Research Computing

Research at the Tuck School at Dartmouth is supported by a comprehensive ecosystem of high-performance hardware, specialized research software, and a dedicated team of research staff. The Tuck Research Computing (TRC) Team provides specialized assistance in research design, data management, and custom programming. TRC can assist with the following: research design and data analysis, statistical computing, specialized programming, and financial data extractions.

For more details, check out our full list of services! 

Meet the Tuck Research Computing (TRC) Team

Robert (Bob) Burnham

Principal Research Software Engineer, Research Computing

Robert (Bob) Burnham

Principal Research Software Engineer, Research Computing

At Tuck since 1999, Bob came to Tuck originally to build TuckPERC, an open-source platform for hosting financial datasets (CRSP, Compustat, TAQ) on the web, written first in C and later rewritten in C++. Prior to Tuck he worked as a software engineer at Fidelity Investments and has also worked with the US Department of State and as a consultant for USAID and the World Bank. He is an adjunct faculty member teaching the VBA Programming elective. His programming experience spans Python, C, C++, Java, Lisp, Perl, Ruby, and BASIC, as well as higher-level packages including SAS and Matlab. He is also the creator of the Sensitivity Toolkit, a collection of Excel add-ins for sensitivity analysis. Other project experience includes database development, statistical analysis, optimization, simulation, web application development, and web scraping.

Rong Guo

Principal Research Software Engineer, Research Computing

Rong Guo

Principal Research Software Engineer, Research Computing

At Tuck since 2006, Rong holds an M.S. in Economics and worked for six years as a senior analyst in the financial industry prior to joining Tuck. She specializes in managing and cleaning large and complex datasets, including projects involving datasets exceeding 100GB. Her software expertise includes SAS, SQL, SPSS, and Excel. Representative project experience includes constructing panel datasets of UPC-level retail transactions, cleaning and analyzing executive compensation data, factor analysis on large donor datasets, and building consumer migration models from promotion and purchase data.

Deepti Poluru

Senior Research Software Engineer, Research Support

Deepti Poluru

Senior Research Software Engineer, Research Support

At Tuck since 2019, Deepti holds an MS in Computer Science and an MBA, and previously worked as a management consultant at Ernst & Young and Hay Group. She focuses on Python, R, Matlab, and SQL workflows, with particular experience in NLP analysis, fuzzy matching for large datasets, and running computing tasks on the Discovery cluster. Other project work includes regression analysis, converting SPSS workflows to R, developing course materials in Python and R, and quantitative analysis of video content.