Ganesh’s Ph.D. research focuses on creating model-based clustering methods that incorporate spatial information to categorize pixels in high-dimensional hyperspectral images. This approach enables precise pixel labelling, which can then be used to train classifiers for analysing future images. Additionally, he is developing a statistical model that accounts for seasonality to improve clustering of weather data. Through this research, Ganesh has gained a solid foundation in statistics and data science techniques for handling large datasets. His work
has also gained him an extensive programming experience in R and Python.

Ganesh holds a Master’s Degree in Data and Computational Science from University College Dublin, Ireland, and a Bachelor’s Degree in Electrical and Electronics Engineering from Anna University, India. Prior to his Masters, he worked as a Senior Analyst at a multinational corporation, amassing over five years of experience in Data Science. His expertise spans the development of various data-driven solutions, including Natural Language Processing (NLP) algorithms, Information Extraction Systems, Recommendation Systems, and Ticket
Classification Systems, leveraging advanced Machine Learning and Clustering techniques.

Areas of Interest: Model-based clustering and classification, Natural Language and Image Processing, High-dimensional data analysis, Neural networks.

12 week Training Placement: Multi-lane modelling using convolutional neural networks and conditional random fields, Valeo.

Developed a hybrid approach for multi-lane modelling that leverages a Convolutional Neural Network (DeepLabv3+) for initial pixel-level lane detection, followed by a statistical graphicalmodel, specifically Conditional Random Fields, to refine lane modelling and enhance detection accuracy.

Deliverables: Documented Python code and published a paper in the IS&T Electronic Imaging Conference 2022.

7 week International Placement: University of Alabama, Tuscaloosa, USA.

Collaborated with Dr. Volodymyr Melnykov to deepen the understanding of matrix-variate clustering for three-way data and contributed to developing a statistical model that incorporates seasonality for clustering weather data.

Professional Links:
LinkedIn : www.linkedin.com/in/ganesh-babu-ucd
GitHub: GaneshBabu1604 (github.com)
Google Scholar: Ganesh Babu