torrance.fennell's picture

Faculty Details

Adjunct Lecturer

Capella University, Minneapolis, MN, Information Technology, Ph.D. 2016

University of Maryland University College, College Park, Maryland, Telecommunications Management, M.S. 2001

Howard University, Washington D.C., Electrical Engineering, B.S. 1996


Network Routing Protocols and Applications
Wireless Communications
Network and Web programming


Research interests include the use of IoT with renewable energy, RF energy harvesting, Free-space optical communications, wireless sensor networks, Ambient RF backscatter communications, Programmable networks, and STEM Education

Subjects Taught: 

EGPP 101 - Introduction to Engineering
Classroom instruction to introduce and engage first year engineering students to the process of innovation in engineering design; the engineering profession and its impact on issues of relevance to society; and non-technical skills critical to professional success.

CSCI-350 Structure of Programming Languages
Classroom instruction to expose students to advanced concepts in programming languages. Emphasis will be on the properties of contemporary languages that affect design, efficiency, levels of abstraction, and its use in problem solving. Several high-level languages were discussed, and students gained an understanding of issues relating to the design and implementation of each language. A major focus of the lectures was to provide an overview of the key paradigms used in developing modern programming languages. During the course, we explored C++, LISP, SNOBOL, XML and PROLOG and others that provide features that illustrate important programming concepts.

CSCI-450 Data Communications and Network Programming
Provided classroom instruction for an introductory course on computer networking. During the course, we covered the layering model of the Internet as well as the upper four layers (application, transport, network and data link) in detail with dominant networking protocols and algorithms. During the course, socket programming was discussed and taught.

Detailed Information

About Me: 

Dr. Fennell is a servant leader and educator who implements various pedagogical strategies focused on driving higher student achievement and engagement in the classroom. Dr. Fennell brings a wealth of industry experience to life during classroom instruction by aligning theory with applied practice and real-world experience.

Dr. Fennell currently holds an appointment as an Adjunct Lecturer at Howard University in the Computer Science Department. Dr. Fennell has more than twenty years of industry experience working for fortune 100 companies in the Telecom and Information Technology industry. Dr. Fennell holds a B.S. in Electrical Engineering from Howard University, M.S. in Telecommunications Management from the University of Maryland University College, and a Ph.D. in Information Technology from Capella University.


Fennell, T. (2016). Examining Offshore Information Technology Outsourcing and STEM College Pipeline: A Quantitative Correlational Study.


Recent Computer Science Ph.D. Graduates Join Industry as Outstanding Researchers

Fri, November 20, 2020

Recent Computer Science Ph.D. graduates Abdulhamid Adebayo (far right) and Ronald Doku (second to the right) joined tech giants IBM Research and Oracle as researchers in cybersecurity and data science. Dr. Adebayo joined IBM Research as Hybrid Cloud Security Researcher and Dr. Doku joined Oracle, Inc. as Data Scientist. Both were graduate research assistants and advisees of Danda B. Rawat, Ph.D., Computer Science Professor and Director of Howard University’s Data Science & Cybersecurity Center (DSC2). Read More >>

Electrical Engineering Lecturer Fadel Lashhab Receives 2020 IEEE IEMTRONICS Best Paper Award

Fri, October 23, 2020

Electrical Engineering Lecturer Fadel Lashhab, Ph.D. recently received the prestigious Institute of Electrical and Electronics Engineers (IEEE), International IoT, Electronics and Mechatronics (IEMTRONICS) Best Paper Award in the Mechatronics track for his paper titled “Estimation of Dynamic Laplacian Eigenvalues in Dynamic Consensus Networks”. Read More >>


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