CfS Annual Conference 2023

Javier Escudero is senior lecturer in biomedical signal processing at the Institute for Digital Communications, School of Engineering, University of Edinburgh. His group develops algorithms for the characterisation of physiological time series based on machine learning and on concepts related to complex systems.

Talk title: Extending Entropy Analysis Techniques to Irregularly Sampled Data: From Multivariate Time Series to Graphs Data and Beyond

Miguel Bernabeu is Professor of Computational Medicine at the Usher Institute and Deputy Director at The Bayes Centre, the University’s innovation hub for Data Science and Artificial Intelligence (AI).  His research concerns the development of computational approaches capable of answering open questions in biomedicine and healthcare. He works closely with biologists, clinicians, and industry in problems of high relevance in both basic and clinical research.

Talk title: AI in Health: a Computer Vision perspective

Audrey Repetti is an Assistant Professor at Heriot-Watt University, affiliated with both the school of Mathematical and Computer Sciences, and the school of Engineering and Physical Sciences. She received an MSc degree in mathematics from Paris-Sorbonne University (former Pierre and Marie Curie University) and a PhD degree in computer sciences from Gustave Eiffel University, both in the field of optimisation, in 2011 and 2015, respectively. She was awarded in 2022 a Fellowship from the Royal Society of Edinburgh, for her works on optimisation for data science; is an AE for IEEE SPL; and an elected member of the TC for EURASIP in Theoretical and Methodological Trends in Signal Processing. Her research encompasses optimisation, inverse problems, and deep learning, with applications to computational imaging.

Talk title: A distributed block-coordinate Gibbs sampler for image recovery 

Mike is the principal research data scientist at the Smart Data Foundry, a startup owned by the University of Edinburgh. His team helps researchers and governments access financial data about businesses and citizens for the public good. Mike has worked in the public, private, academic and charity sectors across a wide range of disciplines including: climate, environment, agriculture, social services, and economics.

Talk title:  Financial data, just for finance?

Ava Khamseh leads the Edinburgh Biomedical AI lab. Addressing challenges in modern quantitative biomedicine requires working across different disciplines and bringing in knowledge from various fields. They collaborate closely with experts from experimental biology, computational biology, mathematics, physics and machine learning. Simultaneously creating experimental designs to generate data whilst developing quantitative methods in tandem to derive meaning from the data, drives research & training in our group.

Talk title: Dispensing with unnecessary assumptions in population genetics analysis

Dr Benjamin Bach established and is now co-leading the VisHub data visualization lab (https://vishub.net) together with Uta Hinrichs. Benjamin’s research designs and investigates interactive information visualization interfacesand ways for engaging storytelling to help people explore, communicate, and understand data across media such as screens, mixed and virtual reality, and paper.

Talk title: What, Why, How: Data visualization for Exploring and Communicating Data

Cristina Iannelli is Professor of Education and Social Stratification at the University of Edinburgh. She is a Fellow of the British Academy and the Academy of Social Sciences. Her main research interests are: social inequalities in education, social mobility, youth transitions, cross-country comparative analysis and advanced quantitative research methods.

Talk title: Social inequalities in occupational attainment: using sibling data to estimate the total effect of family of origin and the role of education