Jennifer A. Williams





I am a PhD student at Washington State University, studying Computer
Science with an emphasis on Aritificial Intelligence and machine learning
applications, as part of the Center for Advanced Studies in Adaptive Systems
(CASAS) group. The current focus of my research is sleep quality analysis
in a smart home environment.

Experience

Graduate Research Assistant
Washington State University

Fall 2011 - present

Teaching Assistant
Washington State University

Courses:
Data Structures
Introduction to Electrical Circuits (non-EE majors)

Summer 2011

Internships

Repperger Intern
Air Force Research Laboratory

Summer 2014

Education

PhD, Computer Science
Washington State University

Fall 2011 - Spring 2016

BS, Computer Science
Washington State University

Fall 2006 - Spring 2011

BS, Computational Mathematics
Washington State University

Fall 2006 - Spring 2011

Fellowships

NSF Integrative Graduate Education and
Research Traineeship (IGERT) Fellow

Fall 2011 - present

Distinguished Research Assistantship for
Diverse Scholars (DRADS) Fellowship

Fall 2011 - Spring 2012

Projects

Seep quality and actions throughout the day, which one has more of an impact on the other?
A joint prediction problem

(Fall 2014 - present)


In our lab, we started by evaluating smart homes as a tool to help people live independently longer. However, the focus of my research does not necessarily involve gerontechnology, but as a tool for injury recovery and for people to live independently that would not have necessarily before. For people that have been seriously injured and would require months in a hospital setting, can we reduce the hospital time for them and move them into a smart home that can do the monitoring of a hospital without that environment? For people who have cogntive impairments, can a smart home be a suitable way for them to have independence while still give loved ones peace of mind that ieverything is alright?

My focus is sleep quality in relation to daily activities. Especially for someone with an injury (either a phyiscal or cogntive one), can we predict how they are going to be during the day from base on how they sleep, similarly, are we able to predict how they will sleep based on their behavior throughout the day. The final question is which has more of an impact: does sleep quality impact the daily activities more, or do the daily activities impact sleep quality more? This is useful if any type of medications are needed as interventions.


Machine learning techniques for diagnostic differentiation of mild cognitive impairment and dementia

(Fall 2012 - Fall 2014)


Use neuropsychological measure and demographic data to predict the Clinical Dementia Rating (CDR) scores and clinical diagnoses through the implemation of well-known machine learning algorithms. Additionally, implementing feature selection methods to reduce the number of neuropsychological measures and demographic data needed to make an accurate diagnosis.


Trend analysis for functional health for older adults

(Spring 2012 - Summer 2012)


Using smart home sensors data (overhead motion sensors), developing methods for determining the functional health of the participants in the study. Analyzing sleep quality in comparison to functional health.

Publications


Journal Articles

A. Weakley, JA. Williams, M. Schmitter-Edgecombe, and DJ. Cook. Classification of mild cognitive impairment and Alzheimer's disease with machine learning and statistical techniques. Journal of Clinical and Experimental Neuropsychology, 37.9 (2015): 899-916.



Workshop Papers

JA. Williams, A. Weakley, DJ. Cook, and M. Schmitter-Edgecombe. Machine learning techniques for diagnostic differentiation of mild cognitive impairment and dementia. Proceedings of the AAAI Workshop on Expanding the Boundaries of Health Informatics Using AI, 2013.

Contact Me

email: jen_williams@wsu.edu