I specialize in autonomous, end-to-end software systems, with a focus on data-engineering workflows, machine-vision pipelines, and reproducible computational methods. My work aims to bridge experimental requirements with robust, maintainable software infrastructures.
I was born in Sicily and trained as a neuroscientist and neuropsychologist across Italy and Germany. Over the last decade I have worked at the intersection of cognitive neuroscience, machine vision, and software engineering, focusing on advancing knowledge and research methods, efficiently and ethically.
During my PhD in Systems Neuroscience at the University of Göttingen, I worked on the electrophysiology of the macaque visual cortex and on the psychophysics of spatial attention. Throughout my PostDocs I built autonomous systems to turn cognitive training of non-human primates into gamified assessment and enrichment that allowed more efficient high-throughput research while enhancing ethical standards.
Today I lead the development of autonomous behavioral tracking and enrichment platforms at the Primate Cognition and Behavior facility at the German Primate Center.
I enjoy designing systems end-to-end: from CAD models and embedded hardware to data pipelines and user-facing tools for scientists, vets, and technicians. My work has led to open-access publications, new research infrastructure, and concrete improvements in animal welfare.
Outside of work I am a father of three, an amateur musician, and an aspiring game designer.
These Python-only metrics summarize the size, complexity, originality, and readability of my codebase. They are based on both curated and non-curated projects available on my GitHub profile.
I work at the intersection of science and engineering, building the data infrastructures, workflows, and computational tools that enable researchers to model and analyze complex systems at scale.
Leading the development of full-stack machine-vision platforms for high-volume, continuous behavioral tracking of primates, including 3D pose estimation, ID recognition, GPU-cluster orchestration, and structured data pipelines. Coordinating a team of engineers and scientists to deliver scalable, production-level systems used across multiple research groups.
Developed CNN-based detection and identification systems (>95% accuracy) enabling autonomous training and assessment of macaques. Designed gamified behavioral tasks increasing data throughput by ~30%, and integrated behavioral, neural, and eye-movement data into reproducible pipelines. Collaborated closely with veterinarians, caretakers, and technicians to translate research needs into deployed technical systems.
Designed and deployed autonomous auditory cognition and psychophysics systems for common marmosets, scaling training from 2 to 14 animals per day. Pioneered group-based cognitive training and enrichment protocols for rhesus and long-tailed macaques, reducing the need for animal isolation and improving welfare standards. Built multimodal acquisition pipelines for long-term studies.
Conducted single-neuron electrophysiology in macaque brain area MST, mapping multidimensional motion selectivity. Investigated human microsaccadic eye movements in visual attention and developed early autonomous touchscreen-based cognitive devices for captive monkeys—now foundational for multiple research platforms at the institute.
A selection of projects across neuroscience, machine vision, and autonomous systems.