Akshay Jagadeesh, an Indian-origin neuroscientist with a strong background in brain research, has recently joined OpenAI as a research resident. This marks an important move from academic work in neuroscience to research in artificial intelligence. His work will now contribute to developing safer AI systems and using AI to support progress in health and medicine.
Jagadeesh has spent nearly ten years studying how the human brain works. He completed his PhD in Computational Neuroscience and Psychology from Stanford University, where he focused on how brain activity is linked to human thinking, perception, and behaviour.
Later, he continued his research as a postdoctoral fellow at Harvard Medical School for almost three years. He has also worked on advanced projects at the University of California, Berkeley, and Humboldt University in Berlin. These experiences have given him strong knowledge in computational models, neural activity, and human cognition.
I’m thrilled to share that I’ve joined @OpenAI as a research resident, focusing on safety research and AI for health.
— Akshay Jagadeesh (@akjags) September 7, 2025
After nearly 10 years studying the brain, I’m excited for this next chapter building AGI to accelerate medical progress and scientific research! #feeltheagi
Now at OpenAI, Jagadeesh will focus on two main areas. The first is AI safety, where he will work to make sure that artificial intelligence systems behave in a reliable and ethical way, and remain aligned with human values. The second area is the use of AI in science and medicine, where he hopes to create new tools that support medical research and innovation.
He believes that his experience in neuroscience will help bridge the gap between how humans think and how AI systems can support that thinking. By applying what he has learnt from studying the brain, Jagadeesh aims to help develop AI tools that are both useful and responsible.
His move reflects the growing connection between brain science and artificial intelligence, as researchers around the world look to human cognition as a guide for developing better AI technologies.
