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Pushing Mobile Inventions Forward Seminar: Fjola Helgadottir, PhD – Director of AI Therapy

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Fjola Helgadottir, PhD

Director of AI Therapy

Vancouver CBT Centre

 

Translating Clinical Psychology Treatments into Algorithms: Successes and Challenges

Abstract: Computerized therapy has the potential to revolutionize how evidence based psychological interventions are delivered to those who need them. Many of the recent advances in AI, from computer vision to natural language processing, will doubtlessly be integral components of future treatment systems.

There is a wide range of approaches to computerized therapy. Many research projects aim to replicate the face-to-face therapy experience. This seems like a natural approach, given that this is a longstanding and proven model of therapy. For example, these systems make use of avatars and chatbots. However, this approach may be misguided. Computer-based approaches and human therapists are fundamentally different, and designing one to mimic the other may not be optimal. The goal should be to find the most effective methods of targeting the key mechanisms that are paramount to change in mental health.

In this talk Dr. Helgadottir will take a look at computerized therapy from the perspective of a practicing clinical psychologist. She will review some of the advantages that computers have over human therapists, as well as considering limitations of these systems. As a practical example, she will explain how her online “Overcome social anxiety” program works and discuss promising results from recent clinical trials.

Bio: Dr Fjola Dogg Helgadottir is a Director at AI-Therapy, a registered psychologist at the Vancouver CBT Centre and previously a Senior Research Clinician at Department of Psychiatry, University of Oxford in the UK. She is a Chartered clinical psychologist within the British Psychological Society, and a registered psychologist with the UK Health and Care Professions Council and with the British Columbia College of Psychologists. Fjola has completed four degrees in psychology (see more professional qualifications). AI-Therapy grew out of her doctoral research, which was focused on innovative computer-based treatments for anxiety disorders.

Fjola has written extensively about online therapy, both in peer reviewed academic journals and conferences. She is an expert writer for Psychology Today with her open access blog Man vs Machine and is featured frequently in the Icelandic media. See Fjola’s publications for more details.

Fjola has received several major awards for her internationally recognized research, including Australia’s prestigious Tracy Goodall Early Career Award for Research Achievement. In addition, she has trained to the highest level as a clinical psychologist in Australia, and ran a successful private practice in Sydney. She currently provides consulting services on the topic of online psychology and psychiatry for her company AICBT Ltd, which has clients in Sydney, Australia; Oxford and London, UK; and Denver and New York in the USA.

Jacob Abernethy and Eric Schwartz: Statistical and Algorithmic Tools to Aid Recovery in Flint

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ABSTRACT: Recovery from the Flint Water Crisis has been hindered by uncertainty in both the water testing process and the causes of contamination. On the other hand, city, state, and federal officials have been collecting and organizing a significant amount of data, including many thousands of water samples, information on pipe materials, and city records. Combining all of this information, and utilizing state-of-the-art algorithmic and statistical tools, we have be able to develop a clearer picture as to the source of the problems, to accurately estimate the greatest risks, and to more efficiently direct resources towards recovery.

Bio: Jacob Abernethy is an Assistant Professor in the EECS Department at the University of Michigan, Ann Arbor. He finished his PhD in Computer Science at the UC Berkeley, and was a Simons postdoctoral fellow at the University of Pennsylvania. Jake’s primary interest is in Machine Learning, and he likes discovering connections between Optimization, Statistics, and Economics.

Bio: Eric Schwartz is an Assistant Professor of Marketing at the University of Michigan’s Ross School of Business in Ann Arbor. He received his PhD in Marketing from the Wharton School at the University of Pennsylvania in 2013. His research focuses on predicting customer behavior, understanding its drivers, and examining how firms actively manage their customer relationships through interactive marketing. The quantitative methods he uses are primarily Bayesian statistics, machine learning, dynamic programming, and field experiments.

U-M Professors Jacob Abernethy and Eric Schwartz to speak on “Statistical and Algorithmic Tools to Aid Recovery in Flint” — Sept. 12

By | Educational, Events, General Interest, News

ABSTRACT: Recovery from the Flint Water Crisis has been hindered by uncertainty in both the water testing process and the causes of contamination. On the other hand, city, state, and federal officials have been collecting and organizing a significant amount of data, including many thousands of water samples, information on pipe materials, and city records. Combining all of this information, and utilizing state-of-the-art algorithmic and statistical tools, we have be able to develop a clearer picture as to the source of the problems, to accurately estimate the greatest risks, and to more efficiently direct resources towards recovery.

Engaging with DARPA, A Presentation by DSO Director Stefanie Thompkins – May 31

By | General Interest, News

Please join us for a presentation and overview of DARPA and the Defense Sciences Office by Dr. Stefanie Tompkins, Defense Sciences Office Director.

Date:  May 31, 2016
Time: 12:30 PM
Location: Room 1500 EECS, North Campus

DARPA’s mission is to make pivotal investments in breakthrough technologies for national security, thus catalyzing the development of capabilities that give the Nation new options for preventing and creating strategic surprise.

The Defense Sciences Office (DSO) is one of six technical offices at the agency.  DSO identifies and pursues high-risk, high-payoff fundamental research initiatives across a broad spectrum of science and engineering disciplines including materials science, computing and autonomy, engineering design and manufacturing, physics, chemistry, mathematics and social science.

This presentation will give an overview of DARPA, working with DARPA and the Defense Sciences Office, and description of some of the current activities DSO’s program managers are working on.

Workshops on Algorithms for Modern Massive Data Sets — June 21-24, Berkeley

By | General Interest, News

Registration for the 2016 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2016) is now available.

In addition to four days of talks on algorithmic and statistical aspects of modern large-scale data analysis, MMDS 2016 will have a contributed poster session one evening.  The registration fee is waived for student poster presenters.  You may apply to present a poster at the event website.

Event: MMDS 2016: Workshop on Algorithms for Modern Massive Data Sets
Dates: June 21-24, 2016
Location: UC Berkeley, Berkeley, CA
Website: http://mmds-data.org
Contact: organizers@mmds-data.org
Synopsis: The 2016 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2016) will address algorithmic, mathematical, and statistical challenges in modern statistical data analysis. The goals of MMDS 2016 are to explore novel techniques for modeling and analyzing massive, high-dimensional, and nonlinearly-structured scientific and internet data sets, and to bring together computer scientists, statisticians, mathematicians, and data analysis practitioners to promote cross-fertilization of ideas.
Organizers: Michael Mahoney (UC Berkeley), Alex Shkolnik (Stanford), and Petros Drineas (RPI)