AI Researcher | Emotion-Aware Systems | LLM Architect | Ph.D. in Artificial Intelligence
Building human-centered, privacy-preserving, and explainable AI from the brain to the browser
Barcelona, Spain πͺπΈ
I'm a multi-domain AI scientist with a flair for solving complex real-world problems through LLMs, neurosignal decoding, and federated machine learning. Whether it's building real-time emotion engines, orchestrating scalable AI pipelines, or designing GPT-based education tools, I thrive at the intersection of research, engineering, and innovation.
π§ I build systems that are:
- π‘ Explainable β not just accurate, but understandable
- π Privacy-preserving β keeping data where it belongs
- βοΈ Scalable β from edge devices to HPC clusters
- π― Domain-specific β tuned to education, neurotech, and health
Role | Organization |
---|---|
𧬠Senior ML Researcher | Eurecat - Technology Center of Catalonia |
π AI Consultant | Tuttify.io β Edtech powered by emotion AI |
π§ LLM Research Consultant | Allen Institute for AI (AI2) |
π Project | π Description |
---|---|
Fed-ReMECS | Real-time federated emotion classifier (EEG, PPG, EDA) |
DFL Framework | Modular federated learning with Docker, MQTT, HPC |
CaamFace (Tuttify) | Facial affect detection for emotionally adaptive learning |
LLM Content Generator | GPT-4o-mini powered content engine with S3, MongoDB, FastAPI |
NeuroDash | Interactive dashboard for real-time biosignal visualization |
- π₯ Vicente LΓ³pez Research Award, Eurecat
- π Published in Springer, Frontiers, Methods, and more
- π¨βπ« Mentored students with AI/Neuro papers at top-tier conferences
π§© AI isnβt just about intelligence. Itβs about insight. Letβs make it meaningful.