FEBIN MARSHEL BABU SOUNDARA RAJAN

As a Data Scientist at DOTCONN with a foundational background in Mechatronics and Intelligent Systems Engineering, I specialize in architecting end-to-end machine learning, quantitative analytics, and large-scale data engineering solutions that transform complex datasets into actionable decision-support systems. My expertise spans the entire project lifecycle—from data ingestion, pipeline development, and distributed cloud computing to risk assessment, computer vision, and deploying robust MLOps architectures. Leveraging a comprehensive technical toolkit that includes Python, SQL, TensorFlow, PyTorch, AWS, Kubernetes, Git, and OpenCV, I am driven by the challenge of applying mathematics and engineering principles to build scalable, intelligent systems that enhance operational efficiency and create measurable business value. I am always eager to connect and collaborate with like-minded professionals across data science, AI, machine learning, and quantitative analytics.

• NVIDIA DLI Certificate for Fundamentals of Deep Learning
• Machine Learning with Python: Foundations.
• Deep Learning: Model Optimization and Tuning.
• C Programming for Embedded Applications.
• Introducing Robotic Process Automation - NASBA.
• Learning PLC Ladder Logic: 1 The Basics.
• Introduction to PLC and Industrial Automation.
• Level Up: Advanced Python.
• Raspberry Pi: GPIO.
• Computer Vision on the Raspberry Pi 4.

• Optimal Path Prediction for Autonomous Bots: This project trains a CNN-LSTM model for motion analysis, helping a bot determine the optimal path to reach a goal. Using optical flow (Lucas-Kanade), it captures spatial and temporal motion features. The model ensures smooth trajectory prediction, making it useful for navigation, object tracking, and robotics applications.
• Obstacle Avoidance training of Wheeled Bot using Reinforcement Learning: Leveraged NVIDIA Isaac Sim and Gazebo simulation environments, alongside PyTorch for reinforcement learning. This initiative focused on training a wheeled robot to autonomously navigate intricate terrains by iteratively developing strategies to evade obstacles and ensure collision-free movement. The project aimed to enhance the robot's operational autonomy and safety in dynamic environments.
• Autonomous Crop Monitoring System: Contributed to building a 4-wheeled robot for greenhouse monitoring. Led deep learning model development for pest detection, collaborated on parts design and managed communication protocols to ensure seamless integration and functionality of AI solutions with Raspberry Pi and Arduino platforms.
• Local AI Chatbot using Ollama: Developed a local AI chatbot using LLMs (Llama 3 via Ollama) with speech-to-text (STT) and text-to-speech (TTS) for voice interaction. Built with Tkinter, it enables real-time dialogue, emotional detection, and math solving (SymPy), leveraging multithreading for smooth performance.
• High-Accuracy Car Detection for Image Recognition: Built a car detection system using a custom ResNet-50-based model with PyTorch and OpenCV, achieving 96.7% accuracy in diverse images. Focused on robustness across varying lighting conditions, angles, and backgrounds.
• Reinforcement Learning for Optimal Agent Navigation: Implemented a Q-learning-based reinforcement learning agent in a grid-world environment, optimizing navigation to find the shortest path while avoiding obstacles. Addressed challenges in exploration-exploitation balance and reward sparsity.
• Two-Wheeled Self-Balancing Robot Simulation: Designed and simulated a self-balancing two-wheeled robot using a PID controller and Kalman filter in Simulink. Successfully stabilized the robot after disturbances, demonstrating effective control algorithms.
• IoT-based Automated Irrigation System: Developed an IoT-based irrigation system with secure network architecture, automating watering based on temperature and humidity sensors. Simulated in Cisco Packet Tracer, ensuring remote monitoring and cybersecurity.
• Mechatronic System Diagnostics: Solar Panel Tracking Upgrade: Enhanced a solar panel system by implementing a closed-loop tracking mechanism using LDR sensors, improving energy efficiency by optimizing sunlight exposure. Designed and simulated in Simulink to validate performance.
• Design and Analysis of a Centrifugal Compressor: Designed a centrifugal compressor using SolidWorks and AutoCAD, optimizing blade geometry for improved efficiency. Conducted CFD analysis in ANSYS Workbench to enhance performance metrics.
• Design and Fabrication of an Oil Skimmer Machine: Developed an oil skimmer using a rotating belt mechanism to remove surface oil efficiently. Constructed a durable frame with arc and MIG welding, integrating a motorized system with an alert feature for optimized operation.
• EcoKart (Electric Go-Kart Competition): Collaborated on designing and fabricating an electric go-kart, focusing on brake system optimization, wheel hub design, and lightweight fabrication using carbon fiber. The team secured a top-10 position in a national-level competition.
• IC Kart (125cc Internal Combustion Kart): Worked on designing and assembling a 125cc IC kart for a national competition, contributing to engine optimization, drivetrain development, and cooling system design. Successfully raced at the Madras International Circuit.

• Autonomous Crop Monitoring System Architect, European Universities in Egypt, 2023.
• Community Service Director, Rotaract Club of Guindy, 2019-2020.
• Professional Service Director, Rotaract Club of SRM Vadapalani, 2018-2029.
• Blood Donation Chairman, Rotaract Club of SRM Vadapalani, 2017-2019.
• Captain of EcoKart, SRM IST Vadapalani, 2019-2020.
• Captain of ICKart, SRM IST Vadapalani, 2019-2020.