At Galois, our research is pushing the boundaries of Artificial Intelligence (AI), Machine Learning (ML), and Data Science to solve complex, real-world problems. Integrating top-down, model-based understanding with bottom-up, data-driven insights, we design, develop, and deploy novel algorithms and inferential frameworks to achieve tangible impact in healthcare, cybersecurity, defense, and other critical domains.
We actively seek collaborators in the AI research community who are anti-bigotry, anti-eugenics, anti-misogyny, and anti-scientific racism. We care about AI risk, prioritizing research that mitigates actual and near-term risks over imaginary monster risks.
Why Galois?
- Safety and Verification: In the brave new world of generative AI, trust and reliability are key concerns. Galois has more than two decades of experience leveraging the mathematical rigor of formal methods to offer an unparalleled level of assurance in system correctness and security, uniquely suiting us to meet the challenges of trust in AI/ML.
- Human-Centered Design: We don’t just consider the technical side of software development; we consider the needs and experience of the human beings who will use it. Harnessing insights from cognitive science, human-factors, and psychometrics, we aim to build systems that users find helpful, reliable, and effortlessly intuitive.
- A Multidisciplinary Approach: Our team combines extensive formal methods experience with a mastery of AI/ML techniques and tools, human/machine teaming, multi-agent system design, cognitive science, and more. Our approach aims to address the challenge of trust-in-systems at multiple levels: technical, cognitive, and social.
