Adam Hornsby

data & cognitive science

I'm a Data and Cognitive Scientist, primarily interested in machine learning and human cognition.

My part-time Cognitive Science PhD at UCL explored memory-based decision making, human memory and their interaction with recommender systems. Read this BBC article for an introduction to my academic research.

Elsewhere, I develop and deploy machine learning models at scale. I'm particularly interested in model deployment (MLOps), recommender systems and economic decision-making

In my spare time, I sometimes build side projects, like Sweepstakes League.

If you would like to get in touch, please email me.

Papers

[ Thesis ] Hornsby, A.N. (2022). Memory-based Preferential Choice in Large Option Spaces. Doctoral Thesis, UCL.

[ Article, Code ] Hornsby, A.N. & Love, B.C. (2022). Sequential consumer choice as multi-cued retrieval. Science Advances. https://doi.org/10.1126/sciadv.abl9754

[ Article, Code ] Hornsby, A.N. & Love, B.C. (2020). How Decisions and the Desire for Coherency Shape Subjective Preferences Over Time. Cognition. https://doi.org/10.1016/j.cognition.2020.104244

[ Abstract ] Hornsby, A.N. & Love, B.C. (2019). Inferring Value by Coherency Maximization of Choices and Preferences. Reinforcement Learning and Decision Making. Montreal, 2019. http://rldm.org/papers/abstracts.pdf

[ Article, Code ] Hornsby, A.N., Evans, T., Riefer, P. S., Prior, R & Love, B.C. (2019). Conceptual Organization is Revealed by Consumer Activity Patterns. Computational Brain and Behavior. https://doi.org/10.1007/s42113-019-00064-9

🥇 Winner of the Computational Brain & Behavior Outstanding Paper Award 2020


[ Link ] Hornsby, A.N. & Love, B.C. (2014). Improved Classification of Mammograms Following Idealized Training. Journal of Applied Research in Memory and Cognition. 3, 2, 72-76. https://doi.org/10.1016/j.jarmac.2014.04.009

Keynotes and blogs

[ Blog ] How your brain decides what you buy @ Medium. (19/11/22)

[ Slides ] How I became a Data Analyst... And then a Data Scientist... And then a PhD student @ UCL Career Talks, London. (24/05/19)

[ Slides ] Conceptual Organization in the Supermarket @ Data Science Festival (Lightning Talks), Facebook, London. (22/11/18)

Understanding Customers Better Through Neural Network Embeddings @ DataMashup, London. (21/06/18)

[ Blog ] Solving the Problem of Product Similarity with Data Science, dunnhumby.com. (03/05/18)

[ YouTube, Abstract ] Understanding Customers Better Through Neural Network Embeddings @ Data Science Festival, London. (21/04/18)

[ Abstract ] Understanding Customers Better Through Neural Network Embeddings @ RE.WORK Deep Learning in Retail Summit, London. (15/03/18)

What is Customer Data Science? @ University of Edinburgh, CDT Data Science Day. (14/10/15)

Awards

[ Article ] Industrial Fellowship, 1851 Royal Commission (2018)

[ Article ] DataIQ, New Talent Award (2018)

[ Profile ] Kaggle, Competitions Master (2016)

UCL, WHR Rivers Prize (i.e. 1st place undergraduate in Psychology) (2013)

UCL, Dean's List (2013)

Taught courses

Development Standards for Data Scientists @ dunnhumby (Co-created and taught) (2019-Present)

Applied Machine Learning @ dunnhumby (Created and taught) (2017-Present)

Work & education

Research Data Science Specialist (Lead) @ dunnhumby. (2020-)

Senior Research Data Scientist @ dunnhumby. (2013-2020)

Experimental Psychology, PhD (part-time) @ UCL (supervised by Professor Brad Love). (2016-2022)

Psychology, BSc (Hons) @ UCL, 1st (dissertation supervised by Professor Brad Love). (2010-2013)

Side projects

[ Sweepstakes League ] A funner way to play World Cup sweepstakes. 2026.

[ Code ] Experimenting with batch reinforcement learning. ~2018.

[ Code ] MNIST pixel in-painting (experimenting with RNNs in TensorFlow). ~2017

[ Viz, Code ] Visualisations of taxi journeys in Porto (experimenting with d3). ~2015

[ Homepage ] Fist year revision notes from my Psychology BSc at UCL. ~2011