Dr Robert E. Blackwell

Data Scientist and Research Software Engineer.

Introduction

Rob is a Senior Research Associate, Foundation Models, at the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.

Publications

Barry, J. et al., 2025 (in press). Avoiding Confusion: Modelling Image Identification Surveys with Classification Errors. Methods in Ecology and Evolution.

Pitois, S. G., Blackwell R. E., Close H., Eftekhari N., Giering S. L. C., Masoudi M., Payne E., Ribeiro J., Scott J., 2025. RAPID: real-time automated plankton identification dashboard using Edge AI at sea. Frontiers in Marine Science 10.3389/fmars.2024.1513463.

Gillson, J. P., Blackwell, R. E., Gregory, S. D., Marsh, J. E., Bašić, T., Elliott, S. A. M., King, R. A., Maxwell, D. L., Riley, W. D., Stevens, J. R., Walker, A. M., & Lauridsen, R. B., 2025. Do the biological characteristics of trout (Salmo trutta) smolts influence their spring migration timing and maiden marine sojourn duration? Journal of Fish Biology, 1–17. 10.1111/jfb.16040.

Cohn, A.G. and Blackwell, R.E., 2024. Can Large Language Models Reason about the Region Connection Calculus? arXiv preprint arXiv:2411.19589.

Eftekhari, N., Pitois S. G., Masoudi, M., Blackwell, R. E., Scott, J., Giering, S. L. C., 2024 (in press). Improving in situ real-time classification of long-tail marine plankton images for ecosystem studies, ECCV, CV4E Workshop.

Blackwell, R.E., Barry, J. and Cohn, A.G., 2024. Towards Reproducible LLM Evaluation: Quantifying Uncertainty in LLM Benchmark Scores. arXiv preprint arXiv:2410.03492.

Anthony G Cohn and Robert E Blackwell. Evaluating the Ability of Large Language Models to Reason About Cardinal Directions (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 28:1-28:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024). (https://doi.org/10.4230/LIPIcs.COSIT.2024.28, Supplementary data).

Alan Turing Institute Data Study Group Final Report: Centre for Environment, Fisheries and Aquaculture Science Automated identification of sea pens using OpenCV and machine learning.

Alan Turing Institute Data Study Group Final Report: Centre for Environment, Fisheries and Aquaculture Science Plankton image classification.

Blackwell, R.E., 2020. Real-time reporting of marine ecosystem metrics from active acoustic sensors. University of East Anglia PhD thesis.

Blackwell, R.E., Harvey, R., Queste, B.Y. and Fielding, S., 2019. Colour maps for fisheries acoustic echograms. ICES Journal of Marine Science. (Supplementary software and data.).

Blackwell, R., Harvey, R., Queste, B. and Fielding, S., 2019. Aliased seabed detection in fisheries acoustic data. arXiv preprint arXiv:1904.10736. (Supplementary software.).

Blackwell, R., 2016. Can satellite synthetic aperture radar be used to detect and classify offshore installations?. Cranfield University MSc thesis.

Albakour, M. D., Blackwell, R.E., Kruschwitz, U., Lucas, S., 2009. Managing Collaboration Projects using Semantic Email Search. SemSearch 2009, Madrid, Spain.

Talks

Scientific Computing in the Southern Ocean, invited talk at dev://east 2018.

Podcasts

The Alan Turing Institute Podcast. Turing deployment at sea: identifying plankton in real time.

Articles

Open minds: How open-source tools are broadening the horizons for data science.

Revealing hidden details of the ocean floor.

Family history

My grandfather
Ordinary Telegrapher AER Rowe
World Jamboree 1929

Contact

You can reach him via Email, Github, Twitter/X (DEACTIVATED), Bluesky, LinkedIn,