Andreas Neofytou

Andreas is a Teaching Assistant in the Department of Computer & Information Sciences and a PhD student in the Department of Management Science at Strathclyde Business School. He is a researcher in the intersection of machine learning and optimization. He is specializing in decision-making under uncertainty and optimization problems utlizing machine learning algorithms.

My broad research area encompasses machine learning and optimization, with a particular focus on decision-making under uncertainty. I attempt to merge machine learning and optimization, by bridging the gap of a good prediction to a good decision. My research interest is to improve the decision-making process under uncertainty with machine learning. Particularly by proposing variants and extensions of robust ML algorithms, starting from data leading to high quality (robust) decisions and predictions. From predictive to prescriptive solutions and approaches, leading to stronger prescriptive performance with advanced machine learning algorithms.

I have been extensively involved with teaching activities in various levels from undergraduate to postgraduate in the department of Computer and Information Sciences, mainly in Machine Learning and Deep Learning classes, along with Optimization classes in the department of Management of Science.

• Machine Learning
• Deep Learning
• Decision-Making under Uncertainty
• Robust Optimization
• Nonparametric Bayesian Models
• Reinforcement Learning