According to Bhushan Gopaluni, Associate Dean of Education and Professional Development in the University of British Columbia’s Department of Chemical and Biological Engineering, we now enjoy an embarrassment of riches when it comes to information technology.

“If you look at the history of systems and control and data analytics, we are at a unique historic moment,” he explains, pointing to a steady improvement in the hardware and software that have become widely available over the last four decades. Dramatic increases in computer processing power and data storage arrived in the 1990s, but it was not until the 2000s that individuals and organizations were able to upload large amounts of data into universally accessible networks.

It was during this period that Gopaluni consulted with Matrikon Inc. (now Honeywell Process Solutions) to develop a new generation of multivariable controllers for British Columbia’s pulp and paper industry. It was a game-changing innovation that dramatically improved efficiency within many of the province’s mills, which could then install a variety of new equipment to automate existing processes and integrate their management with other systems.

Such progress would continue over the next decade, he adds, as machine learning began to thrive within a new environment that was becoming defined by readily available computing capacity and massive volumes of information. Gopaluni subsequently began to work with various parts of the chemical sciences sector, where the introduction of ever more sophisticated controllers would offer gains that might have been unimaginable just a decade earlier.

As the advent of quantum computing technology ushers in an entirely new wave of processing potential, he remains committed to helping the administrators of large industrial systems embrace the accompanying possibilities.

“My focus is on extracting useful, actionable information from large volumes of industrial data,” he says, pointing to a wide range of work in medical biology, manufacturing, natural resources, and energy.

This year his various accomplishments won him the D.G. Fisher Award, which is given annually by the Canadian Society for Chemical Engineering to an individual who has made major contributions in the field of systems and control engineering. The award credits him as a leading expert in the rapidly evolving field of data analytics, where has authored more than 150 refereed papers. This distinction also cites his contribution in the academic sector, where he has earned UBC’s prestigious Killam Teaching Prize and the Dean’s Award for Excellence in Service.

As he looks toward the future of systems and control, Gopaluni cautions there are still limitations to what can be achieved, despite the excitement in areas such as using “big data” to address many formerly insurmountable problems.

“Not all data is good data,” he warns, and establishing the quality of information could become a much-needed speciality to improve any initiative that deals with large data sets. Similarly, many powerful algorithms employed for industrial use are in fact poorly understood, often so much so that they function more or less as “black boxes” that work well, though no one really knows how they do so. It may become imperative to determine how these powerful programs work, not only as a way of avoiding pitfalls but perhaps to make them function better.

Despite these obstacles, Gopaluni remains optimistic. As the scope of this work has proceeded, so too has the scale of what is now possible.

“In the past we focused on individual, small units,” he concludes. “Now because of the tools we have and the computing power we have, the data we have, we can build really large-scale dynamic models. That was never possible before.”