— DATA SHINIGAMI —
K654321`AI/ML ENGINEER · DATA SCIENTIST · IEEE RESEARCHER
Kolkata, India
CS postgraduate student specializing in AI and ML, with hands-on industry experience in building scalable ML solutions, time-series forecasting, LLM orchestration, and production optimization. Published researcher with IEEE recognition. Passionate about turning complex data into actionable insights and building intelligent systems that make a real-world impact.
Technologies and tools in my Zanpakutō arsenal
Soul Society classified project archives
Implemented and benchmarked 6 optimization algorithms (CVFS-CMA-ES, Bayesian Optimization, TuRBO, SAASBO) for cointegration-based basket trading. Achieved 3.851 Sharpe ratio with CVFS-CMA-ES and 63.76% total return with Bayesian Optimization.
End-to-end MLOps book recommender using collaborative filtering with automated data pipelines, Airflow orchestration, DVC versioning, FastAPI services, React frontend, Docker deployment, and Prometheus/Grafana monitoring. Reduced manual operations by 80%.
Designed DNN framework with AlexNet and ResNet-v2 for automated fruit grading, achieving 99% accuracy on 2.2K images and 98.33% accuracy with 0.9752 F1-score on 15.5K images.
Deep Learning-based AEMR system using YOLOv5–v8 achieving 99% accuracy, 94% precision, 93% mAP. Applied erosion and HSV correction on 466 images, reducing errors by 95% and saving 500+ hours annually.
Professional journey through the divisions
Netaji Subhas University of Technology
Jul 2025 – Jun 2027 · CGPA: 6.80Advanced DSA, Machine Learning, Deep Learning, NLP, Blockchain
Haldia Institute of Technology
Oct 2020 – Jul 2024 · CGPA: 8.65Time-Series Analysis, Probability & Statistics, Software Engineering, DSA, DBMS, OS
Designed DNN framework with AlexNet and ResNet-v2 for automated fruit grading, achieving 99% accuracy on 2.2K images and 98.33% accuracy with 0.9752 F1-score on 15.5K images.
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