About Me

Hi — I'm Emiliano.

I'm a machine learning researcher and engineer who enjoys working where theory meets practice, especially on problems that demand both technical rigor and real-world awareness. I'm currently completing my Master's in Applied Computing, where my work focuses on applied ML research, multimodal learning, and building experimental pipelines that are not only performant, but also reliable and interpretable.

My research journey

My research journey started earlier than most. During my undergraduate studies, I became deeply interested in how signals like speech, language, and behavior can reveal subtle cognitive and neurological patterns. That curiosity led me into applied research spanning speech analysis, audio processing, representation learning, and multimodal modeling—often in low-data, high-noise settings where careful experimentation matters more than flashy architectures.

Over time, I've grown particularly interested in designing efficient learning systems, understanding why models behave the way they do, and stress-testing them beyond headline metrics. I enjoy running ablations, probing failure modes, and asking uncomfortable but necessary questions like: Does this generalize? Can we trust it? What is the model actually learning?

Alongside research, I've worked in industry environments where ML had to translate into something usable. Those experiences shaped how I think about engineering: clean pipelines, reproducibility, and communication matter just as much as accuracy. I like being involved across the full loop—from data and modeling decisions to evaluation, documentation, and explaining results to different audiences.

What I care about

On a more personal note, I'll admit something: I've never been great at showcasing my own work. I tend to move fast, learn a lot, and then move on—sometimes before a project feels "perfect enough" to share. This site is my way of changing that mindset.

What you'll find here is not an exhaustive archive of everything I've done. Instead, it's a curated snapshot: selected research directions, representative projects, and experiments that reflect how I think, how I build, and what I'm excited about. Some pieces are polished; others are exploratory by design. All of them are intentional.

Outside of the technical details, I care deeply about being a good collaborator. I'm calm under pressure, honest about uncertainty, and genuinely enjoy helping others reason through complex problems. I take my work seriously, but I leave room for curiosity, humility, and the occasional dry joke—used responsibly.

If this gives you a clearer sense of who I am and how I approach problems, then it's doing its job.

Thanks for stopping by.