Welcome to BAINSA, Italy’s largest student-led AI research lab. We publish with the world’s leading AI researchers at the field’s top conferences, and we open that work to undergraduates across our partner universities.

BAINSA in figures

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Members across 0 partner universities

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Acceptance rate roughly one in ten applicants earns a place in our labs

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External collaborations with leading AI researchers, labs, and companies

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Events a year, from research talks to international AI festivals

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Projects run inside our labs every year, from idea to result

Fine Tuned for Success

BAINSA members on stage at WAICF
BAINSA members at WAICF
BAINSA members with speakers at WAICF
BAINSA members during a classroom session

Our Mission

BAINSA is Italy’s largest student-led AI research lab. We publish research papers at the top AI conferences with some of the world’s leading AI researchers, and we collaborate with the universities setting the field’s agenda. Access to research should not start after graduation: inside our labs, the strongest students at our partner universities do real research from their undergraduate years, on frontier AI and on what neuroscience still teaches us about learning.

Frequently asked questions

Working with the world’s leading universities and labs

Our method lives in the overlap.

On one side, the discipline of publishable research. On the other, a community that reviews, argues, and iterates. Neither is enough on its own, and every paper we are proudest of came out of where they meet.

BAINSA methodologyResearch-driven approaches and community-based learning overlap to form the BAINSA method.Research-drivenapproachMethodCommunity-basedlearning
The methodology combines research-driven work with community-based learning.

One research agenda, three labs.

BAINSA started as the Lab at Bocconi University and now runs three labs in Milan and Rome. Each lab recruits its own researchers and runs its own projects, and every paper they produce is published as BAINSA research.

BAINSA divisions: three ways of working.

The same question — how machines learn, and what brains still teach us — turned into papers you can read, systems you can run, and events you can attend.

Projects

Builds things.

Technical work in AI, neuroscience, and robotics, run as small teams that take a question from an idea to something that runs.

Analysis

Reads the field and argues with it.

Literature reviews, critical write-ups, and the ethical and societal questions that come with applying AI.

Culture

Brings the work into the open.

Events, talks, and the collaborations that connect students with people already working in the field.

Help curious people keep going.

Your support pays for the compute, the conference travel, and the space where our student researchers do the work.

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