About

Lucky Sunda is an Applied Scientist II at Jupiter, with a focus on machine learning and natural language processing (NLP). With 3.78 years of relevant experience, Lucky has worked on a variety of projects, including building a visual question answering architecture from scratch for a new dataset KVQA and achieving state-of-the-art results, as well as developing neural machine translation for low resource languages (English-Hindi). Lucky has also worked on Kaggle House Price prediction using linear regression, random forest, xgboost, GBM, and SVM. Lucky completed their post-graduation in Computer Science from the Indian Institute of Science (IISc), Bangalore. Their research project was a combination of formal verification and machine learning, where they exponentially reduced the solution search space of an existing learning algorithm for verification. Prior to their current role at Jupiter, Lucky worked as a Senior Software Engineer (ML) at Parabole AI and as a Research Assistant at the Indian Institute of Science. They are currently a Summer Intern at genxsoft. Lucky's education history includes a Master's degree in Computer Science and Automation from IISc and a Bachelor's degree in Information Technology from Assam University, Silchar. Lucky's tech stack includes ML, Python, NLP, BERT, SVM, XGBoost, deep learning, search, AI, Pytorch, Azure, Keras, and TensorFlow. With a strong background in machine learning and research, Lucky is a skilled data scientist and software engineer.