Nicholas Rasmussen, core audio AI signal processing developer and patent co-inventor (complex clipping) with Stanford faculty at Virufy, applies big data and machine learning to diverse challenges. His work ranges from AI-guided footwear impression analysis for criminal tracking to COVID-19 detection through cough sound analysis. As a University of South Dakota research assistant, he leverages AI, including neural networks like U-Net, to analyze large datasets and extract meaningful insights. Nicholas's research has been recognized with the Undergraduate Research Award and a National Science Foundation-Research Experience for Undergraduates (NSF-REU) selection, leading to co-authorship on two peer-reviewed publications. His ongoing work focuses on refining these technologies for real-world applications.
