Chethan Sanna Reddy

Project: HelaCloud Led a 5.5-member labeling team, defined QA standards, and built scalable annotation workflows. Developed end-to-end SDS automation pipelines and deployed NLP/LLM models to extract structured data from PDFs. Implemented active learning, cutting manual labeling by up to 70%. Built a FastAPI backend with async processing, distributed jobs, Dockerized deployments, PostgreSQL storage, secure JWT auth, enterprise integrations (e.g., SAP), and production monitoring.

• 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

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

Project: Towards a Smart Factory – Digitization for the Workshop Tasks: • Ran Scrum ceremonies and removed blockers to keep sprints on track • Enforced Scrum practices and aligned team, product, and stakeholders

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: Machine Learning and Statistics

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