NAVEEN_PORTFOLIO v3.0.0
[INIT] kernel..............loaded
[OK] ROS2_STACK..........active
[OK] DJANGO_API..........ready
[OK] POSTGRES_DB.........connected
[OK] AWS_EC2_NODE........online
[OK] ACC2024_PAPER.......published
[OK] PARTICLE_SYS........initialized
Starting interface
Senior AI Engineer @ HCLTech · Open to New Opportunities

Naveen Kumar
Rajarajan

Currently building agentic AI systems and LLM-powered products at HCLTech. Background spanning GenAI, REST APIs, distributed backend systems, robotic fleet management, and control systems research. MS in ECE, Florida State University. Published at ACC 2024.

Django Node.js NestJS REST APIs PostgreSQL MongoDB TypeScript ROS2 AWS / Firebase
View Projects Research
terminal account_tree article
Experience
0 yrs
APIs Shipped
0
Published
ACC 2024 · arXiv
0x01 // Core Competencies

Scalable APIs, distributed systems, and modern backend architecture.

SYSTEM.SKILLS
dns

Backend Systems & API Engineering

Production REST APIs with Django, Node.js, NestJS, and Express.js. 50+ endpoints delivered across warehouse management, SaaS platforms, and robotic fleet control — with PostgreSQL and MongoDB at scale. Strong focus on security, testing, and maintainable code.

Django NestJS Node.js Prisma PostgreSQL
robot_2

Robotics & ROS2 Systems

ROS2 pub/sub frameworks, 30+ topic publishers/subscribers, Docker environments, robotic fleet management, and real-time sensor integration. Published research at ACC 2024.

ROS2 Python / C++
cloud

Cloud & Infrastructure

AWS EC2 deployments, S3 storage, Firebase Auth and Firestore integration. Scalable Docker-based environments on Linux with full CI/CD pipelines.

AWS Firebase Docker

Full-Stack Product Delivery

End-to-end ownership — from database schema design and API development to deployment, security hardening, and frontend-backend integration. Led teams at TCS and Smazee shipping warehouse management, SaaS, and IoT-integrated products.

APIs Shipped
50+ endpoints
Experience
4+ years
Databases
PostgreSQL · MongoDB
0x02 // Published Research
ACC 2024 Control Theory arXiv

Stable Teleoperation under Time Delay using Wave Variables & Smith Predictor

Published at the 2024 American Control Conference (pp. 4365–4371). Passivity-based control framework combining wave variable scattering with Smith predictor techniques for stable adaptive control of a lead vehicle in multi-vehicle platoon formation under high communication delays.

N. Rajarajan, A. Sharifi · Florida State University CAPS Lab · IEEE Xplore: 10.23919/ACC60939.2024.10644849
arXiv open_in_new IEEE Xplore open_in_new
Research Concept — Teleoperation Architecture
MASTER Lead Vehicle WAVE ENCODE NETWORK DELAY Δt Smith Predictor WAVE DECODE SLAVE Platoon Passivity-Based Feedback
Key Contributions
01
Wave Variable Scattering
Passivity-preserving transformation maintaining energy stability across variable network delays
02
Smith Predictor Integration
Predictive compensation technique reducing latency impact on platoon control stability
03
ROS2 Simulation
Multi-vehicle consensus validated in ROS2 simulation environments with variable delay injection
0x03 // Robotics Lab

ROS2 System Architecture

Live-style node graph of the ROS2 communication framework built at FSU CAPS Lab. 30+ topics, Docker environments, deployed on AWS EC2.

MISSION 1
Activate all nodes

Click each ROS2 node once to bring the lab online and unlock the robotics achievement.

MISSION 2
Route /cmd_vel to slam_toolbox

On desktop, click robot_controller, then drag a live packet path to slam_toolbox. Mobile skips this mission automatically.

NODE GRAPH — /rosnode list
Publisher
Subscriber
Topic Flow
Node Inspector
Select a node in the graph to inspect topics, message types, and runtime frequency.
System Metrics
Active Topics 30+
Pub/Sub Nodes 8 nodes
Msg Rate 48 Hz
ros2 topic echo
_
ROS2 Humble Python 3.10 C++17 Docker + Linux AWS EC2 S3 Map Storage Nav2 Stack SLAM Toolbox
0x04 // Skill Profile

Competency Radar

A multi-dimensional view across backend engineering, databases, cloud infrastructure, robotics systems, and research depth. Each axis reflects hands-on production experience and published work.

Backend APIs (Django / Node.js / NestJS)92%
Databases (PostgreSQL / MongoDB)88%
Cloud / DevOps (AWS / Firebase / Docker)82%
Robotics / ROS2 (Python + C++)85%
Control Theory / Research78%
0
Years Experience
0
APIs Shipped
0
ROS2 Topics Built
0
ACC Publication
0x05 // Full Stack

Technology Skill Tree

A scroll-activated RPG layer for the stack: backend services, data systems, robotics tooling, and cloud infrastructure unlock in dependency order as the section comes online.

Skill allocation sequence enabled
SKILL POINTS ALLOCATED: 0 / 36