Jonas Gonçalves

About Jonas Gonçalves

Jonas Rodrigues Lima Gonçalves is a doctoral student in computer science at Örebro University. His research focuses on probabilistic machine learning, neuro-symbolic artificial intelligence, and tractable models for reasoning under uncertainty.

Research

He conducts research at the intersection of probabilistic machine learning, neuro-symbolic artificial intelligence, and knowledge representation. His main interest is in developing models that combine the flexibility of machine learning with the ability to perform efficient and mathematically well-defined reasoning.

A particular focus of his research is on probabilistic circuits and related tractable representations. These models represent complex probability distributions while allowing many probabilistic queries to be computed efficiently. His work investigates their expressive power, computational properties, and extensions beyond conventional probabilistic models, including models that allow more general algebraic and operator-valued representations.

More broadly, his research interests include:

• Probabilistic circuits
• Tractable probabilistic inference
• Neuro-symbolic artificial intelligence
• Knowledge compilation
• Probabilistic reasoning
• Knowledge representation
• Computational complexity

Before joining Örebro University, he completed his MSc in Computer Science at the University of São Paulo (USP), where he worked on neuro-symbolic methods combining probabilistic reasoning and knowledge compilation.

Collaboration

Jonas is interested in collaborations involving probabilistic machine learning, tractable probabilistic models, neuro-symbolic AI, knowledge representation, and computational approaches to reasoning under uncertainty.