Affiliate Research Labs

The Data Science Program is affiliated with a number of faculty-led research labs across a number of different disciplines at William and Mary.  Exceptional students interested in working in one or more of the below labs can apply for a Data Science Fellowship. DSP students are encouraged to reach out to faculty members in labs affiliated with their own interests to get hands-on research experience, or design COLL 400 capstones.  Before contacting labs, it is recommended you take the core (non-elective) Data Science coursework; some labs have further recommendations.  If you are a faculty member and would like to get your lab involved with the DSP, send us an email: datascience@wm.edu.

Lab Name Description Programming Course Recommendations Contact
Social Networks and Political Psychology (SNaPP)

Research topics include (learn more): public opinion, ideology, partisanship, political knowledge, participation, campaigns, the media (including social media), and polarization. 

R is the primary language used in the lab. See here. Jaime Settle
AidData Research and Evaluation (REU)
Quantify the impacts of international aid using geospatial data, econometrics, and machine learning techniques. You will want to be comfortable with Python, R or STATA At least one of: Introduction to GIS, Remote Sensing, Applied Microeconometrics, Algorithms

Dan Runfola (Applied Science)

Ariel BenYishay (Economics)

Carrie Dolan (Kinesiology)

Computational & Experimental Linguistics Lab (CELL) Computational and experimental research on how humans and machines learn, use, and understand language. R and Python

Minimum: LING 220 (Study of Language)

Upper Level: LING 380 (Computational Methods in Language Science), LING/PSYC 370 (Psycholinguistics), LING 304  (Syntax)

Dan Parker

Saha Lab The overarching question that defines the research interests of my laboratory is how cells progressively acquire and maintain their unique identity during early vertebrate embryonic development.  MATLAB and Python are both commonly used.

Margaret Saha

Applied Conservation & Ecological Research (ACER) How spatial and temporal patterns of human stressors and land cover affect biodiversity. ArcGIS and related languages (ArcPy) GIS for Biologists

Matthias Leu

Computational Biology Laboratory (CBL) Mathematical and computational aspects of cell biology and neuroscience: calcium signaling, receptor modeling, neurophysiology. Matlab APSC 351 Cellular Biophysics & Modeling, APSC 350 Computational Neuroscience

Gregory Smith

Zeta Lab We are working on math and technology problems in data science, and building a lot of software related to analyzing and visualizing data problems. C++, Java, and Python CSCI 301, 304, and/or 312

Zhenming Liu