Center for Advanced Computation and Telecommunications

Digital Engineering Graduate Certificate

Compose of four successive courses offered in the Department of Electrical and Computer Engineering

  • These courses implement a project based learning where students will take an initiative to solve real-world problems

Course Descriptions

EECE. 5492 Systems, Modeling and Simulation for Digital Engineering

Introductory course provides a high-level view of systems thinking, systems engineering, physical system modeling, and model-based systems engineering (MBSE). System dynamics will be simulated using MATLAB, Simulink, and Python programming platforms. Student will learn to implement MBSE using the systems modeling language (SysML).


System Engineering Overview:

EECE. 5494 Model-Based Systems Engineering

The second course will focus on a model-based graphical representation of engineered systems. Systems modeling language (SysML) and MBSE will be used as a primary tool to practice in systems thinking. Model-based representation of stakeholder requirements, use-cases and scenarios, and system and interface architecture and behavior will be introduced through case studies. 

User Stories to Activity Diagram:

Model Handoff – Concept, Logical, and Physical Models:

EECE. 5496 Cyber-Physical Systems Modeling and Simulation

The focus of the third course is to analyze physical systems and their interactions with embedded digital sub-systems and communication networks called cyber-physical systems (CPS). Continuous and discrete time systems, system control, and state estimation are presented. The specification of functional, behavioral, and security requirements for CPS using a model-based systems engineering framework is undertaken.

EECE. 5498 Data-Driven Models. Decision Making and Risk Management

The final course of the certificate will address the analysis of decisions driven by data. Data retrieved from models, simulations, or measurements for prediction and inference of estimation of system behavior will be considered. Artificial intelligent (AI) / Machine learning (ML) algorithms, data visualization, and data analytics for making decision, managing  risks, and optimizing will be also introduced .


Charles Thompson

Professor of Electrical and Computer Engineering

University of Massachusetts Lowell

Kavitha Chandra

Associate Dean Undergraduate Programs and Professor of Electrical and Computer Engineering

University of Massachusetts Lowell

Past Guest Speakers

Lindsay Holden

Principal Systems Engineer at Systems & Technology Research
Vineet Mehta

Vineet Mehta

HQE - Cyber

David Hetherington

Principal at System Strategy, Inc

Author of Simple SysML for Beginners: Using CATIA No Magic Tools

Shivakumar Sastry

Professor of Electrical and Computer Engineering

DigEng Student Reflections

Will be updated.