Brendan E. Ashby

Printer-friendly version

Brendan E. Ashby
Contact Info
Emailashbyb@rpi.edu

Brendan is a first semester Graduate student at Rensselaer Polytechnic Institute (RPI).

Brendan is pursuing his Undergraduate degree in Computer Systems Engineering (CSYS) and Computer Science (CSCI) and his Masters degree in Computer Science at RPI.

He is writing his Master's Thesis under his graduate adviser Professor Joanne Luciano.

Other projects Brendan is working on include SeeSaw: A semantic visual computational platform.

Publications

Seyed, P., Chastain, K., Ashby, B.E., Liu, Y., Lebo, T., Patton, E.W., and McGuinness, D.L. 2013. SemantEco Annotator. In Proceedings of ISWC 2013 (October 21-25 2013, Sydney, Australia).

Project Collaborator

TW LogoNightingale: Proactive Depression Treatment with Individual Social, Sensory and Virtual Technologies. (Nightingale)
Principal Investigator: Mei Si, Jonas Braasch, and Joanne S. Luciano
Description: Depression costs! Each year, billions of dollars are wasted and millions of lives are disrupted because depression is complex, access is limited, treatments are one-size-fits-all, and therapies are trial and error. Nightingale aims to develop innovative solutions using social machines, virtual reality, and pervasive sensor technologies. The goals are: (1) predict an upcoming depression based on personalized features and cognitive modeling, (2) intervene using intelligent synthetic characters and augmented realities with telepresence capabilities for therapists, and (3) provide intelligent tools to users to inform themselves about their condition. Nightingale monitors the user using non-invasive cameras and biosensors, web-based weather data and information about the user’s daily activities. Nightingale intervenes with constructive suggestions, a positive environment, or an alert that medical help is needed. Together, these solutions can better target the right treatments for the right patients at the right time.
SeeSaw - A semantic visual computational platform (SeeSaw)
Principal Investigator: Joanne S. Luciano
Description: SeeSaw is a semantic, visual, computational platform. The tool mines, sorts, visualizes, and put content into context, helping readers and authors see their community. It adds value to content that is already associated with a publication.