Chethan Sanna Reddy

Project: HelaCloud • Development of robust data and image extraction techniques from Safety Data Sheets ( SDS - Pdf) using Natural Language Processing • Utilize Simple Transformers to accurately assign extracted data to their respective fields based on contextual information • Object detection using OpenCV in the Safety Data Sheets • Developing a Python Library to automate the evaluation of the ML model's output • Project lead for the ML and Data Labelling team of 5.5 resources

• Detected a set of electric components and text from Single Line Diagrams • Implementation of algorithm to match the object with corresponding text • Focus: Microsoft Azure, LabelImg, Object detection, Text extraction

• Tokenized raw data • Applied Long Shot-Term Memory (LSTM) to predict sentiment of the movie reviews with 81.5% accuracy • Deployed the model into production using AWS SageMaker

• Pre-processed images by normalizing, data augmentation • Achieved initial validation accuracy of 79.3% using custom CNN model and improved it to 90.3% using pre-trained MobileNet model

Tasks: • Researched on existing driver behavior models • Collaborated with other team to gather required CAN data • Classified (SVM, Decision Trees) road types with 97% validation accuracy • Clustered (K-means, Gaussian Mixture Model) different driver behaviours for each road type • Libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn (sklearn)

Tasks: • Developed mathematical model for success probability • Implemented and compared Epidemic Routing algorithm’s results with mathematical model for different cache size • Concepts & Tools: Opportunistic Networks (OppNets), Matlab

Tasks: • Based on requirements, researched, selected and integrated suitable sensors to collect data • Presented results with technical and management teams • Led the role of Scrum Master

Tasks: • Researched threat landscape and agents in connected cars • Proposed mitigation strategies and challenges in implementation and a framework for Business Resilience

• Manual testing (unit and integration), and a few configuration tasks with no issues in production environment • Created comprehensive test plans • Used SQL to retrieve, update and delete data from database • Mentored a junior colleague

• Manual testing and a few configuration tasks • Created test cases and test plans • Monitored production defects and fixed them • SQL queries to modify the database

• Performed comprehensive Regression testing • Monitored production defects and fixed them

Coursework: Convolutional / Recurrent Neural Networks (CNN/RNN), Generative Adversarial Networks (GAN), Natural Language Processing and Cloud Computing (AWS SageMaker, Lambda)

Coursework: Digital Image Analysis and Pattern Recognition and Data Compression (Machine Learning and Statistics)

Coursework: Data Structures and Object Oriented Programming in C++, Probability and Random Processes