Hello, I'm Ragulan Karunanithi
Research Assistant | AI ML Enthusiast
Solving complex problems with machine learning and engineering innovations
About Me
Who I Am
I am a highly motivated mechanical engineering undergraduate at the University of Peradeniya with a passion for combining engineering principles with artificial intelligence to solve complex problems.
What I Do
I specialize in applying machine learning and computer vision techniques to mechanical engineering challenges. My expertise spans from traditional mechanical system design to cutting-edge AI implementations in engineering contexts.
Career Objectives
I am seeking opportunities where I can leverage my unique combination of skills to advance my career, particularly in roles as an ML engineer, Automobile engineer, or at the intersection of ML, Computer Vision, and Automotive engineering.
Core Skills
- Programming: Proficient in Python, MATLAB, and C++ for engineering and AI applications
- Engineering Design: Experienced in designing and simulating mechanical systems using SOLIDWORKS and Ansys
- Problem Solving: Strong analytical thinking with a focus on data-driven decision-making
- Research: Experience in computational fluid dynamics and predictive modeling
- Interdisciplinary Work: Skilled at integrating AI and machine learning into real-world engineering challenges
- Continuous Learning: Committed to staying updated with the latest technologies and methodologies
My Projects
Design and Development of Smart Fish Box Cooler
Developed a smart fish box cooler to maintain fish freshness during transportation. The design caters to the specific needs of fishermen, emphasizing durability, portability, and efficient temperature control.
Designing of an Automatic Kottu Roti-Making Machine
Designed and implemented a semi-automated machine inspired by existing food processing systems like koththu rotti cutting and fried rice machines used in China and Japan.
Enhancing Predictive Capabilities of Multiphysics Modelling Through Machine Learning
Researched the integration of machine learning with multiphysics modeling to improve predictive performance, initially focused on optimizing solar panel efficiency.
Hardware System for Bottle Count and Downtime Monitoring
Implemented a hardware-based solution using ESP8266 to count bottles in a manufacturing plant with a Python GUI (Tkinter) for visualizing bottle count and downtime statistics.
My Experience
Involved in the research project "CFD-based ROM (Reduced Order Model)", contributing to computational fluid dynamics simulations and predictive modeling.
Worked on full-stack web development projects, involving both front-end and back-end technologies. Gained experience in building scalable web applications.
Implemented a hardware system to monitor and store bottle counts in a MySQL database and developed an application to analyze downtime using that data.
Hands-on experience in developing and optimizing water treatment processes and pump maintenance systems within municipal infrastructure.
My Education
Focused on mechanical system design, simulation, and data-driven engineering approaches.
Participated in national-level competitions including Mathematics Olympiads and quizzes.
Achievements:
- Mathematics Olympiad
- Maths Quiz
Contact Me
ragulnithii@gmail.com
Phone
+94 765734486
Location
Malabe, Colombo