Research

Tensor Lab conducts and supports research across multiple domains within artificial intelligence and related computational sciences. Our work is guided by the conviction that advancing AI capabilities and understanding must go hand in hand.

Focus Areas

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Machine Learning Foundations

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We investigate core questions in machine learning theory and practice, exploring new architectures, training methods, and optimization techniques. Our goal is to contribute to a deeper understanding of how learning systems work and how they can be made more capable, efficient, and reliable.

AI Safety and Alignment

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As AI systems grow more powerful, ensuring they behave in accordance with human values and intentions becomes increasingly important. We study approaches to alignment, interpretability, and robustness that help ensure AI systems remain safe and beneficial.

Applied AI for Public Good

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We pursue applied research that demonstrates how AI can be used to address pressing societal challenges. This includes exploring applications in healthcare, education, environmental monitoring, and other domains where AI has the potential to create significant public value.

Open Research Infrastructure

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We develop and maintain computational infrastructure to support AI research. By sharing tools, datasets, and computing resources, we aim to lower the barriers to entry for researchers and institutions that might otherwise lack access to the resources needed for cutting-edge work.

Collaboration

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Tensor Lab welcomes collaboration with academic institutions, nonprofit organizations, and other research groups that share our commitment to advancing AI for the public benefit.