Niki Parmar

Niki Parmar is a former member of the Google Brain team who studies novel techniques in deep learning. The AI researcher is also involved in the application of generative models to machine learning (ML), image generation, and language modeling tasks.

Below, we’ll discuss the senior research scientist’s professional history to date.

Table of Contents

Education and early career

Parmar earned a Bachelor of Engineering at the Pune Institute of Computer Technology in India. Whilst there, she became interested in AI and ML after taking massive open online courses (MOOCs) from Andrew Ng and Peter Norvig.

She then completed a subsequent Master’s Degree in Computer Science at the University of Southern California. At USC, Parmar worked under Professor Morteza Dehghani and explored social science questions with ML and big data.

Google Research

Parmar joined Google Research in 2015 and worked as a software engineer for just over two years. Initially, she worked on end-to-end deep learning systems that created alternative ways to solve NLP problems.

As Parmar learned to harness the power of transferrable embeddings and end-task optimization, she became inspired to transition into a pure research role and contribute to advances in ML.

Google Brain

Parmar joined Google Brain as a Research Software Engineer in October 2017. She was involved in research into the idea of self-attention and how other inductive biases could be used to improve machine learning algorithms. Parmar was also involved in deep learning research for language understanding and vision.

Together with Ashish Vaswani, Noam Shazeer, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin, Parmar co-authored the seminal self-attention paper titled Attention Is All You Need.

Adept AI

Parmar left Google Brain in November 2021 and announced soon after via Twitter that “I’m grateful for the 6+ years I spent there, the peers and friends that are inspiring and the opportunities to push on some of the most important problems in AI.”

She then co-founded Adept AI Labs with Ashish Vaswani, David Luan, and various former employees of Google Brain and DeepMind. The start-up was described as an AI research and product lab with the intention to build useful general intelligence.

Luan had worked with both Parmar and Vaswani at Google with the trio credited with the development of the AI transformer architecture. Parmar currently serves as Adept’s CTO.

Key takeaways:

Niki Parmar is a former member of the Google Brain team who studies novel techniques in deep learning. The AI researcher is also involved in the application of generative models to machine learning, image generation, and language modeling tasks.
Whilst an engineering student at the Pune Institute of Computer Technology, Parmar became interested in AI and ML after taking massive open online courses (MOOCs) from Andrew Ng and Peter Norvig.
Parmar joined Google Research in 2015 and worked as a software engineer for just over two years. She then worked at Google Brain for another four years before co-founding the general intelligence start-up Adept AI.