Problem Solver, Building intelligent AI-Native Scalable AI Solutions & Physical AI Systems
- AI-RAN & Private 5G: KPI forecasting, anomaly detection, network automation
- Cloud / MLOps: ETL pipelines, feature stores, CI/CD for ML, MLflow/Kubeflow
- GPU Analytics: RAPIDS/cuDF, XGBoost, with Accelerated & Distributed compute
- Physical AI: Sensor-driven robotics, edge TinyML, AI Augmented Embedded Sys
Python SQL PyTorch Airflow Sionna
Docker Kubernetes Terraform Spark dbt dbt-cloud
AWS Azure GCP RAPIDS XGBoost SHAP MLOps MLOps-CI/CD
Edge AI TinyML Jetson RAN Telemetry Distributed Compute
- AI-RAN 5G KPI Forecasting — accelerated ML + MLflow
- Telecom Churn EDA & ML — explainable churn with SHAP
- Private 5G RAN Pipeline — ingest → transform → parquet
- QPSK-Wireless-Link-Simulator — performance analysis
- Autonomous Parrallel Parker System — with IR sensors
- Breast Cancer Detection EDA & ML — Agentic SHAP email
- Telemetry pipelines for fiber ISP (GPON/EPON) and wireless RAN
- Accelerated ML (cuDF, XGBoost, PyTorch, distributed compute)
- Responsible & Explainable AI with SHAP, LIME, and agentic reporting
- Edge AI prototyping using Jetson + Pi + TinyML-sensor ecosystems
- Full-stack AI-Native RAN experimentation (Sionna + ML forecast loops)
Connect: LinkedIn • Email