Curriculum vitae

James Tripp’s work, skills, teaching, awards and publications.

James Tripp

Research Software Engineer · University of Birmingham

I’m a cognitive scientist and research software engineer. I build software and data tools, support research teams, and have led technical work in universities and government.

James.Tripp@outlook.com · LinkedIn · GitHub

Skills

I lead teams, work with stakeholders and use agile methods. I build tools in R, Python and PHP. My data science work includes statistics, machine learning, generative AI and geospatial analysis.

Experience

University of Birmingham

Research Software Engineer · Birmingham, UK · September 2026–present

I help academics solve technical problems, analyse data and teach computing skills as part of the central Research Software Group. I use R, Python and Julia.

Government Internal Audit Agency

Data Analytics Specialist (Grade 7) · London, UK · October 2023–September 2026

I managed and worked with senior leaders to improve government audits. I planned and delivered analysis, wrote reports and built tools. Our audits covered financial models, HR, risk, counter-fraud and other government services.

Highlights:

Built online tools for business processes including LLM, agentic workflows, and typical data science methods (Shiny, Django)
Independently checked large datasets used to make decisions affecting millions of people.

Information and Digital Group, University of Warwick

Senior Research Software Engineer · Coventry, UK · October 2021–October 2023

I worked in a central team that supported researchers and technical staff across the University.

Helped researchers document data, use software containers, publish code, review changes and automate tests and releases.
Built research software, including tools to train machine-learning models and websites using Omeka S.
Worked with the Centre for Digital Inquiry to help humanities researchers use digital methods, machine learning and data analysis.

Centre for Interdisciplinary Methodologies, University of Warwick

Senior Academic Technologist · Coventry, UK · June 2019–October 2021

Led the Academic Technology team.
Helped plan the Centre’s technical work.
Helped write and deliver research grants.

Centre for Interdisciplinary Methodologies, University of Warwick

Academic Technologist · Coventry, UK · December 2015–June 2019

I joined a growing centre to build software and research systems, and to teach workshops.

Worked with researchers in ecology, computing, sociology, media studies, anthropology and philosophy.
Designed and taught hundreds of hours of workshops and labs in machine learning, statistics and network analysis.
Built and managed Linux servers for research and teaching.
Built software for data analysis and visualisation.

Department of Psychology, University of Warwick

Post-Doctoral Research Fellow · Coventry, UK · October 2013–September 2016

I worked with Professors Adam Sanborn and Neil Stewart to study how people combine information.

Designed, programmed and ran psychology experiments.
Reviewed research and developed new hypotheses.
Tested hypotheses using Bayesian and other statistical methods.

Education

University of Warwick

Ph.D. in Psychology · 2013

Compared cognitive models using maximum-likelihood and Bayesian methods.
Designed, programmed and ran psychology experiments.
Taught statistics and programming to postgraduate and undergraduate students.

University of Warwick

B.Sc. (Hons) in Psychology · 2010

Awards and grants

Walkability Perception and its Relations to Scenery Elements and Socio-Demographics (University of Warwick) · Co-Investigator · £5K · 2021
Shaping 21st Century AI: Controversy and Closure in Research, Policy and Media (ORA, ESRC) · Research Software Engineer · €1.7M · 2021
COVID and the Social Life of Testing (University of Warwick) · Collaborator · £5K · 2020
What Aren’t You Seeing? (Alan Turing Institute) · Co-Investigator · £305K · 2019
Visual Diagnostics for Markov Chain Monte Carlo – Backfillz.R (Alan Turing Institute) · Co-Investigator · £53K · 2018

Teaching

IM939: Data Science Across Disciplines · 2020–June 2021
Designed and taught practical classes and supported student projects. Topics included Python, data cleaning, visualisation, dimension reduction and model comparison.
IM931: Interdisciplinary Approaches to Machine Learning · 2018–2021
Wrote and taught practical classes using Keras and TensorFlow. Supported projects in Python and R.
IM921: Visualisation · 2017–2021
Co-designed and taught practical classes on visualisation in Python and R. Led discussions about tools and methods.
QS903: Advanced Quantitative Research · 2017–2019
Taught statistics workshops, including generalised linear and hierarchical models. Supervised quantitative dissertations.
IM913: Spatial Methods and Practice in Urban Science · 2016–2021
Taught mapping and spatial analysis using QGIS, ArcGIS, GeoDa, Python and R.
IM906: Dissertation · 2015–2021
Supervised dissertations using mapping, web scraping, text analysis and computer vision.
QSTEP Masterclass: Social Media Analysis · 2019–2021
Designed and taught the course; social media analysis course materials.
QSTEP Masterclass: SQL · 2020–2021
Designed and taught the course; SQL course materials.
IM904: Digital Objects, Digital Methods · 2015–2021
Created course materials on social media analysis, search queries and digital research.
IM902: Approaches to the Digital · 2015–2021
Designed practical classes that led to critical web art projects.
IM920: Digital Sociology · 2016–2018.
PS923: Methods and Analysis in Behavioral Science · 2012–2013
Led classes on fitting models of behaviour.
PS113: Statistical Methods in Psychology · 2010–2013
Led practical classes in introductory statistics.

Publications and presentations

Marres, N., Castelle, M., Gobbo, B., Poletti, C. & Tripp, J. (2024). AI as super-controversy: Eliciting AI and society controversies with an extended expert community in the UK. Big Data & Society, 11(2).
Marres, N., Colombo, G., Bounegru, L., Gray, J., Gerlitz, C. & Tripp, J. (2022). Testing and not testing for coronavirus on Twitter: Surfacing testing situations across scales with interpretative methods. Social Media + Society, 9(3).
Cámara-Menoyo, C., Cagatay, T. & Tripp, J. (2022). Quarto: One library to rule them all? RSE Conference 2022 workshop.
Tripp, J. (2022). Docker and R? Warwick R User Group (WRUG).
Cagatay, T., Sondag, M., Neil, G. & Tripp, J. (2022). Should we keep it real? A crowdsourcing study on realistic analogies in visualisations for communicating disease spread. IEEE VIS 2022 (submitted).
Sanborn, A. N., Noguchi, T., Tripp, J. & Stewart, N. (2020). A dilution effect without dilution: When missing evidence, not non-diagnostic evidence, is judged inaccurately. Cognition, 196, 104110 (project page).
Tripp, J. & Brown, G. D. (2016). Being paid relatively well most of the time: Negatively skewed payments are more satisfying. Memory & Cognition, 44(6), 966–973 (project page).

References

References are available on request.