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Abdeslam Boularias
- Information
Machine learning, robotics, planning and learning in partially observable domains, reinforcement learning
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Mubbasir Kapadia
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Agent-centric models for simulating crowd dynamics that challenge foundational assumptions in crowd modeling, while providing solutions that are validated using comparisons to real data, and virtual reality experiments; solutions can be used to optimize the behavioral dynamics of real crowds and model the relationships between crowd flow and environment features, with applications in predictive analytics and crowd management, and environment layout design
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Casimir Kulikowski
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Image interpretation using planning and learning techniques; methods of theory formation for classification, configuration, planning and design problems with biomedical applications
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Dimitris Metaxas
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American Sign Language and Gesture recognition from video, human identification and intent recognition from video, human computer interaction, shape and motion representation for recognition
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Karl Stratos
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Developing computational models to learn generalizable and human-readable representations from unlabeled data, with a focus on natural language processing; reliance on mathematical frameworks such as Information theory; interest in applications of learned representations to practical problems such as entity linking
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