The following Great Innovative Idea is from Vivian Motti, Assistant Professor in the Department of Information Sciences and Technology at George Mason University. Motti presented her poster, Wearable Health: Exploring Human-Centered Solutions of On-Body Technologies to Improve Healthcare, at the CCC Symposium on Computing Research, May 9-10, 2016. The Idea By combining a variety of sensors and actuators in multiple form factors, wearable technologies are versatile. They accommodate requirements of diverse applications, being successfully employed to support, enhance and replace human activities in several domains, including healthcare, transportation and education. A large number of wearable devices is commercially available today, and the shipments are also expected to grow in the future. Despite such […]

The following Great Innovative Idea is from Bert Huang, Assistant Professor of Computer Science atVirginia Tech. Huang presented his poster, Weakly Supervised Cyberbullying Detection in Social Media, at the CCC Symposium on Computing Research, May 9-10, 2016. The Idea One of my research topics that I’m most passionate about is on developing machine learning algorithms that detect cyberbullying in social media. Cyberbullying is a serious public health threat that is detrimentally shaping the online experience. And while Internet technology is rapidly amplifying our ability to communicate, it’s important to develop complementary technology to help mitigate the harm of such detrimental communication. Computer programs that detect online harassment could allow automatic interventions, […]

The following Great Innovative Idea is from Christopher B. Harris, the Presidential Diversity Postdoctoral Fellow in the School of Engineering at Brown University. Harris presented his poster, Processor Design Exploration for Vision Based Mobile Robots, at the CCC Symposium on Computing Research, May 9-10, 2016. The Idea At Brown University, we’re designing robots! Actually, we’re building the simulation tools used to design mobile robots. Mobile robots require specialized algorithms for tasks such as perception and control. These algorithms are often very processor intensive. As a result, much of the innovation in mobile robotics currently occurs at the software level. Robotics researchers will often devise new algorithms and run them on whatever computing platform is […]

The following Great Innovative Idea is from Gloria Washington, an Assistant Professor of computer science at Howard University. In addition to being an Assistant Professor, Dr. Washington is the Director of the Affective Biometrics Lab. Washington presented her poster, A Socio-Cultural & Technical Approach to Affective Biometrics, at the CCC Symposium on Computing Research, May 9-10, 2016. The Idea Traditional approaches to biometric recognition and affective computing involve using a database to train computer algorithms to recognize different types of individuals and emotional states. However, these databases are usually not diverse and include only subjects from majority populations. Howard University is developing technologies that can use computer vision and affective […]

The following Great Innovative Idea is from Katie Henry, a current PhD student in computer science at Johns Hopkins University. In addition to the department, Henry is also part of the Malone Center for Engineering in Healthcare, the Institute for Computational Medicine, and the Center for Language and Speech Processing. Henry presented her poster, Automated in-patient monitoring in the ICU with application to septic shock prediction, at the CCC Symposium on Computing Research, May 9-10, 2016. The Innovative Idea Traditional approaches to disease prediction involve a panel of experts selecting a small set of clinically meaningful measurements and using these to tabulate a score. While useful, these scores are limited because they require manual […]

The following Great Innovative Idea is from Francesca Rossi from the University of Padova. Rossi and her colleagues Joshua Greene (Harvard University), John Tasioulas (King’s College London), Kristen Brent Venable (Tulane University), and Brian Williams (Massachusetts Institute of Technology) published a paper called Embedding Ethical Principles in Collective Decision Support Systems which was one of the winners at the Computing Community Consortium (CCC) sponsored Blue Sky Ideas Track Competition at the 30th Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-16), February 12-17, 2016 in Phoenix, Arizona. The Innovative Idea We intend to model both ethical principles and safety constraints in (collective) decision making systems. We believe that current AI frameworks to model and reason with preferences, as well as risk-bound reasoning […]