Brandeis Marshall

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Brandeis Marshall
Dr. Brandeis Marshall at the National Library of Medicine.jpg
ResidenceAtlanta, Georgia
Alma mater
Known forBroadening participation in data science
Scientific career
Fields
Institutions
Websitebrandeismarshall.com Edit this at Wikidata

Brandeis Marshall is an American data scientist and Full Professor of Computer Science at Spelman College, where she is the former Chair of the Department of Computer and Information Sciences. Starting in September 2019, Marshall is a faculty associate at Berkman Klein Center for Internet & Society at Harvard University. She has also worked to broaden participation in the field of data science to increase representation of underrepresented minorities.

Education[edit]

Marshall received her bachelor's degree in Science in computer science with a minor in mathematics from the University of Rochester in 2000. She then received her master's degree and Ph.D. from Rensselaer Polytechnic Institute in Computer Science in 2007.[1]

Research & Career[edit]

In 2008, Marshall became an Assistant Professor of Computer and Information Technology in Data Management at Purdue University's College of Technology.[2] She joined the faculty at Spelman College in 2014 as an Associate Professor of Computer Science in the Division of Natural Sciences and Mathematics and became Chair of the Computer and Information Sciences department in 2016.[1] At Spelman, she is the Director of the Data Analytics and Exploration (da+e) Laboratory, which centers on more effectively characterizing complex networks of data to generate useful knowledge.[1] Her research focuses on business intelligence and data analytics, social media, and cybersecurity.

#BlackTwitter Project[edit]

One of Marshall's research projects centers on the use of social media, and Twitter in particular, for advancing social movements across the black community through the use of the hashtag #BlackTwitter.[3] Her team works with Twitter's application programming interface (API) to gather, analyze, and visualize trends in Twitter data to answer questions like who makes up Black Twitter, who are the influencers within the community, and what issues and topics are they responding to as a community. The project also took the form of a course for Spelman College's Interdisciplinary Big Questions Colloquia, exposing students to principles of data science through by collecting, storing, and analyzing social media data related to the #BlackGirlMagic hashtag.[4] Analysis of the efficacy of the course itself was presented at the Institute of Electrical and Electronics Engineers' Frontiers in Education Conference as a way to teach data science concepts in a culturally relevant framework, since the course also wove in themes of black girlhood alongside computational approaches to data analysis.[5]

Business Intelligence[edit]

Marshall has also contributed research to business intelligence, working to organize, integrate, represent, and analyze a diverse array of data to enable businesses to glean more knowledge and keep pace with the increasing rate of data generation. She has worked on a broad range of problems—from recommending more refined algorithms for music recommendations to designing cost-effective cybersecurity security measures to harnessing the power of eye tracking to better design products for consumers.[6][7][8]

Broadening Participation in Data Science[edit]

In addition to her research interests, Marshall is involved in a number of efforts to increase representation of underrepresented groups in data science and increase data readiness across the workforce.[9] She is the Principal Investigator (PI) of the Data Science eXtension (DSX) program, which is funded by a National Science Foundation grant.[10][11] The program is an effort to train faculty at Spelman College and Morehouse College—both historically black colleges and universities (HBCUs) in Atlanta—on how they can infuse data science and analytics into their curricula. DSX seeks to highlight how data science connects to multiple disciplines, while increasing awareness of opportunities in data science to a student body that is currently underrepresented in the field.[12][4] The project was informed by a 2016 NSF-funded workshop on "Planning a Dual Institution Research Center in Socially Relevant Computing."[13]

Prior to the launch of DSX, Marshall was involved in similar programs geared at broadening participation of underrepresented groups. She was the co-PI of the Broadening Participation in Data Mining Workshop, which was first run in conjunction with the 2012 Society for Industrial and Applied Mathematics International Conference on Data Mining.[14] She also served as the PI for the Computer Science for All Workshop in Atlanta, which was part of a larger national effort orchestrated by the Office of Science and Technology Policy—and led by the NSF and United States Department of Education—under President Barack Obama to build capacity in computer science across the country.[15]

Marshall has also lent her expertise to furthering data science training at the undergraduate level, serving on the National Academy of Sciences' 2018 Roundtable on Data Science Postsecondary Education.[16]

References[edit]

  1. ^ a b c "CIS Faculty | Spelman College". www.spelman.edu. Retrieved 2018-08-02.
  2. ^ "Getting to know Brandeis Marshall - Purdue Polytechnic Institute". polytechnic.purdue.edu. Retrieved 2018-08-07.
  3. ^ "The BlackTwitter Project". www.blacktwitterproject.com. Retrieved 2018-08-07.
  4. ^ a b Marshall, Brandeis (2017-12-01). "Data science experiences for undergraduates". Journal of Computing Sciences in Colleges. 33 (2): 198–204. ISSN 1937-4771.
  5. ^ "EvergreenLP: Using a social network as a learning platform - IEEE Conference Publication". ieeexplore.ieee.org. Retrieved 2018-08-07.
  6. ^ Marshall, Brandeis (2010-08-01). "Aggregating music recommendation Web APIs by artist". 2010 IEEE International Conference on Information Reuse and Integration, IRI 2010: 75–79. doi:10.1109/IRI.2010.5558960. ISBN 978-1-4244-8097-5.
  7. ^ C. Idika, Nwokedi; Marshall, Brandeis; K. Bhargava, Bharat (2009-01-01). "Maximizing network security given a limited budget". Maximizing security given a limited budget. pp. 12–17. doi:10.1145/1565799.1565803. ISBN 9781605582177.
  8. ^ Marshall, Brandeis; Sareen, Shweta; Springer, John; Reid, Tahira (2014-10-13). "Eye tracking data understanding for product representation studies". RIIT 2014 - Proceedings of the 3rd Annual Conference on Research in Information Technology: 3–8. doi:10.1145/2656434.2656439. ISBN 9781450327114.
  9. ^ "Preparing Minority Students for the Data - Driven Future - ProQuest" (PDF). search.proquest.com. Retrieved 2018-08-07.
  10. ^ "NSF Award Search: Award#1623362 - Targeted Infusion Project: Data Science eXtension (DSX): Incorporating data science fundamentals in computing curriculum at Spelman and Morehouse Colleges". www.nsf.gov. Retrieved 2018-08-02.
  11. ^ "dsxhub". dsxhub. Retrieved 2018-08-07.
  12. ^ cmaadmin (2017-06-29). "Experts: Data Science and Analytics Skills Essential for Minority Students". Diverse. Retrieved 2018-08-02.
  13. ^ "NSF Award Search: Award#1547714 - Planning a Dual Institution Research Center in Socially Relevant Computing". www.nsf.gov. Retrieved 2018-08-07.
  14. ^ "NSF Award Search: Award#1232397 - Broadening Participation in Data Mining Workshop". www.nsf.gov. Retrieved 2018-08-07.
  15. ^ "Computer Science is for All Students! - Special Report | NSF - National Science Foundation". www.nsf.gov. Retrieved 2018-08-07.
  16. ^ Roundtable on Data Science Postsecondary Education (PDF) (Report). National Academies of Sciences. March 23, 2018.

External links[edit]