With the arrival of Andrea Lodi as the new Canada Excellence Research Chair (CERC) in Data Science for Real-Time Decision-Making at Polytechnique Montréal, Canada is consolidating its position as a leader in one of science’s most dynamic and revolutionary fields: big data.

“There has never before been so much information available to humanity, so it is a revolution,” said Lodi. “We are now able to get data from pretty much everywhere—from cameras and cell phones, of course, but also from online activity, and even from buildings equipped with sensors. The question is: How do we use this data so we can understand it and make decisions that will improve people’s lives based on this understanding?”

Through his research, Lodi is working towards providing some of the answers.

“I will be looking to develop new methodologies to exploit big data,” he said. “This involves creating algorithms to achieve optimized strategies for decision-making, which will help us solve day-to-day problems—sometimes in real time.”

Algorithms are well-defined, step-by-step instructions that define sequences of operations for computers. Lodi uses them in a branch of applied mathematics called “mathematical optimization,” to solve real-world problems in areas from DNA sequencing to traffic-flow operations, all in real time.

“Big data is such a hot topic at the moment—for mathematicians, for planners, and for social scientists,” said Lodi. “My work involves developing applications that collect, understand and then are able to decide on the most efficient use of this data, to provide answers in a concrete way—for example, how to make our cities smarter.”

Improving traffic flow is one of the many ways in which Lodi sees his research having significant benefits in cities around the world.

“Traffic controllers are able to receive so much information nowadays,” he said. “People call on their cell phones, data is received from street cameras and sensors; all of this is real-time data. When there is an unexpected disruption, such as an accident or a severe weather situation, you need to react in real time. Even though some of this can be planned in advance, a lot is not predictable, and data analysis, together with algorithms, helps you to react promptly and effectively.”

Andrea Lodi
Canada Excellence Research Chair in Data Science for Real-Time Decision-Making

“The software we develop is based on mathematical theory and decision science; it enables people to change plans and tells them how to react quickly in case of unexpected disruptions,” he said. “More generally, it helps you make optimal decisions concerning the scheduling of trains or subways, the assignment of telecommunication frequencies, the routing of buses, or health-care management. In real time, it will help minimize disruption and ease congestion.”

Lodi sees significant environmental benefits to his research—and not only because it could reduce the time cars and trucks spend idling in traffic jams. As people increasingly contribute power to the grid, new applications will enable the best possible allocation of resources. For example, Lodi’s algorithms could help power companies know when they might need to draw extra energy into the system.

“We have limited resources as a planet,” said Lodi. “If we can limit our consumption of resources, control their waste and overuse—if we can use these resources in a smarter, optimized way, then it is better for our cities and towns, and better for the planet.”

Lodi says his arrival at Polytechnique Montréal will enable him to grow the theoretical, methodological and applied aspects of his research, and give him the opportunity to work with what he calls “some of the best researchers in the field.”

“This is a great coup for us,” said Christophe Guy, chief executive officer of Polytechnique Montréal. “Andrea Lodi is one of the world’s best researchers in the use of mathematical optimization and big data for decision-making. His arrival here will galvanize an already impressive program.”

“Polytechnique Montréal is a truly collaborative place,” said Lodi. “It is a prestigious and highly relevant institution. The new Chair is not going to be about a single person or a single group. It will be people working together in various different but interconnected disciplines—mathematical optimization, operations research, machine learning, statistics—to develop solutions to problems that affect society.”