Tim CD Lucas

I am a lecturer in the Dept. of Health Sciences at the University of Leicester. Please feel free to email me to discuss stats, modelling, R, job opportunities or anything else. My address is tim.lucas — at — le.ac.uk. Or you can say hello on bluesky @statsforbios.bsky.social.

My interests encompass statistical methods and mathematical models for studying disease. In particular I’m interested in studying methods that account for multiple temporal or spatial scales. For example, disease progression or diagnosis is typically quite a slow process, but we are exposed to environmental factors such as air pollution every second. Depending on our movement patterns, we can have very different exposures from one minute to the next.

I have a continuing interest in infectious disease models and statistical methods for ecology. Recently this has involved developing models of contact tracing to help guide COVID-19 policy. Previously, I worked as a Research Fellow at Imperial College. Before that I worked with Deirdre Hollingsworth and the Malaria Atlas Project at the Big Data Institute, University of Oxford on neglected tropical diseases and malaria.

Current Vacancies/Opportunities

If you are a student looking for opportunities such as masters or PhD projects please email to say hello. There are studentships or pre-doctoral fellowships we could develop a project for.

My belief is that the primary aim in a PhD is simply to be happy and healthy, now and in the future. The secondary aim is to graduate. Gaining skills, doing exciting science and publishing papers typically contribute to the above. I want to be a thoroughly supportive supervisor no matter your strengths, weaknesses and background.

Lab Group

I currently supervise these people in some capacity.

Post Docs

Simon Smart. @smartspuds. A shiny app for disaggregation regression.

Olukemi Olowofoyeku. Developing more predictive disaggregation regression methods. Disease mapping including Lassa Fever.

PhD students

Nidhi Shukla. @nidhienv01. Machine learning and statistical methods for handling resolution mismatch in air pollution. Scholar

Flo Goemans. Using omics data to predict and understand long COVID outcomes.

Enzo Cerullo. @enzo_cerullo. Methods for assessing test accuracy in the absence of a gold standard pdf. Meta-analyses. Scholar

Abeer Al Japany. Machine learning methods for predicting radiotherapy side effects.

Hadiqa Tahir. @Hadiqa_T. Statistical methods for understanding the relationship between human movement, air pollution, green space and health outcomes.

Pre docs

Amber Vayani. NIHR predoctoral fellow. Quantifying the role of air conditioning in protecting against adverse health outcomes in extreme heat.

Lab Alumni

Sylvain Matingou. Statistical methods for combining human movement, air pollution and health data.

Hayley Smith. @96HayleySmith. Combining neural networks and survival models and working out how to fairly compare machine learning and statistical models. Scholar

Hannah Worboys. @HannahWorboys41. Post doc planning evaluation studies for the P-STEP app. PhD work on quality of life.