• Co-led a team in deploying AI / ML techniques to analyze antibody-protein interactions and enhance the development of new vaccines.• Architected and developed a graph convolutional network using Torch Geometric to model recognition between T-cell receptors and epitopes, achieving over 80% accuracy.• Managed the development team, ensuring expedited progress and adherence to project timelines and deliverables.

• Engineered a machine learning pipeline to automate real-time detection and prediction of cellular network degradation.• Created an ML classification tool in Scikit-Learn to identify network degradation in real-time with over 95% accuracy, significantly improving network diagnostics.• Constructed a PyTorch neural network to predict future cellular network downtime with over 60% accuracy, facilitating proactive issue resolution and improving network reliability.• Developed an AI-driven data analytics tool using NLP to process complex data analyses efficiently.• Leveraged SpaCy to build an NLP pipeline, translating plain-English user requests into specific mathematical operations for execution on user-provided databases.• Authored and filed a patent for the novel underlying software architecture of the NLP model.

• Developed advanced software solutions to block domains and URLs hosting illicit material.• Constructed Python tools and a comprehensive unit testing framework to automate the removal of extraneous URLs from AT&T’s database of blocked URLs, reducing database maintenance time by more than 30%.• Authored a deployment guide for using URL blocking tools, facilitating swift and effective integration for clients.• Formulated software to support Vehicle-to-Vehicle (V2V) communication of road hazards for Autonomous Vehicles.• Devised an ML algorithm in Scikit-Learn to predict the probability of accidents given current vehicle conditions.• Established a GPS framework to optimize hazard navigation and supply real-time incident alerts for first responders.

• Supported and produced software solutions for GNU Radio, an open-source DSP framework used in wireless communications.• Constructed CUDA software to accelerate critical signal processing operations by 10 to 20 times.• Developed a neural network in PyTorch to eliminate noise from RF signals, increasing signal quality by more than 10%.• Established a robust CICD pipeline in GitHub Actions, streamlining build and test processes for GPU-related projects.

• Designed software for SecureSense, a discrete spectrum analyzer used by the military to monitor RF spectrum usage.• Created a tool in Python to optimize the detection of low SNR signals, enhancing detection accuracy by more than 20%.• Engineered a visualization tool in JavaScript to produce dynamic spatial displays for detected signals, allowing users to locate emissions efficiently.