Andrew Bernat

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In a problem-based learning (PBL) environment, students work in groups on real-life problems and have the opportunity to determine for themselves what they need to learn in the relevant subject area(s). A common feature of problem-based learning is to provide students with a range of resources that assist them in solving the problems. This paper attempts to(More)
The benefits of working in a research group are clear: students develop domain expertise, gain an understanding and appreciation of the research process and its practice, and acquire team, communication, problem-solving, and higher-level thinking skills. Students with this experience are better equipped to make informed judgements about technical matters(More)
Dynamic binary instrumentation for performance analysis on new, large scale architectures such as the IBM Blue Gene/L system (BG/L) poses new challenges. Their scale---with potentially hundreds of thousands of compute nodes---requires new, more scalable mechanisms to deploy and to organize binary instrumentation and to collect the resulting data gathered by(More)
Dynamic binary instrumentation for performance analysis on large scale architectures such as the IBM Blue Gene/L system (BG/L) poses unique challenges. Their unprecedented scale and often limited OS support require new mechanisms to organize binary instrumentation, to interact with the target application, and to collect the resulting data. We describe the(More)
Author Roger Bivand <Roger.Bivand@nhh.no>, with contributions by Micah Altman, Luc Anselin, Renato Assunção, Olaf Berke, Andrew Bernat, Eric Blankmeyer, Marilia Carvalho, Yongwan Chun, Bjarke Christensen, Carsten Dormann, Stéphane Dray, Rein Halbersma, Elias Krainski, Nicholas Lewin-Koh, Hongfei Li, Jielai Ma, Giovanni Millo, Werner Mueller, Hisaji Ono,(More)
This panel focuses on computer science research and educational activities involving minorities. In addition to highlighting various research in progress, this panel will emphasize how research at a given institution has impacted the corresponding computer curriculum. Specific information to be discussed by the panel will include: 1) a brief overview of(More)
An important area of application of computer vision is the detection of object motion. We are currently developing a computer vision system to automatically detect and track human motion across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of(More)