About Me



I am a sixth-year graduate student in the Sensors Lab in the College of Information and Computer Sciences (CICS) at UMass Amherst, where I have been working since January 2013. My advisor is Prof. Deepak Ganesan, CICS, and I am also mentored by Prof. Christopher Salthouse, ECE. I previously worked in the Architecture and Language Implementation (ALI) lab, advised by Charles Weems, CICS.

I received a B.S. in Electrical Engineering with a Computer Engineering concentration, magna cum laude, from Grove City College in spring 2011. I participated in a Research Experience for Undergraduates (REU) program at UMass in the summer of 2009.

Research Interests

My research focus is in the embedded devices and sensors area of cyber-physical systems (CPS), especially in the fields of mobile health (mHealth) and wearable computing. I believe that the incredible technical achievements in small-form-factor devices in the past few years, and the subsequent explosion of wearable devices, presents a fantastic opportunity for research that will positively affect people's everyday lives. My passion is to synthesize other fields, both in and out of computer science, into mHealth to see what interesting possibilities may arise.

I am also interested in several closely related topics, such as:

Advanced mHealth in Smartphones
Pushing mHealth in the mobile phone space (where it originated) by integrating state-of-art advancements in machine learning and biotechnology so as to push the medical uses of smartphones as far as possible.
Ultra-Low-Power (ULP) Camera Applications
As the advent of ubiquitous low-power wearables and the Internet-of-Things approaches, there is an impending need for practical but extremely energy-efficient cameras to serve as the "eyes" for these kinds of ULP devices.
Information and Communication Technologies for Development (ICTD)
A secondary application of cheap, practical ULP devices is environments where electricity is scarce, as is the case in almost all areas of the third world. I have a deep interest in folding mHealth and embedded sensing techniques into projects targeted at improving quality of life for people living in developing countries.

Research Projects

See Bibliography for all related publications.


The goal of the iShadow project is to design and build the first "computational eyeglass." The idea is to create a programmable platform that provides a suite of context-sensing tools in a low-power, robust manner, and in an unobtrusive form factor - specifically, a pair of eyeglasses. Our design is centered around eye gaze tracking, and one of our primary design goals is to provide accurate real-time gaze information at low power. We have developed a novel method for gaze tracking that uses state-of-the-art machine learning methods to extract accurate gaze information from a low-power, low-resolution embedded camera.

2013 - Present

Project Page

OS Effects on CPU State

As computer systems evolve and increase in complexity, understanding their operation becomes both more difficult and important. Minor variations in system performance can cascade, leading to chaotic performance characteristics that are challenging to evaluate. More accurate simulation and measurement systems are one approach to solving this problem. However, full-system simulation is costly and user-mode simulation omits accurate representation of operating system (OS) effects.We used a cycle-accurate full-system x86 simulator, MARSSx86, to measure effects of system calls on microarchitecture state so as to be able to better model the effects of OS calls on system performance in user-mode simulations.

2011 - 2012