Greater Lexington Area
I’m a Machine Learning and Data Science Engineer with hands-on experience building predictive, generative, and optimization models across healthcare, cybersecurity, and network analytics. My Ph.D. work at Iowa State University focuses on applied AI—designing ML pipelines for real-time systems, reinforcement learning optimization, and data-driven decision models. I enjoy taking research ideas into production, combining strong theoretical grounding with practical deployment using Python, PyTorch, and cloud tools like AWS. I’m currently open to roles in Machine Learning Engineering, Applied AI, or Data Science, where I can contribute to model development, data strategy, and intelligent system design.
Working on edge computing and AI driven industrial solutions as part of the Toyota Vision Inspection Platform project at Hitachi Digital Services. Focused on edge application development, AI integration, distributed systems, and real world deployment of intelligent manufacturing technologies.
• Designed and implemented AI and machine learning solutions for real-time prediction, anomaly detection, and time-series forecasting in robotics and network analytics. • Built Python pipelines using Informer and GRU architectures for ultra-low-latency robotic motion prediction. • Tuned BBRv2 congestion-control algorithms in QUIC using Cloudflare Quiche and Linux tc, achieving 98 percent jitter reduction and 1.5× throughput gains. • Engineered reusable data-processing workflows in Python and PySpark for telemetry and sensor data, improving model development efficiency. • Containerized models with Docker and automated evaluation scripts to streamline deployment and performance benchmarking.
• Built Python and PySpark data pipelines to turn Zeek and Suricata logs into structured and enriched features for security and clinical network monitoring. • Designed and tested machine learning models for anomaly detection on clinical network traffic which reduced analyst triage time by 40 percent. • Deployed services in Docker and integrated outputs with OpenSearch and Kibana so security staff could search events, view alerts and validate model results. • Worked with security engineers to define alert thresholds, cut noisy events and document runbooks for investigation. • Wrote clear technical reports for leadership that showed model accuracy, false positive rates and impact on monitoring workload. • Prototyped a local AI assistant to search Zeek logs and detector output using Python and OpenSearch which improved investigator time to answer.
• Co-founded SabBachao, a grocery delivery and price-optimization platform in Pakistan • Built Python based pricing and product ranking scripts that compared local store prices and suggested the lowest basket for the customer. • Worked with a small team to track activation, repeat orders, and churn and reported weekly metrics
• Taught Python, C++, and embedded systems with a focus on data structures and how to use them in machine learning projects. • Supervised final year projects that used computer vision, IoT data, and simple neural networks for tasks such as object detection and remote monitoring. • Helped students build end to end projects from data collection to model training to reporting which is similar to industry data science workflow.