OCTOBER 24th, 2024

BRAID’S TEAM

<aside> 💡 Welcome to another article in our series of Tech Team Profiles! Here, we’ll introduce you to the team building Braid’s automated engineering design technology. Alessandro is a Researcher at Braid with a background in physics and a career as data scientist in consulting.

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Briefly describe your career thus far.

During my master’s, I was curious about what it would feel like to work in the “real world,” i.e. outside of academia. I ended up joining a consulting firm. While many people choose consulting because they're uncertain about their career path, I saw it as an opportunity to grow—where success depended on being smart and working hard. For me, consulting became a crash course not only in business but in professional skills, like working with clients and managing projects. I spent three and half years in consulting.

During the time I was in consulting, I wanted to get closer to the more analytical side of things. At one point, I was self-studying probability & statistics because I felt these were skills that were missing from my background. Around the same time, the firm's data science division, already established in other countries, expanded to our office in Brazil, where I was based. This gave me the perfect opportunity to transition into data science.

A while later, in 2021, I joined a credit bureau as a data science manager in the so-called “innovation lab.” It was an interesting opportunity because I was mixing agribusiness, credit, and data science to create risk models for agricultural credit. It was my first real management role, where I acted as product lead, project lead, and tech lead, and was heavily involved in the sales process.

Before Braid, I spent six months working in a healthcare startup as the lead of research focused on data science and automation in healthcare.

Alessandro at the Grand Palace in Bangkok during a trip with friends.

Why did you make the leap from corporate to start-up?

Especially during 2023, there was this boom in what people were calling the "GenAI revolution," and big corporations were quick to jump on the hype train. However, it was hard to go beyond the hype and deliver real value. I was involved in an initiative between different units of the credit bureau to figure out what we should be doing, such as running some proof of concepts, but I found myself increasingly involved in politics. Different units didn’t want to collaborate, and as someone trying to help everyone, I felt stuck in the middle.

Although I was in an innovation unit, I felt like I wasn’t creating anymore. I love thinking about new solutions and testing ideas, but I was spending more time aligning stakeholders than actually innovating. I particularly enjoy being close to the research and creative process. That’s why I wanted to shift to a more agile environment, where we could move from ideation to production quickly, and everyone was working together toward the same goal.

Explain in lay terms your master’s research, “Asymptotic symmetries and the black hole information paradox.”

In modern theoretical physics, there are two worlds: the world where you include gravity and the world where you don’t. In the world without gravity, everything works beautifully with all our theories, but as soon as you add gravity, things start to break down. We don’t even know how gravity affects particles in the smallest scales.

My research dealt with black holes, which are the largest manifestation of gravity. Their gravity is so strong that nothing can escape, and it’s hard to understand the laws of physics near them. There is something called the black hole information paradox, which, roughly speaking, says that black holes can destroy information, which goes against one of the basic laws of quantum mechanics. When you burn something, for example, the information is scattered, but it’s still there; black holes seem to actually destroy it, which physicists don’t believe should be the case.

What I worked on was a theory from Stephen Hawking and his collaborators that suggested black holes might store information on their surfaces, or horizons, through what are called "supertranslation charges." The idea is that information might not be destroyed after all, but rather imprinted on the surface of the black hole.

Alessandro and his wife during a boat ride around Ilhabela, Brazil, one of Alessandro's favorite places

What originally sparked your interest in data science and physics?

I wasn’t always in love with physics or math. As a kid, I loved drawing and wanted to be an artist up until my second year of high school. But I met a friend in a Japanese class who was studying physics. He began telling me about some of the things he was learning. He would say things like, "Did you know vectors don’t need to be arrows? Sine and cosine are vectors," or "You can write the equations of mechanics without Newton’s Third Law with this thing called a Lagrangian" At first, I had no idea what he was talking about, but over time, I found it more and more intriguing.

At some point, I started reading Wikipedia articles to make sense of his comments. For example, I remember trying to understand how a star works; I thought it was really beautiful that its structure was fully determined by a handful of equations. Because I was interested in art, I was also drawn to aesthetics; I found physics to be aesthetically beautiful in a way that I hadn’t been exposed to in school. From there, I started studying physics on my own and really got into it.

What’s the most interesting paper you’ve read recently?