Professor Thomas Marlowe has been a member of the Department of Mathematics and Computer Science at Seton Hall University for almost 40 years, and has taught a wide variety of courses in both disciplines. Until he went on phased retirement in 2017, he was coordinator and advisor for the Computer Science program. Professor Marlowe enjoys working with students and with professional colleagues—almost all his research is collaborative. His professional interests include in mathematics, abstract algebra and discrete mathematics; in computer science, programming languages, real-time systems, and software engineering, and pedagogy; and in information science, collaboration and knowledge management. The connection between graphs and algebraic structures is a recurrent theme.

Professor Marlowe has Ph.D. in Computer Science, from Rutgers, The State University, and a Ph.D. in Mathematics, also from Rutgers. Professor Marlowe has many publications and academic distinctions, with over 100 publications in refereed conferences and journals in mathematics, computer science and information science. Some of the more recent and more significant include:

• J. Marlowe, J.R. Laracy, “Logic as a Key to Integrating the Curriculum for STEM Majors”, Journal on Systemics, Cybernetics and Informatics: JSCI Volume 15 - Number 4 - Year 2017, pp. 63-71, ISSN: 1690-4524 (Online)
• Kirova, T.J. Marlowe, C.S. Ku, “Monitoring and Reducing Application Fragility through Traceability and Effective Regression Testing”, Genie Logiciel, No 115, 2-9, December 2015.
• Rountev, S. Kagan, T. J. Marlowe, “Interprocedural Dataflow Analysis in the Presence of Large Libraries”, Proceedings of CC 2006, 216, Lecture Notes in Computer Science 3923, 2006.
• P. Masticola, T. J. Marlowe, B. G. Ryder, "Multisource Data Flow Problems'', ACM Transactions on Programming Languages and Systems, 17 (5), 777 -803, September 1995.
• D. Stoyenko, T. J. Marlowe, "Polynomial-Time Program Transformations and Schedulability Analysis of Parallel Real-time Programs with Restricted Resource Contention'', Journal of Real-Time Systems, 4 (4), 1992.
• J. Marlowe, B. G. Ryder, "Properties of data flow frameworks: A unified model'', Acta Informatica, 28 (2), 121 -164, 1991.

While technology, computing, and "big data" seem to be ubiquitous, transforming, and sometimes more than a bit invasive, many problems confront both the computing and data science (and more generally, the STEM) workforce, on the one hand, and the academic and societal development of those disciplines, on the other. Among these are (1) a true shortage of well-rounded and skilled workers, (2) a lack of "soft skills", ethical and philosophical understanding, broad background, and deep context among those workers, (3) a lack of both social and demographic diversity in the workforce, and (4) a difficulty in carrying out interdisciplinary efforts, both in research and commercially.

In this presentation, I present a step toward a solution: a certificate transitioning between Bachelor's and Master's level studies, offered to students from all undergraduate backgrounds, with an emphasis on background skills, understanding, and context. As these courses are completed by an academically and socially diverse cohort, students will develop an interdisciplinary view as well as a conceptual understanding of computing and data science; enhance communication, teamwork and problem-solving skills; and appreciate the philosophical and ethical issues involved. I then discuss costs, benefits, risks and tradeoffs, plus possible other uses and extensions, and ramifications for the stakeholders.