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Full-stack AI/ML engineer specializing in end-to-end ML systems, AI automation, LLM agents, and ML infrastructure — building systems that solve real-world problems at scale. |
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LangGraph-powered AI assistant integrated with Jupyter that automates data analysis, code generation, and ML workflow orchestration via natural language. Tech: LangChain, OpenAI, React |
Built real-time anomaly detection and severity-based incident classifiers on Kubernetes, reducing false alarms by 30%. Tech: TensorFlow, K8s, Prometheus |
Developed a time-series model with a 98.4% accuracy rate in detecting wetland degradation using Sentinel-1 satellite imagery, reducing field visit costs by 27%. Tech: PyTorch, Docker |
Disaster-response application enabling real-time resource sharing and coordination during crises. Tech: Node.js, React.js, MongoDB |
Developed a fully-featured Linux shell in C with built-in commands, I/O redirection, piping, and interactive editing features like command history and tab completion. Tech: C, Unix System Calls, GNU Readline |
CNN-based system for automated extraction of building footprints from satellite imagery, achieving a 96.2% F1 score. Tech: TensorFlow, QGIS |
MSc in Engineering Artificial Intelligence Specializations: Machine Learning, Data Analytics, and AI System Design Expected May 2025 |
Bachelor of Science in Computer Engineering Relevant Courses: Statistics, Calculus, Data Structures and Algorithms 2016-2022 |
I'm passionate about building AI systems that solve meaningful problems and always open to collaborating on
interesting projects at the intersection of AI, infrastructure, and real-world applications.
