About Me

Hello, my name is Geoff Barrett, and I am the creator of GEBA Technologies. I am not sure what will come of this endeavor yet, but lets just see where it takes us. As you will come to learn from reading the content on this website, my interests are primarily science related (engineering, biotechnology, etc). 

My education is in Biomedical Engineering (B.S. from Drexel University) with a concentration in Neuroengineering. I chose that concentration as I have always been fascinated with the brain, and figured this would allow me to apply engineering principles to solve problems originating in the nervous system. My dream would be to work with Brain Machine/Computer Interfaces (BMI/BCI's), however that will more likely become a reality if I decide to pursue a Ph.D. A secondary, and more likely, goal of mine would be to be involved in developing affordable myoelectric upper-extremity prostheses. As 3D printing becomes more consumer friendly, I will most likely explore developing my own model. A tertiary goal would be exo-skeletons (mainly to provide quadriplegics with the ability to obtain some sort of "normal" locomotion), but then again I could become Iron Man. 

Currently, I am researching Alzheimer's Disease at Columbia University Medical Center. That being said, anything stated on this website is my personal opinion and not that of my employer.

Professional Experience

Columbia University Medical Center - Taub Institute
  • Developing VirtualMaze, a Virtual Reality treadmill for in vivo electrophysiology in Alzheimer's mice models (could theoretically be applied to any model that you want to analyze spatial memory).
  • Optimized large scale electrophysiology analysis by creating user friendly GUI's in MATLAB and Python (using PyQt).
Drexel University Neurorobotics Laboratory 
  • Created Koi Pond, a machine learning algorithm that was used to identify High Frequency Oscillations (HFO's) within human intracranial electroencephalography (iEEG) data of epilepsy subjects. The idea was that HFO's were a potential biomarker for epileptogenic tissue, and thus any discovery of this event in iEEG could lead the clinician to better determine where the seizure onset zone was (for tissue resection).
  • Spearheaded a research protocol delivering auditory tones to epileptic rat models in order to determine if there are any significant differences in sensory gating between the epileptic populations and control groups (also compared to schizophrenia models).