Tuesday, 1 August 2023 19th International Conference on Applied Statistics 2023 (AS 2023)

Between 24 and 26 September the International Conference on Applied Statistics will take place at UP FAMNIT. 

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ABOUT THE CONFERENCE 

The conference will bring together researchers and experts from all around the world in the field of data analysis, data science and statistics, to present the latest research and exchange knowledge.  

The scientific program at AS 2023 includes invited talks as well as oral and poster presentations of accepted abstracts. The two-day main conference will be preceded by a workshop day.

Conference topics

AS 2023 welcomes abstracts of 300 words for oral or poster presentations on topics related to applied statistics in the broadest sense. These include, but are not limited to:

• Artificial intelligence and machine learning
• Biostatistics
• Data science and data mining
• Econometrics
• High performance computing in statistical applications
• Mathematical statistics
• Measurement
• Modeling and simulation
• Network science, social networks, collective intelligence
• Sampling methods
• Social science methodology
• Training in statistics

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Invited Speakers

Dankmar Böhning​ - University of Southampton

Capture-recapture methods with applications in health and society

Abstract: The talk will focus on how capture-recapture methods based upon uni-list approaches can tackle questions of population size in health and society. Starting with typical count data modelling approaches such as zero-truncation of Poisson, geometric or negative-binomial count densities the talk will continue introducing the more flexible ratio regression approach for capture-recapture applications. Among case studies considered will be the completeness of contact-tracing of Covid-19 in Thailand, the amount of drink-driving in Great Britain and the completeness of a meta-analysis on completed suicide after a specific surgery to reduce obesity.

 

Richard De Veaux​  - Williams College

Data science ethics: Some stories from the trenches

Abstract: The ethical use of data may sound simple, but data can have unintended consequences, sometimes causing great harm. In this talk I will present several real examples of breaches of data ethics, both intentional and unintentional. From these, I hope we can all learn how to think about the impact of data in our own work and arrive at a set of principles that can guide us better in the ethical use of data. 

 

 

Cécile Proust-Lima - University of Bordeaux

Analysis of multivariate longitudinal and survival data: From joint models to random forests

Abstract: Health studies usually involve the collection and analysis of variables repeatedly measured over time. This includes exposures (e.g., treatment, blood pressure, nutrition) and markers of progression (e.g., brain volumes, blood tests, cognitive functioning, tumor size). When interested in modeling how these variables are associated with clinical endpoints such as death in survival models, some statistical challenges arise. > MORE

 

 

 

IMPORTANT DATES

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