Edward Preble is a research data scientist in the Center for Data Science, where he applies machine learning, predictive modeling, text analytics, data visualization, and interactive reporting to solving problems in the social sciences, public health, and engineering sciences. Dr. Preble partners with RTI’s wide variety of subject matter experts to extract information from complex data sets and use advanced analytics to reveal new insights. In addition to applying data science to problem-solving, Dr. Preble contributes to research proposals and the publication of interesting technical results.
Dr. Preble is currently conducting data analysis for several studies to determine whether wearable electrocardiogram (EKG) sensors can provide advanced warning of seizures in children, detect mild traumatic brain injury or illnesses before symptoms appear. His work in image and video analysis involves using convolutional neural networks for image classification and rare object detection in video from unmanned aerial vehicles (UAVs), and developing software for quantitative image analysis and visualization of aerosol penetration of protective garments. He also performs financial risk simulations to compare and contrast financial metrics versus impact investing metrics for complex projects or investments using Monte Carlo techniques.
