Deepak Jeganathan

Data-Driven Mechatronics Engineer | MSc Data Science & MSc Mechatronics and Automation

I am a highly motivated and skilled data scientist with a strong background in Mechatronics Engineering and a passion for extracting insights from data. I recently completed my MSc in Data Science at Kingston University London, where I gained expertise in data warehousing, ETL pipelines, data analysis, artificial intelligence and machine learning/deep learning, and visualization techniques. My academic foundation also includes an MSc in Mechatronics and Automation from the University of Strathclyde and a BEng in Mechanical Engineering with Automotive Design from Brunel University.

I am eager to apply my skills and knowledge to solve real-world problems and contribute to data-driven decision-making. My experience in designing, building, and testing robots, coupled with my data science expertise, allows me to approach challenges from a unique and valuable perspective. I am proficient in various programming languages and software tools, including Python, R, SQL, MATLAB, Simulink, ROS, and Tableau.

Here are some of my key skills and accomplishments:

- Developed a data warehouse and ETL pipeline to analyse UK airport punctuality data, utilizing Tableau to visualize key factors impacting flight delays and cancellations.
- Designed and built a 6-axis SCARA robot for use on the shop floor.
- Developed a collision avoidance system for a drone using real-time computer vision and machine learning algorithms.
- Successfully completed a project to levitate light and fragile objects using squeeze film levitation.
- Implemented an in-house solution to reduce vehicle tag errors at Jaguar Land Rover, resulting in significant cost savings.

I am a highly motivated and results-oriented individual with a strong work ethic and a proven track record of success. I am also a team player and I am confident that I can make a significant contribution to any organization.

If you are looking for a talented and ambitious data scientist with a passion for technology and a multidisciplinary background, I would be happy to connect with you.

• Machine Learning and Data Science Hands-on with Python and R, 01/01/21
• Raspberry Pi Workshop, Become a Coder / Maker / Inventor, 07/01/22

Blood Flow Analysis via Fluid Dynamics & AI

This dissertation project developed a sophisticated predictive model by integrating Computational Fluid Dynamics (CFD) with Artificial Intelligence. The core of the research involved creating high-fidelity simulations of hemodynamic systems to generate a rich dataset of blood flow characteristics. This data was then used to train and validate a machine learning model designed to analyze and accurately predict complex blood flow patterns under various physiological conditions. The project successfully demonstrated a powerful methodology for applying AI to complex biological systems, with potential applications in medical diagnostics and biomechanical research.

Key Skills: Computational Fluid Dynamics (CFD), AI / Machine Learning, Data Analysis, Predictive Modelling, Simulation.

Collision-Tolerant Drone

This project involved the end-to-end design and development of a drone capable of autonomous navigation in complex environments. The core of the project was creating a real-time collision avoidance system by integrating computer vision and machine learning algorithms within the Robot Operating System (ROS) framework. The work encompassed the complete project lifecycle, from selecting and integrating the necessary hardware (sensors, cameras, processors) to programming the drone's logic in Python. The system's performance and reliability were validated through a series of rigorous flight tests in simulated and real-world scenarios.

Key Skills: Robot Operating System (ROS), Python, Machine Learning, Computer Vision, Hardware Integration, Flight Testing.

Levitation of Light and Fragile Objects using squeeze film

For my final year project, I conducted a comprehensive design and simulation study on squeeze-film levitation, a novel method for the non-contact handling of fragile objects. Using Ansys Mechanical APDL, I performed a Finite Element Analysis (FEA) on four distinct geometries to determine their effectiveness. The simulations involved applying loads to replicate the force of piezoelectric actuators , successfully verifying that each design could form the "converging gaps" necessary for levitation. The analysis included mapping the resulting structural deformation and von Mises stress to validate the designs' performance and integrity.

Key Skills: Finite Element Analysis (FEA), Ansys Mechanical APDL, Mechanical Design, Simulation & Modelling, Stress Analysis.