As an Artificial Intelligence Research Scientist, I have explored a range of advanced algorithms across the Deep Learning spectrum. My experience includes working with ResNet, ConvNeXt, and SWIN for real-time video classification, PointNet, PointNet++, Point Cloud Transformer, and Point Transformer for 3D mesh regression, and BERT, MISTRAL, and LLAMA for uncertainty-aware retrieval-augmented generation. This diverse expertise highlights my ability to tackle complex AI challenges.I hold a Master’s in Data Science and Data Engineering, along with dual Bachelor’s degrees in Applied Mathematics and Computer Science, all Summa Cum Laude. My undergraduate honors include the Department of Mathematics and Statistics Outstanding Junior Award and the Dean's Medalist distinction. This solid academic foundation has supported my transition from software development to data science, merging theoretical knowledge with practical skills. With 3 years of combined experience in software development and AI, including roles in various Agile environments, I bring a well-rounded skill set. My background includes collaborating effectively with both small and large teams, iterating quickly, and delivering impactful results.My data science journey began with a project simulating college football commitments, achieving over 50% accuracy in predicting student-athlete choices among 100+ universities. In collaboration with Lawrence Livermore National Laboratory, I led a project on electrocardiogram classification, reaching over 99% accuracy and improving model interpretability. I also developed an innovative uncertainty-aware dynamic thresholding method for time series classification for a Parsons-funded project. Most recently, at Corvid Technologies, I adapted PointNet and PointNet++ for regression tasks involving cloud-level metadata.Specializing in uncertainty-aware autonomous decision-making, I am dedicated to uncovering insights within data. By combining statistical expertise with practical data engineering skills, I aim to provide not only accurate models but also transparent and understandable AI solutions, empowering users to confidently rely on and interpret the insights driving their decisions.