Summary
Shobhana Ganesh is an engineer with 10 years of experience applying deep learning to speech and NLP, currently pursuing an MS at the University of Texas at Dallas and working at Qualcomm in San Diego. She has research and industry experience from AWS and IISc, where her work on overlapping speech, diarization, and acoustic embeddings contributed to ICASSP, Interspeech and JASA publications. Past roles include building summarization and keyword-extraction models for ResumePuppy and exploring CNN, LSTM and attention architectures for speech-to-NLU tasks. She blends academic rigor with product-focused engineering, often bridging signal-level speech processing and downstream language understanding. Notably, she has investigated speaker identification in child and infant speech—an underexplored area with practical implications for inclusive voice technologies.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Technology, Computer Science, Bachelor of Technology, Computer Science at PES University
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at The University of Texas at Dallas