Is it possible to interact with computers just the way we interact with each other? — our research focuses on addressing that fundamental question in the context of human-computer interaction. A few examples of our current and past work include: My Automated Conversation coach (MACH) — MACH is a 3D character that could “see”, “hear” and “responds” to people in real-time and give people feedback on their social interactions. We validated MACH in the context of job interviews with 90 undergraduate students and students who interacted with MACH were perceived as better candidates. We are exploring the future of MACH by using it in the context of dating, language learning and public speaking. Students with interests in computer programming are encouraged to apply.
Professor Jiebo Luo's research spans image processing, computer vision, machine learning, data mining, medical imaging, and ubiquitous computing. He has been an advocate for contextual inference in semantic understanding of visual data, and continues to push the frontiers in this area by incorporating geo-location context and social context. A recent research thrust focuses on exploiting social media for machine learning, data mining, and human-computer interaction, for example, mining the wisdom of crowds for social, political, and economic prediction and forecasting. He has published extensively with over 200 papers and 70 US patents (check http://www.cs.rochester.edu/u/jluo/).
The following areas are under current research:
Prerequisite: programming experience in C++, Matlab, Java, or Python