2023 Best 40-Under-40 MBA Professors: David Stillwell, Cambridge Judge Business School, University of Cambridge

Congrats to David Stillwell of Cambridge Judge Business School, University of Cambridge for being named a 2023 Best 40 Under 40 MBA Professor.

David Stillwell

Cambridge Judge Business School, University of Cambridge

“As a psychometrician who has worked with David in the Psychometrics Centre for the past 2 years, I can attest to his outstanding contributions to the field of psychology, business and beyond. David’s research on social media and big data analysis has shed light on the way people interact with technology and how their behavior can be predicted. David’s ability to use his expertise in psychometrics to tackle pressing real-world problems is remarkable, and his work has already had a significant impact on many areas, including marketing and organisational behaviour.”Dr. Joe Watson

David Stillwell, 37, is a professor of computational social science at Cambridge Judge Business School, University of Cambridge. He is also the academic director of Judge’s Psychometrics Centre.

His research uses big data to understand psychology. He published papers using social media data from millions of consenting individuals to show that the computer can predict a user’s personality as accurately as their spouse can. Follow-up research found that personalizing an advert to the recipient’s psychology is more effective than generic ads.

He has spoken at workshops organized by the European Union Data Protection Supervisor, the European Parliament’s Science and Technology Options Assessment Panel, UK government regulators, and to the Bank of England. His research has also been cited by many governments’ national data protection regulators worldwide.

Stillwell does consultancy on the topics of psychometrics, people analytics, and big data. He has worked on projects with companies including Amazon Payments, Barclays, Hilton Hotels, RBS, Shell, and Ubisoft.


At current institution since what year? 2015

Education: Ph.D. Psychology from the University of Nottingham

List of MBA courses you currently teach: Managing Big Data Analysis elective


I knew I wanted to be a business school professor when… I never planned to be a business school professor – I did all of my studies in a Psychology Department, but life had other plans for me. When an opportunity presented itself to move to Cambridge Judge Business School at Cambridge University, I decided to give it a go, and here I am eight years later.

What are you currently researching and what is the most significant discovery you’ve made from it? My research niche in academia is taking methods from computer science, like machine learning or AI, and applying them to social science problems. In my most well-known research, we used machine learning to show that Facebook Likes can predict sensitive information like personality traits. We published this as a warning, which sadly wasn’t heeded when famously a company called Cambridge Analytica predicted the personality of millions of American voters and used it to target political ads in the 2016 Presidential election.

If I weren’t a business school professor… I’d most likely be crunching numbers as a data scientist.

What do you think makes you stand out as a professor? One of my roles at Cambridge Judge is as Academic Director of its Psychometrics Centre. We’re a small team of 10 who blend academic research with commercial consultancy on psychometric testing. Our consultancy work gives me exposure to working with clients and delivering on commercial projects under pressure like my MBA students do. By leading the research team, I also have experience of the challenges and rewards that managing a team of people involves.

One word that describes my first time teaching: Failure! The first time I taught an MBA class, my average student rating was 2.2/5. That’s an objectively horrific score. The problem wasn’t so much what I was teaching, but that the material was structured erratically and the room we were in was wrong. We were learning about big data in a computer room, which was the right place to do the computer exercises but the wrong place to have discussions and do group work. I spoke to my mentor at Cambridge Judge, Prof Stefan Scholtes, and we came up with a plan for what to do next year. As well as restructuring the material to fit a big-picture strategy, I changed locations so that the first 1.5 hours of each class was in a classroom and then we moved to the computer room for the second half. That physical change of context helps students to mentally change context too so that the classroom and computer activities don’t blend together. I came to realize that in teaching there are lots of subtle techniques or tweaks that can improve or hold back a class, and by constantly experimenting and reflecting on what worked, I have come to enjoy the challenge and art of teaching.

Professor I most admire and why: The professor that I admire and who has had the biggest impact on me is Prof John Rust. He founded the Psychometrics Centre research team that I now lead. While lots of the academy talks about the importance of engaging with industry and doing research that has impact, he just went ahead and did it 30 years ago. John saw the wider potential of the research I was doing into social media data before even those of us who were doing the research did. John has always been very welcoming of academics from around the world, rather than just from Western countries. John invited an unknown academic visitor from China in the mid-2010s who is now one of our key collaborators whom we’re doing super interesting work with. John has repeatedly been a visionary.


What do you enjoy most about teaching business students? Teaching business students is by its nature interdisciplinary. It’s great to work with people from different sectors, different companies, and different countries, and they’re all interested to learn about disparate areas of business from accounting to organizational behavior.

What is most challenging? I teach big data, and in my area, the challenge is the huge range of experience and expertise that students come to my class with. Some students are curious about the mathematics of machine learning algorithms, some students want to learn some coding, whereas other students are more interested in the strategic element. So meeting those different expectations is an ongoing balancing act. I tell my students that the most valuable person in an organization is the person who can bridge the divide between data science and business impact, and that’s the role I try to teach them.

In a word, describe your favorite type of student: The nodder. The student who is engaged in class and expresses it through their body language. They nod when you say something that makes sense, they smile when someone says something amusing, or they frown when you’re being confusing. This type of student is so valuable when teaching as a way to keep the pulse of how the class is following so you can adjust as you go.


Favorite book(s): My favorite book is George Orwell’s Nineteen Eighty-Four. It’s a timeless classic that remains relevant today in my teaching about the uses and abuses of big data. The themes of government surveillance and control are still as thought-provoking as ever, and far more technically plausible now than when first published. It’s a book that makes you think and stays with you long after you’ve finished reading it. 

What is your favorite type of music or artist(s) and why? I’m a night owl so I enjoy listening to music that puts me into the zone while I’m getting things done after midnight (it’s 2.15 am now while I’m responding to these questions). That might be melodic trance music like a mix from Armin van Buuren, minimalist piano music composed by Ludovico Einaudi, or epic film music like Zack Hemsey – “The Way (Instrumental).”


If I had my way, the business school of the future would have much more of this… I think the latest developments in generative AI (large language models like ChatGPT, but also image generation, music generation, and video generation) are going to change education fundamentally. Every learner will be able to converse with the AI as a personalized teacher. It will be able to generate problems unique to each learner. Professors will be able to use AI to understand and better meet the individualized needs of every student in the class. I am already working on integrating these technologies into my classes.


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