About

Soumya Vadlamannati is an AI/ML Engineer at Bloomberg AI, specializing in NLP/ML. With a Master's degree in Computer Science from Carnegie Mellon University, Soumya has gained extensive experience in the field of AI and ML. At Bloomberg LP, Soumya worked as an SWE Intern (ML) with the Bloomberg LAW ML Team. Here, she performed Legal Motion Classification for Docket Analysis using Binary Relevance and Classifier Chains for classification in a Multi-Label setting. She also performed Unsupervised classification of legal-motion data using a two-step hierarchical classification model using Snorkel. Soumya used PyTorch, Keras, and scikit-learn to train deep models and worked on distilling Bert to Logistic regression and building Prototypical networks for Few-shot learning of legal motion classes. Soumya has also worked as a Teaching Assistant for Introduction to Deep Learning (11-785) and Distributed Systems (15-640) at Carnegie Mellon University. Her responsibilities included creating quizzes and assignments and holding office hours and tutorials. Soumya's education history includes a Master's degree in Computer Science from Carnegie Mellon University and a Bachelor's degree from the International Institute of Information Technology. Her tech stack includes AI, ML, NLP, BERT, Keras, Software Engineer, Scikit, Pytorch, Deep Learning, and Spring. Soumya has 2.78 years of relevant experience in the field of AI and ML.