Bala Rajakumar

Master of Computer Science

Computer Science

Arizona State University, Tempe, AZ

Bachelor of Engineering

Computer Science

Madras Institute of Technology

Goes Beyond Instructions—Takes Ownership, Designs, and Delivers Independently

“I had the pleasure of working with Bala when he joined my team fresh out of college as a Junior React Developer. From day one, he impressed us with his enthusiasm, adaptability, and hunger to learn. Though new to the professional environment, he quickly got up to speed with our codebase, tools, and the project’s architecture. What truly stands out about Bala is how he moved beyond simply following instructions, he took full ownership of tasks and even took the initiative to propose, design, and develop features almost independently. When faced with challenges, he sought out solutions proactively, asked smart questions, and made sure the features he delivered were of high quality. His contributions helped us move faster without compromising on stability or quality. Beyond his technical skills, he’s a great team player—punctual, receptive to feedback, and always ready to help others. I believe Bala has tremendous potential and will continue to grow into a senior-level engineer and key contributor on any team. I enthusiastically recommend him for any role involving React, front-end development, or more broadly in software engineering.”

AWS Certified Cloud Practitioner

Microsoft Certified: Azure Fundamentals

Cisco Packet Tracer

MLB-IoD: Multi-Layered Blockchain Assisted 6G Internet of Drones Ecosystem

Proposes the MLB-IoD ecosystem, integrating a Global Compliance System (GCoS) for secure drone take-off and route planning, and a Swarm Security System (SSe) for intelligent swarm access control. Combines machine learning and encryption to enhance security and compliance in IoD networks.

Nexus of 6G and Blockchain for Authentication of Aerial Devices

Introduces a blockchain and PUF-based two-way, location-verified authentication system for 6G aerial devices. Achieves high security with low computational overhead, enabling reliable data collection in challenging environments.

Hybrid-AI Blockchain Supported Protection Framework for Smart Grids

Presents HABPF, a hybrid AI model using RNNs and LeNet-5 CNNs with blockchain-based storage to secure smart grid communications. Achieves 96% accuracy in detecting cyberattacks, ensuring resilience against tampering.

Predicting Osteosarcoma using eXtreme Gradient Boosting Model

Proposes an XGBoost-based model for classifying osteosarcoma types using microscopic bone images. Achieves 94.84% accuracy, 94.83% sensitivity, and 97.41% specificity, reducing diagnostic time for pathologists.