Humans of Andela

Annabel Castro, Rio de Janeiro

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Annabel Castro

Rio de Janeiro

“It’s important to incentivize women to jump into technology. This is not just a man's job; technology is for everybody.”

Annabel is a Senior Data Scientist based in Rio de Janeiro, Brazil. This is her story.

As a child, Annabel wanted to be a scientist and build robots that would save the world. Years later, as a grade A student, and driven by a thirst for knowledge, Annabel studied Computer Science at university before pursuing both a master’s and PhD in 3G technology. An accomplished technologist, Annabel has more than a decade of hands-on experience in research, where she has published over 30 articles and won 14 awards, including Google's Brazil Women in Technology Award, and has worked as a professor at the Institute of Technology INFNET.

It was always my dream to build a career around studying. I’ve researched technology and honed my craft for as long as I can remember. As a child, I wanted to become a scientist when I grew up, building robots that would help save the world.

As I got older, I realized I didn’t need robots. With the right amount of research and education, I could work with technology to make life better for other people.

You need to love what you do, and I’m blessed with having a job I enjoy. I started working with computer science in 2005 and I remember wanting to do absolutely everything tech related. Computer science, AI (Artificial Intelligence), robotics… I kept thinking, “how can I apply everything that I love to one job, so I work with every type of tech?” I decided to pursue computer science at PUC Minas University and try my hand at all forms of technology.

My first class was coding. I studied C++ and I remember my teacher discussing how to build a coffee machine into an algorithm. I was totally confused; applying a coding language to a household object made no sense. But gradually, logic kicked in. I tend to over think things, but I soon realized that if I could focus my mathematical brain, it could be the perfect partner for technology.

When you study and work in computer science, logic is your best friend. You must be more focused and proactive to solve problems.

One challenge I was determined to take on was understanding how 3G networks worked. I was driven by a need to learn. I asked my teacher: “‘how can I explore 3G?”’ She said, “don’t just focus on 3G, look to the future… learn about 4G too.”

I wanted to understand how things work, and to do that, I had to focus on what was coming next.

My main obstacle at this point in my studies was my English skills; my English was poor. I was an undergraduate student, still very young, and I had never had the chance to practice either speaking or writing English. I ended up using Google Translate to communicate with English speakers.

I knew I would have to solve this problem by myself. But I do love a challenge. I started watching films and videos with subtitles in English. As I was learning more about tech, I was using my research skills to perfect my English. Both 3G networks and English were studied in tandem!

As my English improved, so did my 3G knowledge. I started applying artificial intelligence research to my 3G work, and I completed and submitted my final paper on “Simulation and Analysis of Call Admission Controls in 3G UMTS Networks.”

Back in 2007, working in 3G, AI was the next logical step in my research. I began a masters, again at PUC Minas, where I conducted all my undergraduate research and studies. I respected my advisors and knew I had more to learn from them.

As my master’s in computer science and informatics reached the final stage, I decided to start a PhD.

I submitted my PhD application to a university in Denmark because I wanted to see if I was good enough to be accepted. They made me an offer, but I’m very connected to my work and family life in Brazil. Brazil is my home, and I’d made such great strides in my research at PUC Minas. I decided to stay in Brazil.

And then I applied to UFMG.

UFGM is the only university that had a PhD program connected to how artificial intelligence applies to sensor networks and is known all over the globe, so I thought “I'm going to apply there as well. Just let me see if I'm good enough to be there too.”

And I was.

In 2009 I received two scholarships to study at UFMG, specializing in vehicular networks.

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Soon after I began my studies, my advisor suggested I focus on algorithms, and how to solve and manage traffic congestion, via real-time data on traffic conditions through map services, using AI. I loved my research, and deciphering how cars can communicate between themselves and different infrastructures all over the road.

I developed a one model for this, a natural ML (Machine Learning) algorithm that uses Bayes' Theorem to predict road congestion. Using predictions, we can identify and plan for traffic congestion ahead of time. We can use data to build an ML model to predict whether there will be congestion in the future or not and if there will be, how we can suggest new routes so motorists can avoid traffic jams, but without causing panic and more chaos.

In 2009, thanks to my 3G research, I was the proud recipient of the Google Brazil Women in Technology Award. It was a game-changer in both my career progression and my industry visibility. I’ve won 13 more tech awards throughout my career.

I really wanted to do something that would benefit my home country, so I used my research to analyze fog, and why it is an important resource for forests.”

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By 2014, I’d consulted for different organizations, including Microsoft. At Microsoft, I moved into climate change, specifically how it was negatively affecting the health of forests in Campos de Jordao City, Brazil. I really wanted to do something that would benefit my home country, so I used my research to analyze fog, and why it is an important resource for forests. We used sensors throughout the forest to monitor roots, tree trunks, leaves and humidity.

The sensor values were submitted to a cloud system on Azure that went to Microsoft and then based on these elements we built one model to identify and predict how climate change, and the reduction of fog, was impacting the forest.

By 2021, I’d worked with networks, vehicles, and the climate. I decided I needed a change, and this time I wanted to focus on working with people.

I had heard so many positive things about Andela through several friends in the tech industry in Brazil, and decided to try a new, human-orientated career path. I knew Andela had expanded to Latin America after success in Africa, so I thought, why not give it a try? Soon after, I was matched to my current role, working as a Senior Data Scientist for a leading media agency.

I have a natural growth mindset. Currently, I’m working on how we can apply machine learning models to improve marketing, finding new ways to connect with audiences. I love discovering how people think, and what makes them seek out companies or products. It’s fascinating. As a data scientist, you always want to find an answer to a problem. Should a company invest more in social media? Should they change their business strategy? I really enjoy helping people think outside the box, and find new ways of doing things, to help themselves, their company, and society.

Andela is people orientated, so it felt a natural fit for me in how I want my career to progress. The community of technologists in Brazil is very welcoming. I’m even working on the same team as other Andelans, and it’s lovely to have that connection.

To win, you must be willing to take a risk, and even to fail.”

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Being remote allows me to focus on my job, and the time I save commuting allows me to write, research, and get my work published in over 30 global tech journals and publications. I’ve also had the opportunity to travel to speak at conferences, meeting up and coming tech innovators.

I’ve always been a high achiever, but you can’t go into a project aiming for the highest marks. That isn’t a winning strategy. To win, you must be willing to take a risk, and even to fail. When I was studying for my masters, and then my PhD, I realized that I didn’t need to aim for 100% to get an A grade. I estimated that I could aim for 90%, risking 10 points but still achieving my goal. In the end, I got 97%. That’s the thing you need to think about; focus on how much you can lose to achieve a result, not how much you will gain.

You can’t predict everything, but you can always try your best to solve a challenge. Every day, I focus on giving my all to my work, and to those around me. That is one thing I can predict.

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