Carnegie Mellon University · Biomedical EngineeringHe Lab
Bin He · Pittsburgh, Pennsylvania
Research Focus
Dr. Bin He’s lab focuses on developing advanced imaging techniques to help improve surgical outcomes for patients with drug-resistant epilepsy. They use innovative machine learning methods to analyze brain activity, particularly during seizures, with a goal of accurately identifying the areas of the brain responsible for seizures. This work could lead to better surgical planning and ultimately improve the lives of many patients suffering from epilepsy.
machine learningepilepsybrain imagingneural networkselectrophysiological source imagingnon-invasive techniquesseizure localizationhigh frequency oscillations
Research Aims
3AIM 01Develop a biophysically constrained deep neural network for imaging epileptogenic tissue.
AIM 02Create a machine learning framework to automatically identify pathological high frequency oscillations from EEG recordings.
AIM 03Validate imaging techniques against clinical findings and surgical outcomes in drug-resistant epilepsy patients.
Skills the Lab Values
electroencephalography (EEG)magnetoencephalography (MEG)deep learningdata-driven feature learningmachine learning model trainingbiophysical modelingscalp EEG analysissource imaging techniquesclinical data validation
Output against the department
Publications1,279top 3% of dept.15th of 595
this lab
most publishedleast published
Citations29ktop 10% of dept.59th of 595
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.