Ted Markowitz, Ph.D.
Doctor of Professional Studies in Computing (D.P.S.), Pace University
Doctoral-level Work in Computer Science, University of Rochester
MS in Computer Science, Columbia University
BA in Music & Russian Studies, Columbia University
Prior to joining the University of New Haven Dr. Markowitz had a long and successful technical career in information systems at a number of large companies including American Express, Xerox, and Netscape/AOL, in addition to working as Chief Architect with a Connecticut-based technology start-up firm that was a sibling to Priceline.com. Over that span his responsibilities as a corporate employee—with titles such as Director of Advanced Technology and Chief Knowledge Engineer—and as an external consultant to both small firms and to international corporations, included the hands-on design and implementation of several leading-edge applications and the development of large-scale information architectures. These projects utilized a variety of technologies and operating environments, e.g., C/C++, Java, Lisp, SQL databases, object-oriented & Artificial Intelligence (AI) tools, Windows/Linux, digital imaging systems, etc. In addition, during that time he also managed software development teams and hardware support organizations, and participated in the creation and oversight of a multi-million dollar corporate R&D process. Having this extensive background in delivering functioning systems and technical management brings a unique industry perspective to Dr. Markowitz’s teaching style—as well as a certain amount of “been there, done that” real-world credibility—which his students can draw upon as needed and have appreciated in the past.
As part of moving back into teaching after a long career in systems work, I undertook and completed a Computer Science research doctorate at the Seidenberg School of Computer Science and Information Systems at Pace University in NY.
My dissertation research—conducted in conjunction with senior investigators at IBM Research in Hawthorne, NY—focused on the use of Machine Learning techniques to autonomously create annotated training & testing corpora (databases of pre-labeled examples) for use by researchers in any number of domains. The specific domain of the corpora described in the dissertation was comprised of e-mail spam and desirable e-mails used for anti-spam filtering research.
I expect my future research to continue pursuing similar lines of inquiry using Machine Learning in some form, though I am also exploring other topics as well, for example, research into pedagogical issues surrounding the teaching of Computer Science at the university level and the use of intelligent, network-based tools to promote learning.
I am a long-standing member of the IEEE Computer Society, the ACM (Association for Computing Machinery), and AAAI (the American Association for Artificial Intelligence).
Awards and Honors
Pace University - 2008 Upsilon Pi Epsilon award (International Honor Society for the Computing & Information Disciplines)
Xerox CIO Leadership Award winner for participating in the analysis and redesign of the internal Xerox global technical infrastructure
Intel/ComputerWorld RealWare Award finalist in recognition of the innovative use of object-oriented technologies and digital imaging in conjunction with on-line transaction processing (OLTP) systems
CEAS 2006 anti-spam conference accepted paper on construction of testing/training databases using Machine Learning techniques: “Fast Uncertainty Sampling for Labeling Large E-mail Corpora"
Co-holder of US Patent 20060271441: “Method and apparatus for dynamic rule and/or offer generation.” November 2006