiatric diseases. Non-invasive phototherapy has the potential to improve disease outcomes, but the information that the brain’s clock tracks in twilight (or any electric light signal) to assure that a person entrains their sleep-wake cycles to the outside world is not understood. The central theme of my research program is to fill in this blank and to usher in an era where therapeutically relevant “high-precision” light administration protocols are institutionalized at the level of the American Medical and Psychiatric Associations to change the standard of care for a wide variety of conditions that impair quality of life. Of the conditions my lab is currently studying, we are particularly interested in how chronic and quick, sequenced light exposure can be designed to: 1. promote normal healthy aging and 2. strengthen adaptive cognitive/emotional responses to being awake in the middle of the night (12-6AM), a key interval of the 24-h cycle that we have associated with increased suicidal ideation and mortality. Our circadian work on suicide is done in very close partnership with the University of Arizona Sleep Health and Research Program directed by Dr. Michael A. Grandner.

Lisa Elfring is an Associate Specialist in the Department of Molecular and Cellular Biology and currently serves as Associate Vice Provost for Instruction and Assessment. In this administrative role, she leads the Office of Instruction and Assessment (OIA), which supports teaching and learning across campus. The office supports technology-enabled teaching (D2L, Panopto, Adobe Connect, VoiceThread); provides professional development and courses on evidence-based teaching for all UA instructors; produces media products (web pages, videos) that support instructors in their teaching; helps departments to carry out assessment of learning outcomes; and helps to connect instructors across departmental and college boundaries. Dr. Elfring is currently involved in two teaching-related research projects. In one, she and her collaborators are investigating a model to train instructors in large, collaborative STEM classes to utilize a team of graduate and undergraduates to improve student learning. In the other, the team is investigating the effects on students on creating and improving models in biological systems, in the context of an Introductory Biology lab course. Both projects are funded by awards from the National Science Foundation. Dr. Elfring's teaching experiences range from large courses in introductory cell/molecular biology and cell biology, to courses focusing on helping undergraduate students to prepare for doing laboratory research. Her research interests are integrated with her teaching role. She is interested in process of systemic change in educational systems, and particularly in how the university can promote the adoption, use, and assessment of research-based teaching strategies across the entire range of STEM (science, technology, engineering, and math) courses. In biology education, she has been involved in research on how students come to make sense of the key biological concept that genes code for RNAs which (mostly) encode proteins to form the structural and catalytic molecules of the cell, a process that is termed the central dogma of molecular biology. She and her collaborators were involved in efforts to introduce more quantitative problem-solving work in the Introductory Biology course and across the undergraduate life-sciences curriculum. Her undergraduate, graduate, and post-doctoral training is in molecular, cell, and developmental biology; she has done research using humans, mice, and fruit flies as experimental systems to investigate embryonic development and cancer. Keywords: Biology education, Faculty professional development

Dr Chen's areas of expertise include:Security informatics, security big data; smart and connected health, health analytics; data, text, web mining.Digital library, intelligent information retrieval, automatic categorization and classification, machine learning for IR, large-scale information analysis and visualization.Internet resource discovery, digital libraries, IR for large-scale scientific and business databases, customized IR, multilingual IR.Knowledge-based systems design, knowledge discovery in databases, hypertext systems, machine learning, neural networks computing, genetic algorithms, simulated annealing.Cognitive modeling, human-computer interactions, IR behaviors, human problem-solving process.