The Shehu lab is pushing the capability of evolutionary algorithms (EAs) to move beyond optimization and obtain comprehensive and detailed maps of complex, multi-modal energy landscapes.
We are interested in learning part based representations of objects and object categories, which would enable efficient recognition and fast retrieval and ultimately lead to scalable object recognition systems.
Minkowski sum is a fundamental operation in many geometric applications, including robotics, penetration depth estimation, solid modeling, and virtual prototyping.
Congratulations to Tatiana Maximova for winning an "Oustanding Research Presentation Prize" at at the Intelligent Systems for Molecular Biology (ISMB) Conference held in Orlando Florida, July 8-12, 2016. Dr. Maximova is a postdoctoral scholar working with Prof. Amarda Shehu.
Data captured by a Tele-Immersion (TI) system can be very large. Compression is usually needed to ensure real-time data transmission.