Mehrdad Saif, former dean of the Faculty of Engineering and a professor in the Department of Electrical and Computer Engineering, has been elevated to Fellow grade by the Institute of Electrical and Electronic Engineers (IEEE).

The IEEE Fellow is one of the institute’s most prestigious honours, bestowed upon a very limited number of senior members who have contributed prominently to the advancement or application of engineering, science, and technology, bringing significant value to society. The number of IEEE Fellows elevated in a year is no more than one-tenth of one per cent of the total IEEE voting membership. According to the IEEE, Saif was elevated to the Fellow grade “for contributions to monitoring, diagnosis, and prognosis in cyber-physical health systems.”

“It certainly is rewarding,” Saif said of the recognition.

“It is satisfying and an honour, but at the same time, nobody does anything alone,” he said. “I have had many great students, post-doctoral fellows, and research colleagues that I have worked and collaborated with, and they have played a role in us advancing research on autonomous and resilient systems.”

The IEEE is the world's largest technical professional organization. Of its more than 427,000 members in 190 different countries, there are fewer than 7,500 Fellows.

Saif has worked as a university professor and a scholar in the systems and control engineering field for nearly four decades. His research focuses on the health monitoring and self-healing of complex engineering systems. It includes control, fault or cyber-attack diagnosis, prognosis, as well as automatic system adaptation to accommodate for the failures/attacks, in cyber-physical systems. In short, Saif’s research goal is to make complex engineering systems more resilient against failures or cyber threats allowing them to function safely and efficiently despite them.

He said that the application areas for his research have ranged from detecting anomalies in aerospace systems, internal combustion engines, electric vehicles, connected vehicles, wind turbines, and smart grid power systems, among others.

Saif’s early research included working on projects sponsored by NASA Lewis (now Glenn) Research Center and the Cleveland Advanced Manufacturing Program sparking his interest in the field.

“It all started with automated failure detection and accommodation tasks. The idea was to make systems such as the space station power system more reliable, something that could withstand failures,” he explained. “And then later manufacturing systems and car engines and all of these other engineering systems where even partial failure of any component could lead to catastrophic safety issues, shut down, negative environmental impact, or added costs.”

As technology advanced and systems became more sophisticated and networked, the door was opened to different types of “anomalies” such as various forms of cyber-attacks that had to be monitored beside failures.

“Nowadays, it’s both failures as well as cyber-attacks in a complex system that you would want to be able to monitor as they both affect the health of the system. The desire remains to continuously monitor the system’s operation and be able to detect all these anomalies. The problem is, however, much more challenging because there is a need to distinguish between failures and cyber-attacks, and then to further identify and isolate the source or type of the failure or the attack. There can be many sources of failures or types of attacks being launched on complex engineering systems like a smart grid, an Industry 4.0 system, or a network of Connected Autonomous Vehicles,” he said. “And the motivation behind it could be again due to safety reasons in a let's say nuclear power plant or an aircraft system. But it could also be costs, in say, a manufacturing system, or environmental impact in another application.”

Saif points to when his skillset brought him to the automotive industry in the early 1990s, working on engine monitoring and diagnosis at the General Motors North American Operation R&D Centre in Warren, Michigan. He said at the time, the Environmental Protection Agency, and California Air Resource Board mandated that all vehicles sold in North America should be equipped with what was called OBD-II (an on-board diagnosis) system to monitor engine performance, detect and identify partial failures of any component in the engine control system that could lead to excess emissions. That was a fruitful research collaboration that lasted for several years after the initial sabbatical year Saif spent at GM R&D.

In recent years, Saif said his research has additionally taken him in the direction of system prognostics.

“That is to not only monitor for failure or cyber attack but if there is a small degradation, say due to aging, into the system,” he said. “We are looking at how long more can we operate the system before we its performance is no longer acceptable, and we need to perform maintenance or repairs?”

An example he gives is electric vehicle batteries.

“Batteries are one of the most expensive components of electric vehicles. An electric vehicle battery needs to be operated with care for optimal performance. During its lifetime the battery needs to be charged and it gets discharged as you operate the vehicle, and as such, a Battery Management System is required. This idea of battery monitoring for possible failures as well as being able to predict what is referred to as the State of the Health of the battery are some of the functions that may be performed within such a system and are the type of research problems that I’m interested in. The idea of stating the health of a battery is to forecast into the future how long the battery is going to last before its performance is no longer acceptable for the task at hand,” he said.

Saif came to the University of Windsor in 2011 as dean of engineering, a position he held for two terms before returning to his professorial duties.

His prolific academic output includes over 400 refereed journal and conference papers, alongside an edited book. His scholarly impact is evidenced by his impressive citation count exceeding 10,000. Recognized globally, Saif is listed among the top 100,000 career scientists by Stanford University, in addition to ranking in the top 0.7 per cent in his field of research in the world.

Saif is a Registered Professional Engineer in Ontario and has been honoured with fellowships in several other organizations, including the Canadian Academy of Engineering, the Engineering Institute of Canada, the Institution of Engineering and Technology, and the Asia-Pacific Artificial Intelligence Association.