Self-motivated Computer Science student with a strong interest in cloud infrastructure, DevOps, and AI/ML. Passionate about building scalable software and solving real-world problems through production-oriented development.
- Machine Learning & Deep Learning
- Explainable AI (XAI)
- Graph Neural Networks
- Cloud Infrastructure & AWS
- DevOps & CI/CD
- Backend Systems
- Real-Time Monitoring Systems
- Graph Algorithms & Optimization
- Distributed Systems
- Python
- Java
- C++
- C
- JavaScript
- SQL
- Bash
- HTML/CSS
- PyTorch
- PyTorch Geometric
- TensorFlow
- Keras
- Scikit-learn
- XGBoost
- CNNs
- Graph Neural Networks
- Streamlit
- Flask
- SHAP / LIME
- AWS (EC2, S3, SNS, CloudWatch, RDS, DynamoDB, EKS, ECS, Lambda, IAM, VPC)
- Docker
- Kubernetes
- Jenkins
- CI/CD Pipelines
- Linux
- GitHub Actions
- Git
- GitHub
- DockerHub
- Grafana
- Prometheus
- Power BI
- MySQL Workbench
Cloud-native OCR-based content moderation pipeline with Jenkins CI/CD, Dockerized deployment, AWS S3 integration, CloudWatch monitoring, and SNS alert workflows.
Multi-input CNN-based phishing detection system combining Character-Level CNNs and screenshot-based 2D CNN inference with Docker and Kubernetes deployment workflows.
GraphSAGE + PyTorch Geometric based forensic fraud detection system using temporal graph learning, GNNExplainer, Streamlit dashboards, and suspicious subgraph visualization.
Explainable AI system for semiconductor scaling analysis and real-time GPU FPS prediction using XGBoost, PyTorch, SHAP, LIME, and hardware-aware feature engineering.
Real-time disaster evacuation and shelter allocation optimization system using Dijkstra’s algorithm, graph-based routing, JavaFX dashboards, MySQL, and geospatial visualization.
- Google Cybersecurity Professional Certificate — Google / Coursera
- AWS Academy Cloud Foundations — AWS Academy
- AWS Cloud Practitioner Essentials — AWS Training
- Python for Everybody — University of Michigan / Coursera
- Java Programming Fundamentals — Infosys Springboard
- AI Agents 101: Building AI Agents with MCP and LangChain — AMD AI Developer Program
- AI Agents 201: Design to Deployment — AMD AI Developer Program
- ML Workshop Participant — NIT Goa
- Observatory infrastructure and telescope setup
- Planetary, nebulae, and galaxy imaging
- Variable star research contributions
- Built Dockerized Python image upscaling & denoising utility
- Organized educational and fitness activities for school students
- Coordinated waste pit installations to reduce local water pollution
- LinkedIn: https://www.linkedin.com/in/kashin-bharadwaj-9410552b2
- GitHub: https://github.com/Kashin10
- Email: kashinb029@gmail.com
Astronomy • Trekking • Football • Fitness • Guitar • Drawing