am an AI Engineer and Data Scientist who designs, builds, and deploys high-impact machine learning solutions, from foundational research to production-ready applications.
My value is unique: I operate at the intersection of academic rigor, product engineering, and cutting-edge AI specialization.
Academic Rigor (The “Why”): I possess a first-principles understanding of AI, validated by 8 Scopus-indexed international publications on Machine Learning (including BERT and CNNs). Unlike typical engineers, I don’t just use models; I deeply understand how and why they work.
Product Engineering (The “How”): As an Apple Developer Academy Alumnus, I am trained to ship high-quality, user-facing products. I led the development of a high-security FinTech SDK, integrating ARKit and CoreML for fraud detection. I am not just a researcher; I am a proven builder.
Full-Stack AI Toolkit (The “What”): I command the complete modern AI stack, enabling me to handle projects end-to-end:
Generative AI: LangChain, RAG, and performance-efficient fine-tuning (LoRA/QLoRA).
Machine Learning: Python, PyTorch, TensorFlow, Scikit-learn.
App & Data: Swift (SwiftUI/UIKit), CoreML, Go, SQL (MySQL), and NoSQL (Firestore).
I am an autonomous, high-performance engineer seeking challenging projects. If you require a partner who can bridge the gap between complex theory and a functional, scalable AI product, let’s connect.
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