Jessica is studying part-time for a DPhil in Social Data Science. Her research lies at the intersection of Natural Language Processing (NLP), Scientific AI, and Metascience. Through her project Flowmetrics, she proposes a new generation of research metrics that conceptualise societal impact as a dynamic semantic flow—traced and modelled using large language models and knowledge graphs.
Flowmetrics builds on the lineage of bibliometrics, scientometrics, webometrics, and altmetrics, but for the first time introduces AI-driven techniques to infer how research disseminates, engages audiences, and produces real-world outcomes. Using NLP methods and structured ontologies, the project extracts and classifies signals of impact across platforms and represents them as evolving trajectories within a knowledge graph.
Alongside her research, Jessica works full-time for Springer Nature as a Lead Data Scientist, where she develops machine learning systems for peer review, research integrity, and editorial decision support. She has also worked across a range of industries in data science roles and holds an MSc in Computer Science with a research focus on Machine Learning and NLP.
Natural Language Processing; Semantic Modelling; Scientific AI; Knowledge Graphs; Research Impact; Language Representation; Research Evaluation; Metascience; Responsible AI.
Associate Professor, Senior Research Fellow
Dr Scott A. Hale is an Associate Professor, Senior Research Fellow, and Turing Fellow. He develops and applies computer science techniques to the social sciences focusing on increasing equitable access to quality information.
Departmental Research Lecturer
Adam Mahdi’s research focuses on digital health and application of machine learning in social sciences. He is the director of the UKRI-funded OxCOVID19 Project and a fellow at Wolfson College, University of Oxford.
