Stephen W. Neville | PhD, PEng (BC), Professor, Software Engineer

Welcome to the academic website of Stephen W. Neville, PhD, PEng (BC).

I am a Professor of Software Engineering in the Department of Electrical and Computer Engineering at the University of Victoria.

Additionally, I co-manage Entrepreneurship@UVic, a highly successful program developed as a collaboration between the University, the Alacrity Foundation, and Wesley Clover International that has to date co-founded 7 successful and growing high-tech ventures which combined employ over 400 people. and have a market value in excess of $300MM. Four of these companies have gone on to have successful acquisition exists.

I am also the Director of Software Engineering, a joint program of the Departments of Computer Science and Electrical and Computer Engineering, where I have recently lead the successful effort to secure BC Provincial Government support under Tech Expansion 2.0 to expand the Bachelors of Software Engineering (BSENG) program by 300-seats by the 2028/29 academic year. This will see the BSENG program nearly double in size from its current 325 declared students to 625+ declared students in 2028/29.

Previously, I was a Co-PI with the Networks of Centres of Excellence of Canada (NCE) funded funding agency cyber-security focused Knowledge Mobilization effort the Smart Cybersecurity Network (SERENE-RISC) hosted by the Université de Montréal, which built on my US industry experience in cyber-security on a US Navy funded SBIR project.

I also was the founding Director of the Faculty of Engineering’s provincially supported Centre for Advanced Security, Privacy, and Information Research (ASPIRe Centre), as well as being one of 15 founding academic members of NSERC’s coast-to-coast cyber-security focused Strategic Network – the Internetworked Systems Security Network (ISSNet), which involved 20+ industry/government partners including the Government of the Province of British Columbia and ran from 2007-2014.

My primary research focuses on real-world applied research targeting important industry- and government problems and concerns spanning the areas of:

High-tech entrepreneurship (15 years experience)
At-scale cyber-security and cyber-privacy issues and involving nation-state adversaries and multi-jurisdictional concerns, e.g. systems of regional, national, and global scales. (20+ years experience)
Software engineering of modern at-scale cloud-deployed software system, particularly with respect to assessing their scalability, performance envelopes, and QoS/QoE predictability (20+ years experience)
Applied data analysis and data science as applied to at-scale industry and societal problems, spanning classical statistical methodologies and AI/ML approaches (30+ years experience)
Cloud computing, dynamical resource management, and QoS predictability.
More recent research is exploring the applications of formal control theory and dynamical systems approaches to formal explore when at-scale software systems admit run-time behavioural predictability and bounded cyber-security risks, as such approaches have direct application to the emerging areas of Cyber-Phyical Systems (CPS), Internet-of-Things (IoT), Smart Cities, Smart Grids, autonomous vehicles, etc.

The common theme underlying these research areas is:

“Building the tools and understandings necessary to become able to quantitatively engineer the larger-scale software, IT, and data analysis systems upon which modern societies are coming to depend upon.”

My research areas build on and make extensive use of the theoretical disciplines of:

Data analysis, artificial intelligence, and machine learning (AI/ML)
Statistical signal processing,
Stochastic processes,
Statistical pattern recognition,
Dynamical systems theory (and ergodic theory),
Game theory,
Large-scale decision support systems
Cyber-security and Privacy, and
Software Engineering.

Much of the research I undertake involves direct industry collaborations which must provide real industry value and end-of-day industry usable results. My in-industry experience spans working on:

A $300M rebuilding and modernization of a consumer loan payment processing systems within the US financial sector for nation-scale deployemnt inclusive of a requirement to execute 100,000+ transitions per hour, significant legal requirement and liabilities (40,000+ legal specification), and the use of AI to expose the underlying payment processing rules to ensure adaptability and maintainability. This large-scale software development effort involved a team of over 300 software development professionals.
Being the Principal Analyst on a US Navy Space and Naval Warfare Command (SPAWAR) funding project to develop an automated decision support system to work at the level of a senior cyber-security analyst for deployment within operational but not mission critical 1,000+ host computer networks.
Working within to context of E@UVic companies to support the development of larger-scale software systems servicing global scale customer bases and cybersecurity and privacy requirements on multinational scales. These systems included those that: i) collected 30B+ QoS measurement daily from globally distributed mobile devices (Tutela Systems), ii) enabled geo-located data analysis across large-scale social media (EchoSec System), and iii) enabled 250M+ mobile ad placements per month (Pretio Interactive).

Hence, my applied software engineering and data science research is informed by core real-world experience and the need to ensure that real-world systems are produced that work correctly at-scale and are maintainable, scalable, secure, privacy preserving, cost-effective, etc.

My research typically involves the use of substantial computing resources available either through my own InSPiRe lab, which contains a closed-facility 60 machine research cluster, or via HPC resources provided via West Grid and Compute Canada.

Students, postdoctoral researcher, visiting scholarly, etc, interesting in working with my Information Security and Privacy Research laboratory should follow the Research Positions link.