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.”
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.
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.”