Vol. I | Spotlight
The Engineer's Portfolio

The Engineer Behind the Code

A conversation about creative problem-solving, machine learning, and building technology that matters

Interview by The Portfolio Magazine
September 2025

Quick Facts

  • Education BSc in Informatics Engineering, ISEP
  • Specialization Software Engineering, AI/ML
  • Location Porto, Portugal
  • Languages Portuguese, English

Some engineers live and breathe code around the clock. Susana Loureiro is not one of them. Her relationship with technology is more deliberate—she's selective about what captures her attention, approaching programming with the same thoughtful consideration she brings to everything else in her life. This perspective, grounded in logic but fueled by creativity when the right knowledge clicks into place, shapes how she thinks about building meaningful systems.

What emerges from this balanced approach is a unique fascination with artificial intelligence that goes beyond pure technical interest. For her, the appeal lies in the philosophical possibility that machines can think—not just process, but genuinely reason. It's this intersection of logical precision and creative potential that drives her work in machine learning, where she sees technology not as a replacement for human connection, but as a thoughtful enhancement to it.

What drives your approach to writing code—is it more about solving problems or building something elegant?
It's definitely both, but my first instinct is always problem-solving. However, I believe coding should go beyond just finding a solution—it should be about building something meaningful that genuinely helps people. I'm not interested in creating technology just for profit. What excites me is that in today's landscape, you can be as creative as an artist while working in fields that are fundamentally logical and mathematical. There's this beautiful intersection where creativity meets precision, and that's where I try to operate.
You're transitioning more into machine learning—what draws you to that field specifically?
What fascinates me most is the idea that machines can actually think—not just process, but genuinely reason through problems. It's absolutely mind-blowing. I often think of AI systems as being like incredibly logical learners. They follow patterns and rules in ways that mirror human thinking, but with this beautiful mathematical precision. I've always felt drawn to logical, systematic thinking, and there's something deeply satisfying about working with systems that operate on clear principles and rules. It's like finding a new way to connect and communicate, but through code and algorithms.
The best systems are those that hide their complexity behind an interface of simplicity.
How do you see your software engineering background helping you in machine learning?
My software engineering foundation gives me the ability to build complete, user-facing applications that actually help people in their daily lives. For example, I developed 'Her.'—a personal assistant app that demonstrates how ML can be integrated into practical tools. Having that full-stack development background means I'm not just working with models in isolation; I can create entire systems that bring machine learning capabilities directly to users in intuitive, helpful ways. It's about bridging that gap between the technology and real human needs.
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