CIS Computing & Information Services Data Science & Business Intelligence
Improving Brown's use of data.

About Us

The CIS Data Science Practice
collaborates with researchers on complex data projects.

Our team of data scientists...

  • help researchers apply new methods and derive insights from their data;
  • have expertise in machine learning, informatics, data exploration and visualization, databases and data management, and software engineering;
  • work with faculty, postdocs, and graduate students in all areas of research, including the physical, life, and social sciences and the humanities;
  • build analytics solutions with Brown's institutional data and support data-driven decision making by senior administrators.


The CIS Business Intelligence Team
provides data and decision support to administrators.

Our team of BI professionals...

  • make data available in a user-friendly environment, using our primary business intelligence tools Cognos Analytics and Tableau;
  • educate and support a wide range of Brown administrators in their use of tools for reporting and analysis;
  • architect and promote new reporting and analytical capabilities;
  • collaborate with data stewards on data management and governance to ensure the ongoing quality, consistency, and availability of institutional data.



Data Science Practice

Fernando Gelin

Data Science Associate

Ashley Lee

Data Science Associate

Ashok Ragavendran

Computational Biologist

Isabel Restrepo

Biomedical Data Scientist

Paul Stey

Lead Data Scientist

Andras Zsom

Lead Data Scientist

Ted Lawless

Research Data Manager

Yiyi Yang

Data Science Associate

John Ucles

Research Data Manager

Andrew Leith

Genomics Data Scientist

Sam Bell

Data Science Associate

August Guang

Genomics Data Scientist

Mary McGrath

Biomedical Informatics Developer/Analyst

Business Intelligence Team

Jennifer Lane

Manager, Business Intelligence

Mike Enos

Business Intelligence Developer

Wendi Lewis

Business Intelligence Analyst

Brook Moles

Business Intelligence Developer

Brian Gauvin

Lead Data Warehouse Developer

Kate Stepanova

Business Intelligence Developer


Through our in-depth collaborations with faculty members and their labs, we frequently co-author publications describing our methods and results:

Berenbaum D, Deighan D, Marlow T, Lee A, Frickel A, Howison M. 2016. Mining Spatio-temporal Data on Industrialization from Historical Registries. arXiv:1612.00992

Chen ES, Melton GB, Howison M, Knoll E, Lee A, Sarkar IN. 2016. Mining and visualizing sequential patterns in the electronic health record: a case study for asthma with and without mental disorders. In AMIA Annu Symp Proc.. (accepted)

Guang A, Zapata F, Howison M, Lawrence CE, Dunn CW. 2016. An Integrated Perspective on Phylogenetic Workflows. Trends in Ecology & Evolution 31(2): 116-126. doi: 10.1016/j.tree.2015.12.007

Zapata F, Goetz F, Smith S, Howison M, et al. 2015. Phylogenomic Analyses Support Traditional Relationships within Cnidaria. PLOS ONE 10(10): e0139068. doi:10.1371/journal.pone.0139068

Zapata F, Wilson NG, Howison M, et al. 2014. Phylogenomic analyses of deep gastropod relationships reject Orthogastropoda. Proc. R. Soc. B 281(1794): 20141739. doi:10.1098/rspb.2014.1739

Dunn CW, Howison M, Zapata F. 2013. Agalma: an automated phylogenomics workflow. BMC Bioinformatics 14(1): 330. doi:10.1186/1471-2105-14-330

Howison M, Sinnott-Armstrong NA, Dunn CW. 2012. BioLite, a lightweight bioinformatics framework with automated tracking of diagnostics and provenance. In Proceedings of the 4th USENIX Workshop on the Theory and Practice of Provenance (TaPP '12), 14-15 June 2012, Boston, MA, USA.