Prashant Singh is a postdoctoral researcher at the Division of Scientific Computing, Department of Computer Science, Uppsala University. His current research involves developing machine learning and optimization methods to enable fast, data-efficient analysis and processing of scientific data, particularly in the domain of systems biology.
Keywords: scientific computing systems biology machine learning optimization active learning bayesian inference surrogate models
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Prashant Singh obtained the degree of PhD in Computer Science Engineering from Ghent University, Belgium in May 2016, where he specialized in model-based optimization and active learning. Prashant received his MSc degree in Computer Science from the University of Delhi, India in 2011, with specialization in data mining and supervised machine learning.
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