Computer science, software, and research
I hold a Ph.D. in Computer Science from the University of Buenos Aires. My work sits across software, artificial intelligence, cognitive science, and technology transfer; since 2024 I have been working at Mon Ami.
I combine hands-on software work with an academic background in computational models of learning and experience in the public sector.
I have worked on commercial products used by large and distributed teams, with extensive Ruby on Rails experience. I care about scalable systems that are simple to use and useful to the people who operate large volumes of data every day.
My research connected artificial intelligence, probabilistic programming, cognitive science, and language of thought models to study how people learn from sparse data.
At CONICET, I led the Technology Transfer Office with a team of more than 100 professionals across Argentina, connecting scientific capabilities with companies, public agencies, and concrete social needs.
I taught Operating Systems at the University of Buenos Aires and spent years working on computer-literacy programs in underserved neighborhoods.
A path across industry, research, university teaching, and public-sector management.
I work on product and software for a platform focused on services, organizations, and government teams dedicated to caring for older adults.
I rebuilt and coordinated technology-transfer teams across Argentina, first focused on solutions for the COVID crisis and later on deepening the connection between science, companies, government, and society at large. CONICET is Latin America's leading research institution.
Full-time scientific research period to complete my Ph.D. During the first weeks of COVID isolation, I collaborated with researchers and Argentine software companies on definitions for CuidAr, the public app that surpassed 10 million downloads in Argentina.
Software development and architecture for a commerce platform built with independent Ruby on Rails microservices for a Fortune 500 company during its international expansion. The platform powered KEEP Collective, administrative tooling, and sales experiences for more than 50,000 independent representatives.
Public-sector management, field work, and institutional coordination.
I joined as a Ruby on Rails engineer and grew into Managing Director. I led product, team, and infrastructure work on a platform with more than 2 million repositories, 10 million commits per day, and continuous delivery; annual recurring revenue grew from USD 24,000 to USD 3,000,000 and the team from 5 to more than 40 people.
I founded a small Ruby on Rails outsourcing company, delivering projects for clients in the United States, Spain, England, and Argentina. Assembla started as one of that company's clients.
Built an online tool for defining and improving business processes using Ruby on Rails when the framework was still in its early public versions.
ASP development for an application that exposed and managed large volumes of OLAP cube data for Exiros, the Techint Group procurement company with operations in 12 countries.
My academic work focused on computational models for understanding learning, memory, randomness, and generalization biases in humans.
I participated in an interdisciplinary environment combining computational neuroscience, computational linguistics, corpus analysis, interactive systems, and brain-signal analysis.
I worked with researchers across disciplines on decision-making, confidence, subjective beliefs, and computational tools for studying human behavior.
In 2017, I spent three months visiting Josh Tenenbaum's lab to deepen my work in computational cognitive modeling.
In 2018, I received this award for my doctoral work on language of thought models and learning from sparse data.
Abriola S, Tano P, Romano S, Figuera S. A logical framework to study concept-learning biases in the presence of multiple explanations. Behavior Research Methods.
Planton S, van Kerkoerle T, Abbih L, Maheu M, Meyniel F, Sigman M, Wang L, Figueria S, Romano S, Dehaene S. A theory of memory for binary sequences. PLOS Computational Biology.
Tano P, Romano S, Sigman M, Salles A, Figueira S. Towards a more flexible Language of Thought. Physical Review E.
Romano S, Salles A, Amalric M, Dehaene S, Sigman M, Figueira S. Bayesian validation of grammar productions for the language of thought. PLOS ONE.
Romano S, Sigman M, Figueira S. LT2C2: A Language of Thought with Turing-Computable Kolmogorov Complexity. Papers in Physics.
University training in computer science, doctoral research, teaching, and institutional participation at the University of Buenos Aires.
CONICET fellow. Advisors: Mariano Sigman and Santiago Figueira. Thesis: Language of thought models and techniques for machine learning from sparse data.
University of Buenos Aires. Thesis: Random generation in humans: a computational model.
Teaching assistant and later senior teaching assistant at the Department of Computer Science, Faculty of Exact and Natural Sciences, University of Buenos Aires.
Elected graduate representative at the Faculty of Exact and Natural Sciences council and later at the University of Buenos Aires Superior Council.
Volunteer, teacher, and director in a university extension project for underserved neighborhoods, funded by Exactas con la Sociedad and UBANEX.
Gold medal in ORT's metropolitan math competition, finalist in Argentina's national math olympiad, second place in SimuroSot Middle League at the FIRA Robot Soccer World Championship, and 127th place in Google Code Jam Latin America.