
Machine Learning Intern at Lab2Market Innovations, skilled in developing neural network algorithms for object detection and binary classifiers. Proficient in Python and TensorFlow, I successfully achieved fault detection with accuracy. My strong analytical abilities, solution focused approach and innovative mindset contributed to impactful projects, showcasing my expertise in machine learning and algorithm development.
Developed an object detection algorithm and a binary classifier CNN to identify and classify components on moving freight trains as healthy or defective.
Implemented an optical character recognition (OCR) system to read wagon numbers, with improvements for accuracy.
Implemented using Yolov5, Tensorflow with Keras, and EasyOCR based on Pytorch
Built a 20-channel temperature data logger using One-Wire sensors and a Raspberry Pi cutting wiring complexity and eliminating A/D converters
Used Grafana with InfluxDB for sleek real-time visualisation, and designed the system to scale effortlessly with more sensors or actuators.
Python programming
Supervised learning
Neural networks
Algorithm development
TensorFlow framework
Random forests
Keras library
Machine learning
Econometrics
Statistics
Scikit-learn library
Game Theory
Matching and Fair Division
Routing Games
Explainable AI
Co authored a paper titled "Differing Roles of Leisure and Productivity in GDP - a Machine Learning Based Comparative Analysis of Germany and USA" at International Conference on Emerging Techniques in Computational Intelligence (ICETCI 2025) organized by Mahindra University, École Centrale School of Engineering, Hyderabad, from 21-23 August 2025