About Me
Bridging science and engineering to solve complex challenges
Experienced Lead ML Engineer and Research Scientist based in Barcelona, with a PhD in Computer Science and 10 years of experience in AI and data science. Having worked in both academia and industry, I have sharpened skills in data analysis, AI/ML development, and scientific experimentation. I cover the full spectrum from designing predictive models to engineering scalable solutions with modern frameworks and cloud platforms. My projects often leverage cloud infrastructure to maximize efficiency. Over my career, I have collaborated on a variety of initiatives, and my work has been published in scientific venues like Springer, Frontiers, and Nature.
Career Highlights
Building scalable ML and AI solutions and advancing research across multiple domains, companies and countries
Years of Expertise
ML and AI Projects
Lines of Code Written
Research Publications
Universities Worked At
Countries of Long-term Living
Featured Projects
Delivering ML/AI systems and research tools that solve complex challenges in healthcare, life science, and enterprise
A wavelet-based deep learning system that non-invasively estimates intracranial pressure from cerebral blood-flow signals, enabling accurate bedside ICP monitoring without surgical risk. Validated on 200+ hours of clinical data, the model achieves clinically actionable accuracy and demonstrates a scalable alternative to invasive neuro-monitoring.
An end-to-end AI system that automates outbound lead generation by scoring jobs, contacts, and companies using hybrid heuristic–embedding models. It transforms slow manual sourcing into a scalable, data-driven workflow that dramatically cuts time-to-lead from days to minutes while boosting targeting accuracy and conversion potential.
A hybrid machine learning pipeline that classifies tumor immune phenotypes from whole-slide histopathology images using deep nucleus segmentation, feature engineering, and AutoML-based cell classification. Achieving an 89% weighted F1-score, it enables automated adenocarcinoma slide analysis, reducing manual workload and supporting more precise, personalized immunotherapy decisions.
A multi-stage machine learning pipeline that detects and segments laser-induced tissue ablation from hyperspectral imaging data using PCA/t-SNE reduction, Faster R-CNN detection, and Mean Shift clustering. The workflow enables automated assessment of thermal damage across organs, improving diagnostic accuracy and supporting research in laser-based cancer therapy.
Expertise & Leadership
Bridging the gap between academic research and industrial-scale engineering to build high-performing technical teams
10+ Years of Advanced R&D
From a PhD in Computer Science to research roles across Europe's leading institutions: Pompeu Fabra, Sorbonne, ICFO, Politecnico di Milano, University of Leeds, Madrid Polytechnic, and UniTrento. Bridging fundamental research with practical applications in computer science, big data, AI and machine learning.
Medical Imaging AI
Developing advanced ML and AI systems for medical imaging across ultrasound, CT, MRI, hyperspectral, and time-series physiological data. Projects delivered for leading medical centers including Vall d'Hebron, Beth Israel Deaconess, Boston Children's, and the Institute for Image-Guided Surgery.
Scalable ML Systems
Building scalable ML and AI systems with AutoML, PyTorch, TensorFlow, LangChain, scikit-learn, MLflow, and DVC, deployed across AWS and Google Cloud. Integrating Generative AI with OpenAI, Qwen, Llama, and Stable Diffusion models for intelligent pipelines and workflow automation.
Technology Leadership
Serving as AI thought leader, driving strategic direction, architectural decisions, and execution across client and internal projects. Establishing long-term technical vision and aligning technological units around scalable, AI-driven innovation for sustainable growth and competitive advantage.
Cross-Functional Management
Leading and scaling a cross-functional department focused on AI, ML, autonomous agents, and automation. Managing diverse teams of developers, scientists, and product managers to deliver innovative solutions while fostering collaboration, mentorship, and continuous learning.
Applied ML & AI Across Industries
Developing applied ML & AI systems for insurance, diagnostics, and pharma with deployments involving AmTrust, CNA, Plateau Group, leading medical centers, and pharmaceutical companies like Bristol Myers Squibb, Boehringer Ingelheim, and Volastra Therapeutics.
Selected Clients
Helping companies build better software and scale their research and engineering teams
Let's Build What Matters
Whether you are looking to scale your AI capabilities, lead complex research initiatives, or build high-performing technical teams, I'm here to help transform your vision into reality