I am a Computer Science student bridging the gap between rigorous scientific computing and applied intelligence. Currently, I focus on building robust AI/ML/DL pipelines, scalable data architectures, and full-stack software systems tailored for high-impact domains like Healthcare, Finance, Agriculture, and Engineering.
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Applied AI/ML & Domain Engineering ── Deep learning models, LLMs, PINNs, and predictive systems.
PyTorchSciKit-LearnHealthcare (DICOM)GenomicsAgri-TechEngineering Simulations -
Data Systems & MLOps Pipelines ── Reproducible modeling, model tracking, and specialized data structures.
MLflowDVCVector DBsGraph Neural Networks / DBsPostgreSQL -
Full-Stack Software Engineering ── Building robust, type-safe, and highly scalable production architectures.
TypeScriptNext.jsNestJSPrismaFastAPI -
Scientific Computing & Simulations (Foundations) ── Low-level acceleration and mathematical / graphical systems.
CUDAC++FEM/FEAOpenGL / WebGL
📖 Always learning. Always building.