Advanced Studies in Adaptive
Systems (CASAS) lab
Electrical Engineering and Computer Science
I am selected to attend
Google Summer of Code 2017 Mentor Summit, Oct. 13th - 14th,
07/17/2017: I am one of the students
in receipt of EECS's Scholarship to atttend 2017 Grace Hopper
Celebrating, Oct. 4th-6th, Orlando, FL!
in Computer Science, Washington State University Jan. 2016-Present.
3.79 Advisor: Dr. Diane J.
I am a Ph.D. student and have been using data to find human
patterns as a preventative study to detect early signs of chronic
diseases under the smart home environment. To do this, I have been
applying big data and machine learning technologies to do data analysis
by using Python and R with well-defined methods and algorithms as well
as exploring and developing new methods and algorithms.
project I have been working on is granted by the Department of
Energy and by the U.S. Environmental Protection Agency's Science to
Achieve Results (STAR) program. Our research is about Integrated
Measurements and Modeling Using US Smart Homes
to Assess Climate Change and Human Behaviors Impact on Indoor Air
My most recent work is about Population Modeling. Currently we
billions of dollars treating the late-stage chronic disease when it’s
often in vain, this preventative study is to detect chronic diseases
earlier when it can be cured under the SH environment by applying big
data and machine learning technologies.
My research interests include smart home, machine learning,
applications for healthcare, and compute science education.
2017 Publications (Journal Articles)
Kirk, Max, Madeline Fuchs, Yibo Huangfu, Tom
Jobson, Patrick O’Keeffe, Shelley Pressley, Von Walden, Beiyu Lin,
Diane Cook, and Brian
Lamb. Indoor Air Quality and Wild Fire Smoke Impacts in the Pacific
Northwest, the ASHRAE Journal of
Science and Technology for the Built Environment, 2017 (to be
B. Lin, Y. Huangfu, N. Lima, B. Jobson, M.
Kirk, P. O'Keeffe, S. N. Pressley, V. Walden, B. Lamb, and D. J. Cook.
Analyzing the Relationship
between Human Behavior and Indoor Air Quality, Journal of Sensor
and Actuator Networks, 2017, 6(3), 13.
Correction: the selected VOCs, including
acetaldehyde, acetonitrile, methanol, ethanol, acetone, benzene,
toluene, xylenes, styrene, and monoterpenes, were measured continuously
with a proton transfer reaction mass spectrometer (PTR-MS, Ionicon
Analytik, Innsbruck, Austria, Europe).
Part 1: data
visualization and transformation: smarthome-based human behavior
Part 2: finding the
relationship between human behavior and indoor air quality based on three
analyses and we
report correlation coefficients that are moderate or large (r >=
Part 3: feature
extraction based on three learning algorithms.
Part 1: point
density for mobile phone data with different radium values.
Part 2: modelling for aggregated dataset.