Associate senior lecturer/Assistant Professor at Department of Information Technology, Division of Scientific Computing
Prashant Singh is an Assistant Professor at the Division of Scientific Computing, Department of Information Technology and also affiliated to the Science for Life Laboratory, Uppsala University as a SciLifeLab fellow. His research interests involve developing machine learning and optimization methods to enable fast, data-efficient analysis and processing of scientific data, particularly in the domain of life sciences.
Keywords: scientific computing systems biology machine learning optimization active learning bayesian inference surrogate models
Prior to joining Uppsala University, Prashant Singh was an Assistant Professor at the Department of Computing Science, Umeå University. Prashant was a postdoctoral researcher at the Division of Scientific Computing, Department of Information Technology, Uppsala University between 2017 and 2020, where his research explored machine learning and statistical sampling methods within the domain of computational biology. 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.
Prashant's research interests broadly span optimization and machine learning. He is particularly interested in developing efficient methods for data-scarce or computationally expensive problems. Some related topics include constrained multi-objective optimization, surrogate modeling, parameter inference, inverse modeling, active learning, sequential sampling, design of experiments, etc.
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