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in the ongoing project ProcTwin that investigates how a distributed AI system can capture and predict the behavior of a production system under operational conditions. The project develops data
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embedded within a collaborative research program between MBZUAI and the AI for Climate initiative at the University of Chicago, supported by funding from the International Affairs Office at the Presidential
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to ethical and reproducible research. Relevant experience may include network measurement, mobile systems, browser instrumentation, distributed experimentation, statistical analysis, causal inference, large
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projects focused on optimization, data analytics, and control of power distribution systems. This position offers the opportunity to collaborate closely with utility company partners and national
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image reconstruction. Your research will focus on creating a new generation of ultrasound imaging systems that combine multiple distributed transducers into a coherent imaging platform. You will develop
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DeepMD, NEXMD, i-PI, MixPI, NWChem, CP2K, or comparable packages. Experience with GPU acceleration, distributed training, high-performance computing systems, or C/C++ scientific software development
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Professor of Machine Learning and Computer Science, MBZUAI. Dr. Ho specializes in distributed machine learning and systems architecture. His expertise drives the design of robust, parallelized systems
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Science, MBZUAI. Dr. Ho specializes in distributed machine learning and systems architecture. His expertise drives the design of robust, parallelized systems required to scale massive biomedical imaging models
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systems that combine multiple distributed transducers into a coherent imaging platform. You will develop novel methods for multi-aperture ultrasound acquisition, ultrasound-based probe localisation, and
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Distributed Systems projects focused on financial systems, in collaboration with FINOS and a “Big Tech” hyperscaler Teaching load: 1 course/semester in addition to supervision of undergraduate research in