Lyn Thomas Impact Medal

The Lyn Thomas Impact Medal is awarded annually for the academic OR research which best demonstrates both novelty and real-world impact, backed up by evidence. Impact can be of many forms including societal, economic, cultural, entertainment, health related, political, quality of life, etc.

The underpinning research should have been undertaken in the previous ten years and the impact itself must be demonstrable within the past three years. All academic researchers who are members of the Society and work at UK universities are eligible to enter.

The deadline for entries is 31 March and should be submitted to [email protected].

2025 Winner

Bahman Rostami-Tabar for ‘Forecasting for Social Good' 

Bahman’s main research interest is the application of forecasting for societal benefit, and he has developed novel methods for settings such as developing countries where data are sparse or of low quality.  These approaches include hybrid models that integrate established, scaled methods with time series forecasting techniques and machine learning, designed specifically to manage the data quality issues common in low-resource settings; hierarchical reconciliation frameworks to ensure forecast consistency across organisational levels, from local health centres to national planners; and models that draw on the contextual knowledge of experienced field practitioners to ensure relevance and operational fit.   

In 2017 Bahman founded the initiative Forecasting for Social Good, which has had significant impact in several African countries.   He worked with USAID in Côte d’Ivoire on global health supply chains, focusing on family planning operations. This work enabled more reliable stock allocations and benefited over one million women through better access to reproductive health services.  He worked with JSI (an American non-profit) in Kenya to develop a hierarchical forecasting method for vaccine needs that aligned estimates across health system levels, from local to national, which improved the forecast accuracy benchmarked against the current approach in practice.  He has also worked on projects in Senegal, Nigeria, and Ethiopia. 

Additionally, he created the Democratising Forecasting initiative to address the analytical capacity gap in low- and lower-middle-income countries. Between Jan. 2018 and Jan. 2025, he designed, prepared, and travelled to each country to deliver 18 in-person, three-day training workshops across 16 countries, training over 316 participants in forecasting and advanced analytics using R. Moreover, through AFRICAST,  a five-day, online training programme focused on tidy forecasting and time series analysis using R and specifically tailored for learners across sub-Saharan Africa, Bahman has trained 206 people in 12 African countries and provides free online training materials, case studies, and code libraries.  He has also written a free, open-access book aimed at practitioners, which to date (according to Google Analytics) has reached over 57,000 unique users across 158 countries.  More recently, and more locally, he has worked on several research projects with the NHS in Wales and has delivered training in R to NHS analysts.