Biography
I earned my PhD from the University of Cambridge, where I developed novel approaches to dental phenotype classification and analysis for quantifying and classifying human population structures. Following my PhD, I completed a joint postdoctoral fellowship at The Alan Turing Institute and the University of Cambridge as part of Professor Robert Foley’s Palaeoanalytics project, where I developed machine learning and computer vision software for the classification and quantification lithic technologies. I have also served as Associate Editor of PLOS ONE where I helped launch PLOS’ policies on inclusion in global research, and as Senior Data Scientist at Digital Science’s Dimensions database — the world's most advanced academic database.
Research
Broadly speaking, my research interests are in Lower Palaeolithic tool technologies, the evolutionary origins of modern human and their diversity, and the application of novel computational methods to human evolutionary studies.
Key Publications
Gellis JJ and Foley RA, 2023 Hominin Evolution. Oxford Handbook of Archaeological Sciences. DOI:10.1002/9781119592112
Gellis JJ, Rangel-Smith C, and Foley RA, 2022 PyLithics – An open-source software package for lithic analysis. Journal of Open Source Software, 7 (69) https://doi.org/10.21105/JOSS.03738
Gellis JJ, Rangel-Smith C, and Foley RA, 2022 PyLithics – An open source software package for lithic analysis (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.5898149 |
Gellis JJ and Foley RA, 2021 (Journal of Anatomy) Patterns of variation in canal and root number in human post-canine teeth. doi: https://doi.org/10.1101/2022.02.01.478656
Gellis JJ and Foley RA, 2021 A novel system for determining tooth-root phenotypes. PLOS ONE, 16 (11) https://doi.org/10.1371/journal.pone.0251953
Teaching and Supervisions
Previous teaching experience:
• Humans in a Biological Perspective (B1),
• Human Evolution (and Palaeolithic Archaeology (B3/G03)
• Major Topics in Human Evolution (B5)
Other Professional Activities
University of Cambridge Data Champion