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Est. 2026 · Ourinhos/BR · Cork/IE

Where psychology
meets computation

A research and technology laboratory dedicated to applying machine learning, data science, and computational methods to the most pressing challenges in mental health and human wellbeing.

Company registration
Celue.lab Innovation Ltda
Legal type Limitada unipessoal (ME)
Founded 23 Feb 2026
NIRE 35269259260
Jurisdiction JUCESP · São Paulo, BR
Focus AI · data science · digital health
About the lab

Research at the boundary of mind and machine

Celue.lab Innovation is a research and development company focused on experimental science at the intersection of artificial intelligence, psychology, and digital health. Formally incorporated in February 2026, the laboratory's roots trace back to 2022 and 2023, when its founding researchers began combining psychological theory with machine learning techniques inside an academic environment — a pairing that was, at the time, unusual in the Brazilian mental health landscape.

What began as a university research group investigating whether computers could detect human emotions from visual cues has grown into a multi-study laboratory conducting investigations spanning psychosocial risk modeling, neuro-oncological AI, and computational epidemiology across 12 countries. The lab's corporate purpose, as registered with the JUCESP, is explicit: experimental research and development in physical and natural sciences, with a focus on artificial intelligence applied to mental health, data science, analytical software development, and digital health technology solutions.

2022 – 2023
First formal research project initiated inside a university setting: a computer vision system for human emotion detection, translating facial expressions into structured numerical data via Likert-scale scores. Co-authored with Alan Silva Martins, this work — published in Humanidades & Inovação in 2024 — established the lab's core interdisciplinary approach: psychological theory driving computational design.
2024
Expansion into large-scale field research. The first structured interview campaigns begin in Brazil, with 197 trained interviewers deployed across clinical settings in 37 municipalities of São Paulo and Paraná. Doctoral research formally begins at UNESP with a CAPES sandwich scholarship, anchoring the lab's scientific production to an international academic framework. Collaborative work extends to Chile with the Universidad de Chile and Universidad de Los Lagos.
2025
International research exchange at the University of Macau consolidates the lab's global reach. The Psychosocial Risk Index (IRP) enters validation with a dataset exceeding 1,000 structured interviews. A second major project receives ethics approval: a multimodal deep learning system for differentiating pseudoprogression from real tumor progression in high-grade gliomas. The lab presents at international congresses in São Paulo, Ourinhos, and Santiago.
Feb 2026
Celue.lab Innovation Ltda is formally incorporated under Brazilian commercial law, registered with the Junta Comercial do Estado de São Paulo. The company becomes the institutional home for ongoing and future research, technology transfer, and analytical software development in the health and social sciences sector.
Mission

Building instruments that translate complexity into action

The lab works from a clear conviction: the most important problems in mental health — early identification of risk, reduction of diagnostic uncertainty, equitable access to care — are tractable with the right combination of empirical rigor and computational power. Our research does not treat AI as an end in itself, but as a means of making clinical knowledge more precise, more scalable, and more honest about its own limitations.

Empirical depth
Every model begins with real data from real people in real clinical and community settings — not benchmark datasets. Field collection is central to everything we build.
Methodological transparency
We follow TRIPOD-ML, Radiomics Quality Score, and open validation standards. Interpretability is not an afterthought — SHAP, Grad-CAM++, and VIF auditing are built into the pipeline from the start.
Latin American voice
Most AI health research ignores populations like ours. We contribute data, models, and evidence from a context that is underrepresented in international literature — and that matters clinically and scientifically.
People

The researchers behind the work

LF
Luciano Ferreira Rodrigues Filho
Founder · Principal Researcher
Psychologist, educator, and doctoral researcher in Medical Biotechnology R&D at UNESP, with a sandwich period at the University of Macau (CAPES scholarship). Holds a Master's in Social Psychology from PUC-SP and undergraduate degrees in both Clinical and Organizational Psychology. His research spans 15 years, beginning in socio-historical psychology and labor studies before converging on the intersection of data science, AI, and mental health. Has published 23 peer-reviewed articles, 5 books, and 10 book chapters. Served as a public sector psychologist for nearly a decade, winning two Best Practices in Public Management awards from the State of Paraná. Visiting researcher at Universidad de Chile, Universidad de Los Lagos, and participant in seminars at the New School for Social Research (New York) and East Side Institute.
Clinical psychology Machine learning Biopsychosocial modeling Public health Biotechnology
AS
Alan Silva Martins
Researcher · Software Engineer
Systems analyst and full-stack software developer, currently based in Cork, Ireland, where he works as IT Support Technician at Erin College. Holds a Bachelor's degree in Information Systems and a technical diploma in Electronics. His professional background spans enterprise banking systems development at Tata Consultancy Services (Bradesco project), REST API and authentication system architecture, network infrastructure deployment, and administrative process automation. Co-author of the lab's foundational paper on machine learning for emotion detection, Alan bridges the gap between psychological research design and production-grade software implementation — ensuring that theoretical models translate into robust, deployable systems.
Software engineering Angular · Java · Node.js Computer vision REST APIs Network infrastructure
Selected publications

Recent scientific output

2025
Suicide in Chile: from macro to micro
Rodrigues-Filho, L.F.; Rojas, G. · Semina: Ciências Sociais e Humanas (Online) · v.46, e52394
2025
Artificial intelligence in identifying unusual clinical cases in mental health: an integrative biotechnology approach
Rodrigues-Filho, L.F.; Simões, R.P. · II Workshop Internacional em Biotecnologia na Saúde, Botucatu
2025
Identification of clinical and psychological profiles through principal component analysis and clusterization: symptom patterns, risk factors and access to healthcare
Rodrigues-Filho, L.F.; Simões, R.P. · 5º Congresso Internacional de Saúde Mental, Ourinhos
2024
Emotion detection using machine learning: assessment of effectiveness and applicability in different contexts
Rodrigues-Filho, L.F.; Martins, A.S. · Humanidades & Inovação · v.10, p.273
2023
A study on the application of the artificial intelligence model for the production of scientific knowledge: the boundary between the moral and the ethical
Rodrigues-Filho, L.F. · Sistemas de Informação (Macaé) · v.1, p.11–23