Efficient Ai Hardware Algorithm Professors in Global

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Il-min Kim
Queen's University Canada
ai physical systems
generative ai
safe generative ai
responsible ai
ai alignment
multiple ai agents
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Yiren Zhao
Imperial College London United Kingdom
efficient ai
hardware-algorithm interplay
large-scale generative ai systems
automatic co-design of ai systems
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Jiaqi Gu
Arizona State University China
No active positions
efficient ai hardware design
efficient algorithm
emerging hardware design for efficient computing
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Beidi Chen
Carnegie Mellon University United States of America
efficient machine learning
hardware acceleration for machine learning
algorithm optimization
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Guang Lin
Purdue University United States of America
reliable ai
robust ai
physics-informed ai
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David Pan
University of Texas at Austin United States of America
efficient machine learning
ai chip designs
hardware acceleration
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Guangzhi Tang
Maastricht University Netherlands
efficient deep learning
ai-enabled automation
edge ai
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Anne Marx
ETH Zurich Switzerland
interactive ai systems
multimodal ai
human-ai collaboration
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Michael Rovatsos
University of Edinburgh United Kingdom
human-friendly ai
game-theoretic ai
ethical ai
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Mobarak Hoque
University of Manchester United Kingdom
medical imaging ai
agent-based ai
safe and trusted ai
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Steven Whang
Korea Advanced Institute of Science and Technology South Korea
trustworthy ai
data-centric ai
responsible ai
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Wm. Kennedy
University of Oxford United Kingdom
interdisciplinary ai
ai evaluations
ai education
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Michael Rovatsos
University of Edinburgh United Kingdom
game-theoretic ai
responsible ai
ethical ai
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Jiaqi Gu
Arizona State University China
No active positions
efficient ai hardware & algorithm
efficient computing
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Priyadarshini Panda
University of Southern California United States of America
efficient ai
algorithm-hardware co-design
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Priyadarshini Panda
University of Southern California United States of America
efficient artificial intelligence
algorithm-hardware co-design
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Lars Karlsson
Umeå University Sweden
efficient algorithms
high-performance computing
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Michael Bader
Technical University of Munich Germany
hardware-aware algorithms
high performance computing
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Yue Zhao
University of Southern California United States of America
reliable ai systems
scalable ai systems
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Yue Zhao
University of Southern California United States of America
reliable ai systems
evaluation frameworks for ai
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Moses Charikar
Stanford University United States of America
efficient algorithmic techniques for processing high-dimensional data sets
efficient algorithms for computational problems in high-dimensional statistics
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