Advising

Let’s work together!

I’ll join Princeton as an assistant professor in Spring 2025 — Let’s work together! If you…

Want to do a PhD, please apply to Princeton’s CS program.
Are in Princeton’s CS PhD program, please reach out by email.
Have a PhD, please see post-doc/fellowship opportunities at CITP.

In general, feel free to email me, and I will do my best to reply!

Advising style

I am hands-on. I try to explicitly set goals and rituals, but adapt my involvement to feedback (implicit and requested) and the current challenges we are facing in the research project. I expect that my students’ interests will shape my lab’s direction.

Examples of projects with master students I advised:

Prevalence and prevention of large language model use in crowd work (under review at CACM; Venia went on to do his doctorate at Princeton);
On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial (informed Anthropic’s model evaluation strategy; This is currently under review at Nature Human Behavior);
Quotatives Indicate Decline in Objectivity in US Political News (published at ICWSM; Tiancheng went on to do his doctorate at Cambridge);

Research flavor

I like doing research that tackles real-world issues and provides actionable insights. Ideally, these insights translate into policy and design changes. This often requires…

Expertise in machine learning. Understanding the nuts and bolts of AI or machine learning models is key. E.g., see this paper to see how even simple collaborative filtering algorithms eluded social scientists for quite a while.
Answering causal questions. This entails using applied causal inference methods and statistical models, designing experiments, and finding “natural experiments” in observational data.
Building infrastructure to collect data and run experiments. E.g., designing bots to audit YouTube or experimental platforms to conduct synchronous experiments.
Working closely with companies and other stakeholders. E.g., in the past, I’ve worked with Meta, Reddit, Microsoft, and Prolific.

Research topics

I am currently interested in three broad, interconnected research topics.

Measuring and modulating the impact of generative AI in society. How will LLM-generated propaganda and sockpuppetry shape people’s opinions? How will Generative AI change crowd work? I believe generative AI will shape the world in the coming years, and I’m interested in research that minimizes the harms and maximizes the benefits of this new technology.¹𝄒²𝄒³
Improving content moderation and algorithms in online platforms. What is the effect of deplatforming influencers from social media? How do we align recommender systems to user values? The way we design and curate content on online platforms is still ill-informed by rigorous academic research. I started to address this gap during my PhD and want to continue doing so as a professor.⁴𝄒⁵𝄒⁶
Using large language models to study human behavior. Large language models allow you to create reasonably good predictive models of human behavior and preference. How can this help the social sciences? This is the direction I’ve explored the least, although it may be the one I’m the most excited about.

Those are things I intend to pursue, but, as I said, I expect the interests of my students will shape the direction of my lab. I’m keen to explore new (related) directions!

Students @ EPFL

2024	Guosheng Feng	MSc	DataBricks
2023	Francesco Salvi	MSc
2023	Paula Rescala	MSc
2023	Veniamin Veselovsky	MSc	Princeton University (PhD)
2022	Maciej Styczen	MSc	Uber
2022	Mateo Echeverry Hoyos	BSc	Microsoft
2022	Tiancheng Hu	MSc	University of Oxford (PhD)
2022	Mihaela Berezantev	MSc	ELCA
2022	Jordi Cluet i Martinell	MSc	Swisscom
2022	Breno Matos	MSc	Data Commons Brazil
2022	Julia Majkowska	MSc	Google
2022	Marie Biolková	MSc	Akina
2022	Francis Murray	MSc	Rolex
2021	Léopaul Boesinger	MSc	Akina
2021	Deniz Ira	MSc	SwissBorg
2021	Marie Reignier-Tayar	MSc	Greenly
2021	Barbara Gomes Ribeiro	BSc	Google
2020	Robin Mamié	MSc	Supreme Court of Switzerland
2020	Stanislas Jouven	MSc	Firmenich
2020	Olivier Lam	MSc	Nestlé
2019	Thomas Spilsbury	MSc	University of Aaalto (PhD)

References

Giuseppe Russo Latona, Manoel Horta Ribeiro, Tim R. Davidson, Veniamin Veselovsky, and Robert West. “The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Rates.” arXiv e-prints (2024): arXiv-2405. (link) ↩
Francesco Salvi, Manoel Horta Ribeiro, Riccardo Gallotti, and Robert West. “On the conversational persuasiveness of large language models: A randomized controlled trial.” arXiv preprint arXiv:2403.14380 (2024). (link) ↩
Veniamin Veselovsky, Manoel Horta Ribeiro, and Robert West. “Artificial artificial artificial intelligence: Crowd workers widely use large language models for text production tasks.” arXiv preprint arXiv:2306.07899 (2023). (link) ↩
Homa Hosseinmardi, Amir Ghasemian, Miguel Rivera-Lanas, Manoel Horta Ribeiro, Robert West, and Duncan J. Watts. “Causally estimating the effect of YouTube’s recommender system using counterfactual bots.” Proceedings of the National Academy of Sciences 121, no. 8 (2024): e2313377121. (link) ↩
Manoel Horta Ribeiro, Homa Hosseinmardi, Robert West, and Duncan J. Watts. “Deplatforming did not decrease Parler users’ activity on fringe social media.” PNAS nexus 2, no. 3 (2023): pgad035. (link) ↩
My reference. ↩