Adam S. Charles,PhD

Assistant Professor

Specialization: Computational approaches and mathematical modeling for processing and analysis of neural data


Johns Hopkins Whiting School of Engineering

3400 N. Charles Street

Clark Hall rooms 301 & 307

Baltimore, MD 21218


More Info

To understand the brain, powerful imaging and algorithmic tools need to be developed to meet the unique signal processing and machine learning challenges posed by neurophysiological data, neural imaging, and computational neuroscience. 

My lab aims to create the next generation of imaging systems and analysis tools capable of overcoming the difficulties posed by the high dimensionality and complexity of neural activity. This goal spans the development both of advanced recording technologies via collaborative designs of hardware and algorithms, and computational and theoretical frameworks for understanding biological and artificial neural systems. 


My lab approaches these topics by performing highly collaborative research that draws on both theory- and data-driven philosophies. Specific lab interests span 1) advancing the capabilities of specific technologies, for example multi-photon calcium imaging, via new data science and signal processing methods 2) the theoretical analysis and development of important models in neuroscience, such as recurrent neural networks, and 3) building off these areas to create more general-purpose data science advances with broader impact in applications beyond neuroscience.


To advance neuroscience discovery by uniting neuroscience, engineering and computational data science to understand the structure and function of the brain.