I’m a Tenure Track Assistant Professor in the Department of Computer Science at Aalborg University Copenhagen from Feb 1, 2026. My research centers around reliable and sustainable AI. Core to my work is understanding when and how can NLP systems make the world’s information reliable and accessible, while mitigating the environmental and social risks these systems can bring. This includes the factuality, faithfulness, and diversity of information these systems produce, as well as the efficiency with which they can produce them. The methods I use come from machine learning and natural language processing.
Previously I was a Danish Data Science Academy postdoctoral fellow at the University of Copenhagen, was a visitor to the BlaBlaBlab at the University of Michigan, and was a postdoc in the Saints Lab working on sustainable AI. I did my PhD at the University of Copenhagen in the CopeNLU lab where I worked on automated fact checking, automatic understanding and analysis of science communication, and domain adaptation. I received my master’s degree from University of California, San Diego, and have worked at IBM Research and the Allen Institute for Artificial Intelligence on the Semantic Scholar project. I also write sometimes on substack. Outside of science I like making music and playing table top role-playing games and rhythm games.
Open Positions
Prospective lab members (PhD students and Postdocs) should fill out the following form to express their interest in working with me: Interest form
- DDSA Open PhD Fellowship 2026 (deadline: March 4, 2026): Open PhD fellowships on any topic relevant to the lab
- DARA Open PhD Fellowship Winter 2026 (deadline: February 20, 2026): Open PhD fellowships on any topic relevant to the lab
Recent News
(01/09/2025) I’ll be starting as a Tenure Track Assistant Professor at Aalborg University Copenhagen from Februrary 2026!
(20/08/2025) Our paper “Unstructured Evidence Attribution for Long Context Query Focused Summarization” was accepted to EMNLP 2025 (Main)!
(21/07/2025) Co-led the tutorial Addressing AI Driven Misinformation at IC2S2 2025 in Norreköping
(23/06/2025) Gave a keynote at the ICWSM workshop on Misinformation titled The Many Faces of Science Misinformation
(23/06/2025) Co-led the tutorial Addressing AI Driven Misinformation at ICWSM 2025
(01/06/2025) I was awarded a 1.7M DKK Carlsberg Internationalization Postdoctoral Fellowship!
(01/05/2025) Our paper “Efficiency and Effectiveness of LLM-Based Summarization of Evidence in Crowdsourced Fact-Checking was accepted to SIGIR!
(25/04/2025) Gave an invited talk at the Pioneer Center for AI in Copenhagen titled Revealing Political Opinions in Large Language Models
(07/04/2025) Gave a research seminar at University of Minnesota titled Socially Sustainable NLP
Featured Publications
Unstructured Evidence Attribution for Long Context Query Focused Summarization
Dustin Wright, Zain Muhammad Mujahid, Lu Wang, Isabelle Augenstein, David Jurgens
Published in EMNLP, 2025
We propose the task of unstructured evidence attribution for long context query focused summarization and generate a synthetic dataset (SUnsET) to improve model performance on it.
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Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI
Dustin Wright, Christian Igel, Gabrielle Samuel, and Raghavendra Selvan
Published in Communications of the ACM, 2025
We present a perspective on why efficiency will not make AI sustainable and propose systems thinking as a paradigm for the AI community to adopt.
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LLM Tropes: Revealing Fine-Grained Values and Opinions in Large Language Models
Dustin Wright*, Arnav Arora*, Nadav Borenstein, Shrishti Yadav, Serge Belongie, and Isabelle Augenstein
Published in EMNLP Findings, 2024
We generate 156,000 responses to 62 political propositions across 6 language models and demonstrate systematic biases in their stances and plain-text responses.
Download here