Computer Science, Psychology
I have always been intrigued by technology, which led me into computer science. While I had used computers for many years before, I was ten when I typed my first line of BASIC code. Since that day early in the fourth grade, I have learned a variety of languages suited to the many tasks programmers face. More importantly, however, is the fact that I did this without any supervision as my school district did not offer any programming classes at any point during my primary school career. This really defines my drive to go out into the world and forge my own path to new knowledge.
Coming to Rensselaer Polytechnic Institute allowed me to expand my knowledge and I quickly chose a dual major in Computer Science and Psychology. My first semester, I joined the CogWorks Laboratories and began the start of my collegiate research career. I worked along undergraduates, graduates, and professors performing experiments studying human cognition and examining cognitive models. This early exposure to research was a driving factor in my application and acceptance into the Accelerated B.S./Ph.D. Program at RPI.
There were a number of additional things which led me to join the Accelerated B.S./Ph.D. Program. The lure of completing two degrees in such a short time frame was a major component in my decision. I am always looking to push myself harder in order to test the limit of my mental abilities and the accelerated program sounded like a perfect fit for someone ambitious as myself.
I am a Ph.D. student in the Tetherless World Constellation and am advised by Prof. Deborah McGuinness. My research is primarily focused on performance and power optimizations for reasoning agents on mobile devices such as smartphones that will enable next-generation applications in fields such as personalization services and healthcare. Consumer and professional grade sensors combined with the connectedness of our mobile devices provide a rich wealth of data that may be used to guide us in our decision-making or just to provide overviews of our overall well-being but current applications often work in the cloud and are often closed to sharing data with other platforms. The goal of my work is to make data collected by such sensors openly available to other applications on mobile devices to encourage those who think outside the box to generate new and innovative applications using this wealth of data.