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Webinar Technology

The shrinking distance between human and machine: Computing where we end and the technologies begin

This webinar is brought to you by the Science/AAAS Custom Publishing Office

The shrinking distance between human and machine: Computing where we end and the technologies begin

15 June 2021

12:00 p.m. ET

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Speakers

Mobile and wearable technologies such as smartphones, smartwatches, and fitness trackers are growing more ubiquitous by the day. Unlike experiments carried out in traditional lab settings, they are allowing us to track a growing array of biological measures in mass populations, with many prompting behavioral changes based on this data, such as sitting less or sleeping more. The increasing complexity and accuracy of this data, in concert with the application of artificial intelligence, are empowering users to make more informed choices that impact not only their lifestyle and physical health, but potentially their mental health and cognitive functioning as well. This webinar will examine how humans are increasingly integrating with technologies, and how as these apps grow more advanced, they are enabling a new type of active, two-way interaction that could provide benefits well beyond the passive collection of data.

During this webinar, viewers will:

  • Discover how integrating mobile/wearable technologies into our daily lives can provide useful and actionable physical and mental health data
  • Learn how technology can influence our behavior and how we can encourage more positive than negative outcomes
  • Listen in as our experts discuss future opportunities for using these technologies to enhance cognitive function and physical fitness
  • Have the opportunity to ask questions during the live broadcast.

This Webinar will last for approximately 60 minutes.

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Related conference event

The Tianqiao and Chrissie Chen Institute and Science will hold the first annual conference on breakthroughs in cognitive science October 6 – 7, 2021. This year’s conference will be held virtually and will highlight two emerging areas:

  • Day 1: Recent progress in Affective Computing/Emotion/Facial Expression
  • Day 2: Machine Learning/Speech/Language

To learn more and register for the conference, click here. Registrants for this webinar will receive a 20% discount code for the conference.

Speaker bios

Michael Snyder, Ph.D.

Stanford University
Stanford, CA

Dr. Snyder is the Stanford W. Ascherman Professor and Chair, Department of Genetics, and director of the Stanford Center for Genomics and Personalized Medicine at Stanford University School of Medicine. He received his Ph.D. from the California Institute of Technology and carried out his postdoctoral training at Stanford University. He is a leader in the field of functional genomics and multiomics, and one of the major participants in the Encyclopedia of DNA Elements (ENCODE) project. His laboratory was the first to perform a large-scale functional genomics project for any organism, and has developed many technologies in genomics and proteomics. These technologies have been used for characterizing genomes, proteomes, and regulatory networks. Seminal findings from the Snyder laboratory include the discovery that much more of the human genome is transcribed and contains regulatory information than was previously appreciated (for example, long noncoding RNAs and transcription-factor binding sites), and that a high diversity of transcription-factor binding occurs both between and within species. He launched the field of personalized medicine by combining different state-of-the-art 'omics technologies to perform the first longitudinal detailed integrative personal 'omics profile (iPOP) of a person, and his laboratory pioneered the use of wearable technologies (smartwatches and continuous glucose monitoring) for precision health. He is a cofounder of many biotechnology companies, including Personalis, SensOmics, Q Bio, January, Protos, Oralome, Mirvie, and Filtricine.

 

Evelina G. Fedorenko, Ph.D.

Massachusetts Institute of Technology
Cambridge, MA

Dr. Fedorenko is a cognitive neuroscientist who studies the language system. She received her Bachelor’s degree from Harvard University in 2002, and her Ph.D. from the Massachusetts Institute of Technology in 2007. She was then awarded a K99/R00 career development award from the National Institute for Child Health and Human Development at the U.S. National Institutes of Health. In 2014, she joined the faculty at Harvard Medical School/Massachusetts General Hospital in Boston, and in 2019 she returned to MIT where she is currently the Frederick A. (1971) and Carole J. Middleton Career Development Associate Professor of Neuroscience in the Brain and Cognitive Sciences Department and the McGovern Institute for Brain Research. Dr. Fedorenko uses fMRI, EEG/ERPs, MEG, intracranial recordings and stimulation, and computational modeling to study adults and children, including those with developmental and acquired brain disorders.

Tom Griffiths, Ph.D.

Princeton University
Princeton, NJ

Dr. Griffiths is the Henry R. Luce Professor of Information Technology, Consciousness and Culture in the Departments of Psychology and Computer Science at Princeton University, New Jersey. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life. He completed his Ph.D. in psychology at Stanford University in 2005 and taught at Brown University and the University of California, Berkeley, before moving to Princeton. He has received awards for his research from organizations ranging from the American Psychological Association to the National Academy of Sciences, and is a coauthor of the book Algorithms to Live By: The Computer Science of Human Decisions, introducing ideas from computer science and cognitive science to a general audience.

Dina Katabi, Ph.D.

Massachusetts Institute of Technology
Cambridge, MA

Dr. Katabi is the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts. She is also director of MIT’s Center for Wireless Networks and Mobile Computing, a member of the National Academy of Engineering, and a recipient of the MacArthur Genius Award. She received her Ph.D. and Master’s degrees from MIT, and her B.S. from Damascus University. Her research focuses on innovations in mobile computing, wireless sensing, and machine learning with application to digital health. Dr. Katabi’s research has been recognized with the Association for Computing Machinery (ACM) Prize in Computing, the ACM Grace Murray Hopper Award, the SIGCOMM Test of Time Award, the Faculty Research Innovation Fellowship, a Sloan Research Fellowship, the NBX Career Development Chair, and the National Science Foundation CAREER Award. Her students twice received the ACM Doctoral Dissertation Award in computer science and engineering. Her work was also recognized with the IEEE William R. Bennett Prize, three ACM SIGCOMM Best Paper awards, a Networked Systems Design and Implementation Best Paper award, and a TR10 award. Several startups have been spun out of Katabi’s lab, including PiCharging and Emerald.

Sean Sanders, Ph.D.

Science/AAAS
Washington, DC

Dr. Sanders did his undergraduate training at the University of Cape Town, South Africa, and his Ph.D. at the University of Cambridge, UK, supported by the Wellcome Trust. Following postdoctoral training at the National Institutes of Health and Georgetown University, Dr. Sanders joined TranXenoGen, a startup biotechnology company in Massachusetts working on avian transgenics. Pursuing his parallel passion for writing and editing, Dr. Sanders joined BioTechniques as an editor, before joining Science/AAAS in 2006. Currently, Dr. Sanders is the Director and Senior Editor for Custom Publishing for the journal Science and Program Director for Outreach.

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