Our Team
Co-Directors
Pramit Chaudhuri
Pramit Chaudhuri (Ph.D. Yale) is Associate Professor of Classics at the University of Texas at Austin and co-founder and co-director of the Quantitative Criticism Lab. He specializes in the Latin poetry of the early Roman empire, set within a broader study of classical and early modern epic and tragedy.
Joseph Dexter
Joseph Dexter (Ph.D. Harvard) is a Data Science Fellow at Harvard University and co-founder and co-director of the Quantitative Criticism Lab. A computational biologist by training, he has broad interests across data science and is particularly enthusiastic about research that brings together traditionally quantitative and qualitative disciplines.Principal Collaborators
Patrick Burns
Patrick J. Burns (Ph.D. Fordham) is the ACLS Postdoctoral Fellow for the Quantitative Criticism Lab.
Tathagata Dasgupta
Tathagata Dasgupta received his Ph.D. from the University of Cambridge as a member of Trinity College, where his research focused on string theory. More recently, his work at Harvard University involved various inter-disciplinary combinations of computational, mathematical projects in systems biology and the clinical and biomedical sciences. His interests lie in the interplay between modern machine learning theory and non-equilibrium statistical physics for building novel algorithms to describe various complex phenomena across disciplines.
Ayelet Haimson Lushkov
Ayelet Haimson Lushkov (Ph.D. Yale) is Associate Professor of Classics at the University of Texas at Austin.
M. Ski Krieger
M. Ski Krieger completed his undergraduate training in Physics and Classics at the University of Chicago, which is where he acquired a love of philology. After a brief stint in Crimea working for the Peace Corps he returned and did his doctoral work in theoretical soft-matter physics at Brown University.
Nilesh Tripuraneni
Nilesh Tripuraneni received his B.A. from Harvard, where he studied physics, and an M.Phil in Information Engineering from the University of Cambridge, where he focused on probabilistic machine learning.Research Associates
Alvin Deng
Alvin is a research engineer at Drawbridge. He graduated from the University of Texas at Austin in 2017 with a B.S. in Computer Science.
Jeffrey Flynt
Jeffrey Flynt has a strong background in UI/UX Design and programming in JavaScript, Python, MongoDB & MySQL.
Tim Gianitsos
Tim Gianitsos is a software development engineer at Amazon. He earned his B.S. in Computer Science from The University of Texas at Austin.
Sally Heiter
Sally Heiter (B.S., Rutgers) has a background in design (landscape architecture and graphic design), music (classical voice, choral conducting, composition), copyediting (scientific journals and textbooks), and marketing (copy, photography and graphics).
James Patterson
James F. Patterson (Ph.D. UTexas) is a Lecturer in Classics at the University of Texas at Austin.
Eric Rincon
Eric is a student at UT Austin studying computer science and math. He is interested on working on applying machine learning to cross disciplinary research, and on problems involving natural language and computer vision.
Ariane Schwartz
Ariane Schwartz (Ph.D. Harvard) is Assistant Editor, I Tatti Renaissance Library. She specializes in Latin literature set within a wider study of cultural and intellectual history, the classical tradition, and the history of reading and sociology of texts.Graduate Students
Undergraduate Students
Aleksandr Fedchin
Aleksandr Fedchin is an undergraduate student at Bard College majoring in Classics and Computer Science.
Catherine Goode
Catherine Goode is an undergraduate student at the University of Texas at Austin.
Teddy Katz
Teddy Katz is an undergraduate student at MIT, majoring in Electrical Engineering and Computer Science.
Michelle Yakubek
Michelle Yakubek is a freshman at MIT planning to major in Computer Science and Engineering and minor in Brain and Cognitive Sciences.High School Students
Bihan Dasgupta
Bihan Dasgupta is a senior at Brookline High School. She is working with QCL on a quantitative, corpus-based study of race and racism in the reception of the classics.
Krithika Iyer
Krithika Iyer is a senior at the IB World School at Plano East Senior High School. She is an active mathematics and cognitive science researcher who has worked on Bayesian decision support systems for mammograms, analyzing cancer mutations, and Bayesian knowledge traces for mind theoretic applications.
Daniel Michael
Daniel Michael is a senior at Wooster School in Danbury, CT. He is an active computational linguistics and cognitive science researcher who has worked for the past two years on developing machine learning and natural language processing-based diagnostic systems for neurodegenerative diseases.
Prathik Naidu
Prathik Naidu is a senior at Thomas Jefferson High School for Science and Technology. He is an active computational biology researcher who has worked for the past three years in the fields of protein modelling, machine learning, and cancer genomics (Johns Hopkins University and The Broad Institute of MIT/Harvard).Advisory Board
Joe Farrell
Joseph Farrell is Professor of Classical Studies and Mark K. and Esther W. Watkins Professor in the Humanities at the University of Pennsylvania.
Stephen Hinds
Stephen Hinds is Professor of Classics at the University of Washington, Seattle.
Dan Rockmore
Daniel Rockmore is the Director of the Neukom Institute, the William H. Neukom 1964 Distinguished Professor of Computational Science, and Professor of Mathematics at Dartmouth College.Alumni
Jorge Bonilla Lopez
Jorge Bonilla (A.B. Dartmouth) is a J.D. candidate at Yale Law School. His involvement with the project grew out of coursework and a research assistantship with Pramit Chaudhuri at Dartmouth College.
James Brofos
James is interested broadly in statistical theory, particularly Bayesian nonparametrics and graphical models.
Caleb Caldwell
Caleb Caldwell is an undergraduate student at Dartmouth College, majoring in Classical Languages and Literatures.
Ajay Kannan
Ajay Kannan (B.A. Dartmouth) is a software engineer at Baidu. He is interested in computational problems, especially the intersection of computing and language.