About

Shobhana Ganesh is a highly skilled Engineer at Qualcomm with a passion for Natural Language Processing (NLP) and Deep Learning. She is currently pursuing her Master of Science degree in Computer Science at the University of Texas Dallas. With almost three years of relevant experience, Shobhana has worked on a range of projects related to speech and NLP, including research at Amazon AI and IISc. At Amazon, Shobhana conducted research on speech processing and Natural Language Understanding (NLU). She explored the application of acoustic embeddings for downstream NLU tasks and experimented with various deep learning models such as CNN, LSTM, and attention-based models. Prior to that, she worked as a Software Engineer at resumepuppy, where she built summarization models and keyword extraction to enhance resumes. Shobhana's education background includes a Bachelor of Technology degree in Computer Science from PES University and her current Master's program at the University of Texas Dallas. Her technical skills include NLP, Research Scientist, Deep Learning, AI, Software Engineering, NLU, and CNN. She is currently interested in applying deep learning for speech in downstream NLP tasks. Overall, Shobhana is a highly motivated and skilled Engineer with a passion for NLP and Deep Learning. Her experience in research and software engineering has given her a unique perspective on how to leverage technology to solve complex problems.