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Neukom Fellows '18 Announced!

The Neukom Institute for Computational Science at Dartmouth College is pleased to announce the incoming class of Neukom Postdoctoral Fellows. The Neukom Fellows Program launched in 2012. Fellows have three-year appointments and for their interdisciplinary work which has a computational theme, are co-sponsored and mentored by faculty in at least two departments or programs. Fellows teach one course in each year of their residency. The 2018 Neukom Fellows with their Ph.D. granting institutions and departmental affiliations are given below, along with descriptions from the Fellows of their research plans: 


Brinker Ferguson 
Anthropology and Computer Science;
Mentors -  Sienna Craig, John Watanabe, and Hany Farid
(Ph.D., expected 2018)

brinker ferguson

Brinker’s research lies at the intersection of digital heritage, computational photography, and indigenous agency. Her dissertation project focused on the 3D documentation of a Maori meetinghouse, currently at the Museum of New Zealand Te Papa. Her goal as a Neukom Fellow will be to continue building upon this research and develop software tools that can help to quantifiably track and document change to surface geometry of objects overtime to hopefully catch deterioration issues earlier and more effectively. Brinker completed her Ph.D. at UCSC in the History of Art and Visual Studies department and holds a MA from Tufts University with a focus in art and technology. In addition to researching computational photography and heritage studies in her Ph.D., she has also worked in the museum/heritage conservation and digital media fields. Most recently she was a digital production manager at a non-profit that digitally documents at-risk world heritage sites with partners such as UNESCO, World Monuments Fund and the National Parks Service. She is also professionally certified in several types of conservation scientific imaging techniques such as photogrammetry, laser scanning, structured light, and reflectance transformation imaging.


Ethan Coffel
Geography and Earth Sciences;
Mentors- Justin Mankin, Jonathan Winter, and Erich Osterberg
(Ph.D. expected 2018)

ethan coffel

Ethan studies how climate change is affecting extreme weather, and what impacts these changes will have on human societies and natural ecosystems. His tools are climate models, which enable investigation of the behavior of the climate system both in the past and the future. He strives to understand the physical mechanisms driving changes in the climate, and to present climate information and its uncertainty clearly to facilitate adaptation planning. He has a PhD from Columbia University, where he studied extreme heat and its impacts on human health and infrastructure. As a Neukom Fellow, he will develop methods to analyze how increasingly frequent hot and dry conditions will affect global agriculture.


Joseph Dexter 
Comparative Literature, Biological Sciences, Computer Science and Classics;
Mentors - Michelle Warren, Mark McPeek, Saeed Hassanpour and Margaret Graver

(PhD., expected 2018)

joseph dexter

Joseph has broad research interests that span both the humanities and the natural sciences. His main interests in computational biology are the development of mathematical models that capture the collective, systems-level properties of metabolic and signaling networks, and predictive analytics for high-dimensional clinical data. Dexter’s humanistic research focuses on quantitative literary criticism, especially as applied to classics and the profound influence of Greek and Latin authors on subsequent culture. He is a Ph.D. candidate in the Department of Systems Biology at Harvard Medical School and co-founder and co-director with Pramit Chaudhuri of the Quantitative Criticism Lab. At the Quantitative Criticism Lab he has been working on diverse problems at the intersection of literature, computation, and biology. Particular interests of the group include the development of enhanced computational methods to support literary criticism and intertextual profiling (often drawing on techniques from bioinformatics), elucidation of authorial, generic, and temporal stylistic signatures using machine learning, and cultural evolutionary studies of literature. 






Last Updated: 2/27/18