About

Shefali Garg received her Masters in Intelligent Information Systems from Language Technologies Institute at Carnegie Mellon University, USA in 2019 with research focus on NLP and Speech. She completed her Bachelors in Computer Science from Birla Institute of Technology and Science, India in 2016.

She is currently working at Google DeepMind where she specializes in developing and refining large multimodal AI models leveraging Large Language Models (LLMs) alongside techniques like Parameter Efficient Fine Tuning (PEFT), Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human Feedback (RLHF). Previously, as part of Google’s Speech Research Team, I contributed to building large-scale Automatic Speech Recognition (ASR) models, with a focus on domain adaptation, data minimization through unsupervised learning, parameter-efficient fine-tuning, speech personalization, contextualization, and bias mitigation."

In parallel with her research, she writes about topics related to Artificial Intelligence and Machine Learning, and shares these resources on her website to make them accessible for everyone.

In her spare time, she loves playing sports, particularly basketball and badminton and also expressing herself through painting.

All opinions shared here are her own and don’t represent her employer.