faculty

Lance Fiondella, PhD

Director

Cybersecurity Center

Professor

Electrical & Computer Engineering

Dependable Software and Systems Lab

Contact

508-999-8596

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Science & Engineering 209B

Contact

508-999-8596

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Science & Engineering 209B

Education

2013

RMIT University

Postdoc in Geospatial Science & Statistics

2012

University of Connecticut

PhD in Computer Science & Engineering

2003

University of Connecticut

MS in Computer Science

1999

Eastern Connecticut State University

BS in Computer Science

Teaching

Programs

Teaching

Courses

EAS 601: Pre-Dissertation Research

Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.

EAS 701: Doctoral Dissertation Research

Investigations of a fundamental and/or applied nature representing an original contribution to the scholarly research literature of the field. PhD dissertations are often published in refereed journals or presented at major conferences. A written dissertation must be completed in accordance with the rules of the Graduate School and the College of Engineering. Admission to the course is based on successful completion of the PhD comprehensive examination and submission of a formal proposal endorsed by the student's graduate committee and submitted to the EAS Graduate Program Director.

ECE 171: Data Structures

Computer system and program design issues, abstract data types, dynamic memory allocation, procedural and data structures using a system programming language. Concepts of the machine model, procedural programming and program development including coding, debugging, and testing of programs are covered. The following data structures are covered: linked lists, stacks, queues, binary trees and hash tables. Run time complexity and procedural abstractions such as recursive functions are discussed. Features of the system programming language such as multiple files, libraries and input/output programming with files are covered using engineering examples. Object-oriented concepts are introduced.

ECE 171: Data Structures

ECE 403: Specl Topics-Elec & Comp Egr

Topics of timely interest in electrical and computer engineering. Course content may change from year to year according to instructor's preferences.

ECE 577: Artificial Intelligence

An introduction to artificial intelligence and expert systems. Topics covered include state-space representations and search methods; problem-reduction representation and search methods; Bayes networks; theorem proving using predicate calculus; natural languages; expert system design using Lisp or Prolog; and an introduction to neural networks and pattern recognition.

Research

Research activities

Software reliability engineering
System reliability and resilience engineering

Research

Research awards

$ 60,000 awarded by Alion Science and Technology for Resilience Modeling for Analysis, Prediction, and Optimization
$ 499,999 awarded by Commonwealth of Massachusetts for Mass Skills - Intelligent Industrial Robotics and Cyber Security Test Bed
$ 1,218,640 awarded by National Science Foundation for CyberCorps Scholarship for Service: Accelerating Cybersecurity Education, Scholarship and Service
$ 149,903 awarded by U.S. Department of the Army for Resilience Engineering of Machine Learning-enabled Open World Recognition for Network Intrusion Detection Systems
$ 94,864 awarded by U.S. Army Research Office for Part-time Intergovernmental Personnel Act (IPA) Assignment with US Army Corps of Engineers

Research

Research interests

Autonomous systems
Software and system security
Software processes
Transportation network vulnerability
Prognostics and health management

Select publications

P. Silva, B. Gaspard, M. Hotchkiss, G. Kul, N. Bastian, and L. Fiondella (2024).
Regression and Time Series Mixture Approaches to Predict System Performance and Assess Resilience
IEEE Transactions on Reliability
Z. Faddi, K. da Mata, P. Silva, V. Nagaraju, S. Ghosh, G. Kul, and L. Fiondella (2025).
Quantitative Assessment of Machine Learning Reliability and Resilience
Risk Analysis, 45(4), 790-807.
V. Shekar and L. Fiondella (2025).
Efficient Vulnerability Assessment of Large-scale Dynamic Transportation Networks
IEEE Transactions on Reliability, 74(2), 2738-2750.
J. Steakelum, H. Dinh, and L. Fiondella (2025).
Towards a Quantitative Science of Nonviolence: A Systematic Analysis of an Agent-based Model of Nonviolent Resistance
In Proc. Annual Modeling and Simulation Conference (ANNSIM)
F. Salboukh and L. Fiondella (2025).
Optimizing Software Defect Classification with Locally Linear Embedding Method
In Proc. 71st Annual Reliability and Maintainability Symposium (RAMS 2025)

Lance Fiondella joined the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth as an assistant professor in 2013. Effective September 1, 2025, he is a professor and the Director of the University of Massachusetts Dartmouth Cybersecurity Center, an NSA/DHS National Center of Academic Excellence in Cyber Research (CAE-R). He conducts research in the areas of system and software reliability, security, and resilience. He has published over 180 peer-reviewed journal articles and conference papers on these topics, and has received over $7.5 million in external funding as principal investigator, including an NSF CAREER Award.