About Us

Professor Mihailidis is the Associate Vice-President for International Partnerships at the University of Toronto, and the Scientific Director of the AGE-WELL Network of Centers of Excellence, which focuses on the development of new technologies and services for older adults. He is a Professor in the Department of Occupational Science and Occupational Therapy (U of T) and in Biomedical Engineering (U of T), with a cross appointment in the Department of Computer Science (U of T). Professor Mihailidis has been conducting research in the field of technology to support older adults for the past 24 years, having published over 250 journal papers, conference papers, and abstracts in this field. Dr. Mihailidis is also very active in the rehabilitation engineering profession, currently as a Past-President for RESNA (Rehabilitation Engineering and Assistive Technology Society of North America). He was also named a Fellow of RESNA in 2014, one of the highest honors within this field of research and practice, and a Fellow in the Canadian Academy of Health Science (CAHS) in 2021 for his contributions to the health and well-being of older Canadians. In 2022, Dr. Mihailidis was recognized by the UN as one of the Healthy Ageing 50 – 50 leaders working to transform the world to be a better place in which to grow older. Professor Mihailidis received a B.A.Sc. in Mechanical Engineering from University of Toronto in 1996, a M.A.Sc. in Biomedical Engineering in 1998 from the University of Toronto, and a PhD in Bioengineering (Rehabilitation Engineering) in 2002 from the University of Strathclyde (Glasgow, Scotland).

Deepak Ganesan is a professor in the Manning College of Information and Computer Sciences (CICS) in the Department of Computer Science at UMASS Amherst. Ganesan's research is at the intersection of low-power sensing and communication, networked systems, and machine learning to enable pervasive sensing at scale for societal applications. His recent work includes the design of ultra-low passive radios for wearables, novel wearable technologies such as low-power eye trackers to monitor health signals, and robust detection of important health targets such as drug use, smoking, and overeating. He is a thrust lead on the NIH funded MD2K Center for Excellence on Mobile Sensor-to-Knowledge and on the executive committee of the Center for Personal Health Monitoring at UMass Amherst. Ganesan is the director of the Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer's Disease (MassAITC), a multidisciplinary initiative spanning UMass Amherst, Brigham and Women's Hospital, Massachusetts General Hospital, Brandeis University and Northeastern University, and also directs the Center for Personalized Health Monitoring (CPHM)at UMass Amherst. He received his PhD in computer science from UCLA in 2004 and his bachelor's in computer science from IIT, Madras in 1998. He is an ACM Fellow.

His work recognizes the central role that families, friends, and communities play in caring for the increasing – and increasingly diverse – number of persons living with Alzheimer’s disease and similar dementia illnesses and helping them to remain as independent as possible in their communities. He sees family caregivers as occupying what is, in effect, a clinical role – or, really, an amalgam of a variety of clinical roles. As such, caregivers need training and education to help them understand the conditions with which they are dealing, to strengthen their own sense of competence to enable them to approach the role with confidence, and to develop strategies for caregiving that take the strengths and deficits of the care recipient into account. He and colleagues from a very wide range of disciplines have developed and tested programs designed to strengthen the capacity of informal caregivers to function effectively in their caregiving role in a manner that preserves their own health and well-being. They have drawn from the work of Albert Bandura in designing psychoeducation programs that strengthen caregivers' sense of self-efficacy for caregiving. Through a  series of projects that, with support from the National Institute on Aging  (NIA), the National Institute of Nursing Research (NINR), and the national Alzheimer's Association, Hepburn and his colleagues have established the evidence base for the Savvy Caregiver Program and Tele-Savvy (an online version of Savvy), psychoeducation programs for caregivers of persons with Alzheimer's disease and other dementia disorders. Hepburn is the co-Director of the NIA-supported Emory Roybal Center for Dementia Caregiver Mastery, an NIA-sponsored program to provide support for projects that pilot interventions designed to promote caregiving competence and confidence (mastery) in a variety of dementia caregiving contexts and situations. He is also Director of Research in the Woodruff Health Science Center for Health in Aging.

