Houman Safaai

Senior ML Research Scientist

Contact Information

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About

Houman Safaai earned his Ph.D. in Theoretical Physics from the International School for Advanced Studies in Trieste, Italy, and continued his postgraduate studies in computational neuroscience. He worked at the Italian Institute of Technology as a research fellow, studying various aspects of information processing in brain networks, cellular cultures, and neuromorphic chips by developing computational and theoretical methods and tools. Safaai then joined Harvard Medical School as a research associate, where he developed probabilistic inference and information estimation tools, such as vine-copulas, for high-dimensional multivariate data to study complex network-level neural mechanisms of sensory processing and decision making.

Research Focus

Safaai’s research focuses on leveraging advanced statistical and machine learning techniques and models to understand complex neural processes. He uses information theory, copula-based models, and deep-learning frameworks to analyze high-dimensional neural data, aiming to elucidate the neural population codes that underpin cognitive functions and decision making. His work explores different applications of AI in understanding brain activity and also uses biologically-driven insights from neuronal representations to design more effective AI systems. By bridging theoretical models with empirical data, his research aims to advance our knowledge of brain function and contribute to the development of next-generation AI technologies.