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18 February 2021 | Story ANDRE DAMONS | Photo Supplied
Prof Maxim Finkelstein, distinguished Professor at the Department of Mathematical Statistics and Actuarial Science at the UFS has become the only researcher with an A1-rating in South Africa (awarded by NRF) in Probability, Statistics and Operations Research.

A professor in the Faculty of Natural and Agricultural Sciences at the University of the Free State (UFS) has become the only researcher with an A1-rating in Probability, Statistics and Operations Research in South Africa after being awarded this prestigious rating by the National Research Foundation (NRF).

This is the second time Prof Maxim Finkelstein, the distinguished Professor at the Department of Mathematical Statistics and Actuarial Science in the Faculty of Natural and Agricultural Sciences, has been awarded with an A-rating. The first was in 2015.

The goal is to produce quality research

According to Prof Finkelstein, the rating should not be a goal as such for a researcher but should produce a quality research that is recognised by peers and that, above all, brings a real satisfaction in life. Prof Finkelstein says: “The rating is just a consequence of what one, as a researcher, has achieved in the past eight years and, actually, during the whole professional life as well. South Africa is the only country in the world that is able to perform this rigorous internationally sound rating process for individual researchers. ‘Scientifically large’ countries just cannot do it, technically.”

Prof Finkelstein’s area of expertise is the modelling of random events and quantifying probabilities of their occurrences. He explains: “For instance, in industry, people are interested in probabilities that a machine or process or mission will accomplish its task without failure or accident. In order to assess the probabilities of interest, one must have an adequate mathematical/stochastic model that should be properly developed. 

“Thus, I am developing such models that can be rather advanced because they should take into account numerous factors, e.g., that the object is operating in a random environment, that its structure could change, that there can be human errors affecting the outcome, that an object interacts with other objects, etc. This is usually done in the framework of mathematical reliability theory that considers operation of technical devices.” 

The only A-rating at NAS

“I am quite excited to get the A-rating for the second time, especially because it is the only A-rating in Probability, Statistics and Operations Research in South Africa. It is also the only A-rating at our Faculty of Natural and Agricultural Sciences.

“The fact that it is an A1 and not A2, as previously, does not, in fact, mean too much to me. What matters really is that it is the A-category defined by the reviewers’ opinions that the applicant is a world leader in his discipline,” says Prof Finkelstein.

During his numerous visits as a research professor to the Max Planck Institute of Demographic Research in Germany, he jointly with the colleagues from this institute, were applying the developed stochastic approaches to modelling lifespans of organisms as well. 

One of Prof Finkelstein’s evolving interests is in the area of healthcare engineering when, for instance, monitoring the key health parameters of a patient, some optimal cost-wise decisions can be made on preventive treatments and interventions. 

“I want also to stress that, in general, international collaboration is very important for emerging and established researchers, especially in ‘remote’ South Africa, although nowadays the term ‘remote’ is obviously outdated,” says Prof Finkelstein.

He also collaborates with numerous colleagues around the globe. Apart from the visiting position in the Max Planck Institute he held for many years, Prof Finkelstein regularly visits the ITMO University in St Petersburg, Russia, and is also now establishing a Visiting Professor position at the University of Strathclyde in Glasgow, Scotland.

News Archive

Researcher works on finding practical solutions to plant diseases for farmers
2017-10-03

 Description: Lisa read more Tags: Plant disease, Lisa Ann Rothman, Department of Plant Sciences, 3 Minute Thesis,  

Lisa Ann Rothman, researcher in the Department of
Plant Sciences.
Photo: Supplied

 


Plant disease epidemics have wreaked havoc for many centuries. Notable examples are the devastating Great Famine in Ireland and the Witches of Salem. 

Plant diseases form, due to a reaction to suitable environments, when a susceptible host and viable disease causal organism are present. If the interactions between these three factors are monitored over space and time the outcome has the ability to form a “simplification of reality”. This is more formally known as a plant disease model. Lisa Ann Rothman, a researcher in the Department of Plant Sciences at the University of the Free State (UFS) participated in the Three Minute Thesis competition in which she presented on Using mathematical models to predict plant disease. 

Forecast models provide promise fighting plant diseases
The aim of Lisa’s study is to identify weather and other driving variables that interact with critical host growth stages and pathogens to favour disease incidence and severity, for future development of risk forecasting models. Lisa used the disease, sorghum grain mold, caused by colonisation of Fusarium graminearum, and concomitant mycotoxin production to illustrate the modelling process. 

She said: “Internationally, forecasting models for many plant diseases exist and are applied commercially for important agricultural crops. The application of these models in a South African context has been limited, but provides promise for effective disease intervention technologies.

Contributing to the betterment of society
“My BSc Agric (Plant Pathology) undergraduate degree was completed in combination with Agrometeorology, agricultural weather science. I knew that I wanted to combine my love for weather science with my primary interest, Plant Pathology. 
“My research is built on the statement of Lord Kelvin: ‘To measure is to know and if you cannot measure it, you cannot improve it’. Measuring the changes in plant disease epidemics allows for these models to be developed and ultimately provide practical solutions for our farmers. Plant disease prediction models have the potential ability to reduce the risk for famers, allowing the timing of fungicide applications to be optimised, thus protecting their yields and ultimately their livelihoods. I am continuing my studies in agriculture in the hope of contributing to the betterment of society.” 

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