Bio
Hamed received his PhD in Electrical & Computer Engineering from Johns Hopkins University. With his background in Artificial Intelligence, Machine Learning, Statistical Signal/Image Processing and passion in software prototyping and proof of concept, he is interested in methodology development and application of AI in neuroimaging, computational neuroscience, and interdisciplinary research and development.
Before joining Stanford, he worked a Data Scientist at World Bank Group in Washington, DC where he used his background and research skills leveraging AI for innovative solutions and showcase effectiveness of technology-driven solutions in real-world contexts through design thinking research and PoV prototyping, including Computer Vision, Generative AI (LLMs), and NLP.
During his PhD, he worked on introducing new approaches for assessing time-varying functional brain connectivity. Currently, as a Postdoctoral Research Fellow, his interests are focused on use of data driven techniques and machine learning for neuroimaging in particular for assessing functional connectivity.
Hamed has shown a track record of applying research and problem solving across various domains and its corresponding domain data such as Healthcare, Financial and Public Sector, Energy and Interdisciplinary Engineering domains.
