Ph.D., Computer Science
M.S., Computer Systems
B.S., Business Data Processing
Ph.D., Computer Science
M.S., Computer Systems
B.S., Business Data Processing
Fuzzy logic, decision support systems, project management, artificial intelligence, machine learning
Dr. Hammell joined Towson University in the fall of 2001; he is a Full Professor and is also currently the Associate Chair of the department. He has taught a wide variety of graduate and undergraduate courses for the department, as well as graduate courses in the Center for Applied Information Technology.
Prior to joining Towson University, Dr. Hammell served 22 years in the U.S. Army, retiring as a Lieutenant Colonel. During his career he served in both the Signal Corps (tactical mobile communications) and the Acquisitions Corps (materiel development, acquisition and procurement). Career highlights include 3 ½ years developing and teaching computer engineering graduate courses at the Air Force Institute of Technology; 2 ½ years in a Program Management Office managing budgetary and programmatic aspects of a highly visible and successful program to field the first U.S. Army tactical personal computer; and 6 years as a Senior Computer Scientist for the U.S. Army Research Laboratory, focusing on the area of tactical intelligent systems.
J. Auten, and R.J. Hammell II, “Predicting the Terminal Ballistics of Kinetic Energy Projectiles Using Artificial Neural Networks”, Journal of Information Systems Applied Research, 7(1) pp 23-32, 2014. http://jisar.org/2014-7/, ISSN: 1946-1836. (A preliminary version appears in The Proceedings of CONISAR 2013)
D. Kwon, and R.J. Hammell II, "Early Stage Probabilistic Software Project Schedule Estimation", Journal of Information Systems Applied Research, 6(4) pp 31-48, 2013. http://jisar.org/2013-6/, ISSN: 1946-1836. (A preliminary version appears in The Proceedings of CONISAR 2012)
A. Conover and R.J. Hammell II, “Temporally Autonomous Agent Interaction”, in Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications, G. Trajkovski, ed., Information Science Reference, Hershey, PA, pp. 19-37, 2010.
R.J. Hammell II, J. Powell, J. Wood, and M. Christensen, “Computational Intelligence for Information Technology Project Management”, in Intelligent Systems in Operations: Models, Methods, and Applications, B. Nag, ed., IGI Global, Hershey, PA, pp. 80-104, 2010.
A. Barnes and R.J. Hammell II, “Employing Intelligent Decision Systems to Aid in Information Technology Project Status Decisions”, in Intelligent Systems in Operations: Models, Methods, and Applications, B. Nag, ed., IGI Global, Hershey, PA, pp. 1-26, 2010.
J. Auten and R.J. Hammell II, “Comparing the Prediction Capabilities of an Artificial Neural Network vs a Phenomenological Model for Predicting the Terminal Ballistics of Kinetic Energy Projectiles”, Proceedings of the Conference on Information Systems Applied Research (CONISAR 2015), 1-4 November, Wilmington, NC.
C. Fowler and R.J. Hammell II, “Mining Information Assurance Data with a Hybrid Intelligence/Multi-agent System”, Proceedings of the 14h IEEE/ACIS International Conference on Computer and Information Science (ICIS 2015), pp. 23-28, June 28-July 1, 2015, Las Vegas, NV.
D. Kwon and R.J. Hammell II, “Objective Framework for Early-Stage Comparison of Software Development Project Types.”, Proceedings of the 14h IEEE/ACIS International Conference on Computer and Information Science (ICIS 2015), pp. 393-398, June 28-July 1, 2015, Las Vegas, NV.
S. Miao, R.J. Hammell II, Z. Tang, T. Hanratty, J. Dumer, J. Richardson, “Integrating Complementary/Contradictory Information into Fuzzy-Based VoI Determinations”, Proceedings of the 8th IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA 2015), pp. 1-7, May 26-28, 2015, Verona, NY.
S. Smith, R.J. Hammell II, T. Parker, and L. Marvel, “A Theoretical Exploration of the Impact of Packet Loss on Network Intrusion Detection”, Proceedings of the 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014), pp. 161-166, June 30-July 2, 2014, Las Vegas, NV.
T. Hanratty, J. Dumer, R.J. Hammell II, Z. Tang, and S. Miao, “Tuning Fuzzy Membership Functions to Improve Value of Information Calculations", Proceedings of the 2014 North American Fuzzy Information Processing Society Conference (NAFIPS 2014), pp. 1-7, 24-26 June, 2014, Boston, MA.
A. Newcomb and R.J. Hammell II, "Validating a Fuzzy-based Mechanism for Improved Decision Support" Proceedings of the 14th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), pp. 143-148, 1-3 July, 2013, Honolulu, Hawaii.
J. McQuighan and R.J. Hammell II, "Applying the Design Science Research Methodology to IT Project Management", Proceedings of the IADIS International Conference on Information Systems (IS 2013), pp. 191-198, 13–15 March, 2013, Lisbon, Portugal.
Current and recent research is focused on applying soft computing techniques to various application areas as well as research related to decision making, project management, and military situational awareness.
Funded collaborative research with the US Army Research Laboratory with respect to information fusion, especially as related to battlefield situational awareness. A major thrust of the current work focuses on fuzzy-based methods for producing Value of Information (VoI) determinations and how these can be used by military intelligence analysts.
Doctoral research focused on the application of the above VoI architecture to the domain of cyber security. This research has direct relevance to the U.S. Army through the student’s ties to the U.S. Army Research Laboratory at Adelphi, MD.
Doctoral research focused on the application of Artificial Neural Networks (ANNs) to the prediction of the terminal ballistics of Kinetic Energy Projectiles (KEPs). This research has direct relevance to the U.S. Army through the student’s ties to the U.S. Army Research Laboratory at Aberdeen Proving Ground, MD.
Doctoral research to develop and test hybrid intelligence/multi-agent systems for mining information assurance data.
Doctoral research focused on exploring possible areas where decision support systems (DSS) can be applied to the project management process with respect to information technology (IT) projects, especially as related to the areas of planning, scheduling, and decision making.
Doctoral research aimed at the advancement of computer-based decision support; specifically extending the agent-based naturalistic decision making model through improved human-agent collaboration. The research has direct relevance to the U.S. Army through the student’s ties to the U.S. Army Research Laboratory at Aberdeen Proving Ground, MD.
Application of fuzzy logic and neural networks to pattern recognition and classification of ion mobility spectrometry time-of-flight mass spectrometry data. Multiple algorithms have been developed to recognize and classify chemical warfare agents from raw two-dimensional data sets. Two different chemical agent stimulant data sets have been used and results show 100% classification accuracy.
Discovery of fuzzy temporal associations in multiple data streams. This research is aimed at extending current data mining techniques to allow distributed temporal data to be analyzed. Fuzzy sets are used to define imprecise temporal durations and permit the discovery of temporal associations. An algorithm was developed and applied to two real-world medical data sets with excellent results.
Associate Chair, Department of Computer and Information Sciences;
Chair, Department Assessment Committee;
Serve on the department Open House Committee (co-Chair), Diversity Committee, Alumni Relations Committee, Scholarships and Awards Committee, and the IS Program Committee.