She serves as the director of the Ken Kennedy Institute at Rice University. Kavraki received her B.A. in Computer Science from the University of Crete in Greece and her Ph.D. in Computer Science from Stanford University, working with Professor Jean-Claude Latombe. She was a research associate at Stanford University before moving to Rice. Kavraki works broadly in robotics, computational biomedicine, and physical AI. She has authored more than 300 peer-reviewed journal and conference publications and is one of the authors of the widely used robotics textbook “Principles of Robot Motion” published by MIT Press. Work in her group has produced the Open Motion Planning Library (OMPL), an open-source library of motion planning algorithms used worldwide. Besides this library her group maintains several web servers for computational biomedicine applications. Kavraki’s research has been funded by NSF, NIH, ARO, DOD, NASA, industry, and the Cancer Prevention and Research Institute of Texas (CPRIT). Kavraki's more than 40 postdocs and PhD students have gone on to faculty positions at top universities, industry research labs, startups, and large software companies. Through her role at the Ken Kennedy Institute, she brings faculty together across seven schools and twenty-seven departments to shape large research projects and future directions in AI, data, and computing at Rice University.

Baker’s research agenda has been to establish an original, meaningful and coherent program of research in pain management, health outcomes and behaviors, and domains of health disparities and social determinants of health among diverse race and marginalized populations. Specifically, it is her intent to continue a line of research that provides a knowledge base to understand and explain the experience and management of chronic pain among older minority populations, with an interest in further understanding the influence of social determinants of health. This will be accomplished with continued productivity in developing and testing models identifying clinical and psychosocial factors that influence the pain experience, health behaviors, and outcomes, and by developing and implementing intervention programs leading to optimal pain management in clinic- and community-based settings.

Tara Behrend is the John Richard Butler II Endowed Professor at the School of Human Resources and Labor Relations at Michigan State University. She is currently serving as President of the Society for Industrial and Organizational Psychology (SIOP). Her research group, the Workplaces and Virtual Environments Lab, focuses on workplace technologies and their ethical, social, and psychological implications. She is a recognized expert in the areas of electronic surveillance and human-AI interactions, speaking regularly with policy makers and other audiences worldwide. Her work is multidisciplinary and has been published in psychology, education, and technology journals.

Walter R. Boot, Ph.D., is Professor of Psychology in Medicine within the Division of Geriatrics and Palliative Medicine and Associate Director of the Center on Aging and Behavioral Research at Weill Cornell Medicine. He is one of five principal investigators at the multi-disciplinary Center for Research and Education on Aging and Technology Enhancement (CREATE), a long-standing and award-winning National Institute on Aging-funded center dedicated to ensuring that the benefits of technology can be realized by older adults. He is also Co-Director of the ENHANCE (Enhancing Neurocognitive Health, Abilities, Networks, & Community Engagement) Center, funded by the National Institute on Disability, Independent Living, and Rehabilitation Research, with a focus on how technology can support older adults living with cognitive impairment. His research interests include how existing and emerging technologies can support the health, wellbeing, quality of life, and social connectivity of older adults with and without cognitive impairments. He is a Fellow of the American Psychological Association (APA) and the Gerontological Society of America.

Dr. Xiaopeng Zhao is a professor of mechanical, aerospace, and biomedical engineering at the University of Tennessee, Knoxville. He received BS and MS degrees in engineering mechanics in 1996 and 1999 respectively from Tsinghua University, China. He received Ph.D. in engineering science and mechanics in 2004 from Virginia Tech. He worked as a postdoctoral research associate in biomedical engineering at Duke University in 2005-2007. Dr. Zhao joined the Department of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville in 2007 and has become a full professor since 2019. Dr. Zhao is the project director on Detection, Care, and Treatment of Alzheimer’s Disease and Related Dementia, a research consortium that brings together researchers, scientists, students, and clinicians across the state of Tennessee and neighboring states to develop innovative cross-disciplinary techniques to improve the quality of life for people with ADRD as well as their caregivers. He serves as the faculty lead for the Brain-computer Interface (BCI) Community of Scholars at UTK and as a joint faculty professor at the Bredesen Center. His research focuses on neural engineering, BCI, robotics, and artificial intelligence. He has broad training and expertise on biomedical signal processing, machine learning, dynamics and control, electrophysiology, data mining, data analytics, and computer simulations. His lab has developed EEG biomarkers for detecting cognitive deficits such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and traumatic brain injury (TBI). His lab has also developed EEG-based BCI for controlling robotic devices, including social robots, drones, remote-controlled cars, and robotic arms. His lab has developed award-winning computer algorithms suitable for improving qualities of physiological signals.