School of Mathematics


We have three full-time consultants with close links to members of the School of Mathematics' Data and Decision research theme, and the University of Edinburgh's Centre for Statistics.

Dr Michael Allerhand

Photo of Mike Allerhand

Mike is a statistician with a background in statistical modelling, machine learning, statistical programming, and numerical analysis.  He has skills in data visualization, data reduction, feature engineering, statistical modelling, and machine learning for inference, prediction, and classification.

Mike is an expert R programmer with many years' experience applying these methods to a wide variety of data. He has substantial experience of consultancy, collaboration, and teaching, with excellent written and verbal communication skills, and the ability to explain complicated technical material in simple terms.

Dr Zeynep Suvak

Photograph of Zeynep

Zeynep is an industrial engineer with a background in optimization and operational research. She has worked on developing optimization models and solution approaches for the problems from energy and construction sectors. These include but not limited to scheduling, resource allocation, and various energy planning problems.

She is an experienced programmer in languages C++, C#, Python, GAMS and R. She completed her PhD at Bogazici University in 2019 in network optimization and worked as a postdoctoral researcher at the University of Edinburgh in a field involving both machine learning and optimization before becoming an operational research (OR) consultant. In addition to her career in research and teaching, she has experience as data scientist where she involved in sales forecasting, transport and price optimization projects in retail industry.

Dr Alemseged Weldeyesus

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Alemseged is an operational researcher with a background in the development of new models and efficient methods for large-scale optimization problems, mostly in engineering applications.

Alemseged is an experienced Python and MATLAB user. He has practical experience in building optimization models involving large data sets and in developing efficient optimization algorithms and visualizations.  Alemseged has also substantial academic experience.  Before his current consultancy position, he has worked at the University of Edinburgh from 2016 to 2020 as a postdoctoral research associate.  Prior to that, he was a postdoctoral fellow for two years at the Technical University of Denmark where he also completed his PhD in 2014.