Associate Professor of Electrical and Computer Engineering
Adjunct Associate Professor of Biomedical Engineering
Program Faculty Bioengineering
Education
Ph.D., Electrical Engineering, Stanford University, Stanford, CA, 2009
M.Sc., Electrical Engineering, Stanford University, Stanford, CA, 2005
B.Sc., Electrical Engineering, Stanford University, Stanford, CA, 2004
Major Awards
Office of Naval Research Young Investigator Award (ONR YIP), 2018
National Science Foundation CAREER Award, 2018
IEEE Sensors Early Career (Young Professional) Award, 2018
Roger P. Webb Outstanding Junior Faculty Member Award (ECE), Georgia Tech, 2018
Sigma Xi Young Faculty Award, Georgia Tech, 2017
Lockheed Dean’s Excellence in Teaching Award, Georgia Tech, 2016
G. J. Lieberman Fellowship, Stanford University, 2009
Interested in circuit design for wearable and clinically-accurate biomedical instruments and the processing of biomedical signals. Specifically, I have been working on the design of instruments and signal processing techniques to monitor the health of joints such as the knee and the wrist.
My research interests center around the development of embedded systems and statistical signal processing algorithms for bio-medical applications. Specifically, I am currently working on developing methods for detecting local muscle fatigue during physical exercise.
I am interested in researching physiological responses to external stimuli and designing non-invasive monitoring devices to process these responses. Overall, I aim to develop wearable biomedical instrumentations that will be able to monitor a patient both in a clinic and at home.
I am interested in researching medical devices and systems, particularly those used for long-term home monitoring. This research focuses on measuring biological signals and leveraging the results to provide useful clinical data. At-home systems challenge us to minimize intrusiveness to daily activities and limit required patient system knowledge and input.
My research interests are manifold but center around the concepts of intelligent design and integration of medical devices at the systems level. I am especially keen on developing technologies to advance the fields of noninvasive diagnostics, rehabilitation, and space medicine.
My research interests focus on novel, non-invasive techniques for characterizing physiological processes.
In particular, I am designing a cadaver model for better understanding the underlying biomechanical properties
responsible for joint sounds and correlating that with clinical diagnosis/prognosis.
My research interest is in the field of biosensing device, e.g., wearable and bioMEMS device. I have worked on implantable neural array for large neuronal mapping. Presently I am working on noninvasive medical devices, sensor fusion, signal processing and machine learning with emphasis on cardiovascular monitoring for patients with heart failure.
My research interests include physiological modulation, monitoring, active sensing, bio-inspired circuits and systems. I work on biomedical instrumentation, signal processing, and machine learning with a focus on mood and performance improvement.
My research interest focus on biomedical sensing system for home monitoring. This includes developing novel wearable devices, measuring bio-signals, and analyzing those through signal processing algorithms to get clinically useful data.
My research interests are to use embedded systems and machine learning to develop miniaturized sensors that can be used in and outside the clinic. My main focus is to develop a miniaturized bioimpedance sensor to detect IV infiltration and evaluate joint health.
My research interests focus on non-invasive wearables that leverage novel signal processing techniques for physiological monitoring.
My research interests include designing circuits and systems for sensing biological signals, and finding biomarkers for quantifying the biomedical condition through signal processing techniques. Designing such systems and miniaturizing them to a wearable size helps with health monitoring for both clinical and at-home settings.
My interests focus on learning, automation and noise-reduction algorithms for use in non-invasive wearable devices for physiological monitoring. In particular, I am working towards an algorithm to non-invasively estimate an individual’s blood volume status.
My main research interests are embedded systems and assistive robotics.
