Leonard Campanello (Ph.D. ’20, physics) spent the last three years on an ambitious mission—helping billions of Google Maps users find exactly what they’re looking for.
“I worked on the search function for Google Maps: you move the screen to a section of the map where you want to look for restaurants or hotels or things to do, add filters or attributes, like it has to be dog friendly or have a waterfront view,” Campanello explained. “And you want Google Maps to give you the best answer every time.”
As a Senior Data Scientist at Google, Campanello’s work brought science to the search process, applying the interdisciplinary physics training he received as a Ph.D. student in Professor Wolfgang Losert’s lab at the University of Maryland. Working on the Google Maps team, Campanello put his experience with models, algorithms, and analytics to work to better understand Maps users and optimize their search results.
“So, when you first issue a search, there's a list of places in a particular order. That order is carefully controlled,” Campanello explained. “We’ve proven that changing ranking algorithm has a material impact on the user's experience, and, at the end of the day, we need to know, did we have a net positive or a net negative effect on users? And we always strive to go in the net positive direction.”
As a scientist, Campanello has always been passionate about finding the stories hidden in data and building statistical models that capture the essence of the data, putting his physics skill set to work to answer a question or solve a problem.
“At the core of many problems in both physics and data science, I think we are trying to understand the data generating process so that we can better explain the fundamental physical phenomena driving what we see,” Campanello explained. “We observe that applying a force results in some change in a measurable quantity, whether the subject is a Google Maps user or a cell under the microscope. What's going on in the background that's fundamentally causing that change? How can we use this information to better understand our world? That’s what we want to find out.”
All in on physics
Campanello was a strong student who went all in on science and math since high school and earned a bachelor’s degree in physics from St. John’s University in 2013. Then, still unsure about how physics would translate into a future career, Campanello decided to pursue his Ph.D. at UMD, where he would have access to various options.
“I didn't know that what I wanted to do with enough certainty that I could commit to a graduate school that was kind of one dimensional,” Campanello recalled. “UMD had a massive physics department with a diversity of people in experiment and theory, whether it was condensed matter or high energy or biophysics or whatever, and that range of options was what ultimately kind of pulled me to UMD.”
After spending his first year working in condensed matter theory, a class with Physics Professor Michelle Girvan gave Campanello a whole new perspective.
“The class was nonlinear dynamics of extended systems and to this day it's probably the most influential class I ever took,” Campanello said. “Her problem-solving approach, including using graph theory and complex systems models, which I was never exposed to before, was eye-opening. We could actually create mathematical representations of all of these phenomena that we see in the world. And I was just wowed.”
At Girvan’s suggestion, Campanello joined Losert’s lab and began his Ph.D. research quantifying and modeling different dynamic processes, specifically complex interactions in biological systems.
“We already knew what some of the interactions were, so we knew that if we put this immune cell in the presence of some material, the immune cell would react in a specific way, which we could also measure under a microscope,” Campanello explained. “So given this set of biochemical information on the way these things behave short-term, medium-term and long-term, we said, how can we fit mathematical models to the microscope data and then use this to make inferences about this system as a whole?”
Opportunities, collaborations and simulations
Campanello took advantage of many opportunities at UMD, from teaching multiple MATLAB Boot Camps on image processing, computer vision and data analysis to coaching teams of data science students for the annual university-wide Data Challenge competition. Meanwhile, his continuing work in Losert’s lab exposed him to a world of possibilities.
“Wolfgang gave me and everyone in his lab the opportunity to work on so many different projects and collaborations with the National Institutes of Health and others, whether it was fundamental cell biology to projects on the interface of immunotherapies and autoimmune diseases to cancer, it's just crazy how much exposure we had,” Campanello noted. “He would help us identify opportunities to apply our analysis and modeling tools, give us guidance on the projects, and then let us to run with it. I really appreciated that.”
Campanello earned his Ph.D. in August 2020 and continued to do research at UMD for about six months before landing a job at Citibank in early 2021, applying his experience in modeling and analytics to consumer banking.
Later that same year, he accepted a very different kind of opportunity at Google, working with the team that supports Google Maps to evaluate, advance and improve its ever-expanding search functions and, later, new capabilities, thanks to the addition of artificial intelligence.
“The team is like 30 or so engineers, product managers, designers, user-experience researchers, and I was the one data scientist,” Campanello explained. “One of my primary responsibilities when I first joined was to create metrics or measurements that were absolute—meaning not open to interpretation—and I spent a lot of time doing research in that area to ensure that those measurements aligned with what we wanted for the user. What do we measure to know if we made the experience better?”
A new opportunity
In February 2025, after more than three years at Google, Campanello left to join Optiver, an Amsterdam-based global market maker that buys and sells securities to provide liquidity to markets. In this new position, he’ll again leverage his physics skill set, this time as a quantitative researcher.
“Part of my role will be to help improve the team's predictions in order to make better trading decisions. Can we make predictions right now about what will happen later today or later this hour or even just one minute from now?” Campanello explained. “If we can put numbers to these things and build models that accurately predict outcomes, then we can ultimately use those models to improve liquidity for all market participants.”
Fascinated by finance—and still inspired by the power of physics—Campanello looks forward to this next opportunity to grow.
“I've always had an interest in finance and what I'm looking forward to the most in this new role is the ability to really further my skill set,” Campanello said. “I want to get more exposure to what's happening at the bleeding edge of modeling and data science in quantitative finance. And I think this will be a good avenue for me to do that.”
Written by Leslie Miller