Histopathology image classification: Highlighting the gap between manual analysis and AI automation

Ashish Vaswani (born 1986) is a computer scientist working in deep learning,^[1] who is known for his significant contributions to the field of artificial intelligence (AI) and natural language processing (NLP). He is one of the co-authors of the seminal paper "Attention Is All You Need"^[2] which introduced the Transformer model, a novel architecture that uses a self-attention mechanism and has since become foundational to many state-of-the-art models in NLP. Transformer architecture is the core of language models that power applications such as ChatGPT.^[3][4][5] He was a co-founder of Adept AI Labs^[6][7] and a former staff research scientist at Google Brain.^[8][9]

Vaswani completed his engineering in Computer Science from BIT Mesra in 2002. In 2004, he moved to the US to pursue higher studies at University of Southern California.^[10] He did his PhD at the University of Southern California under the supervision of Prof. David Chiang.^[11] He has worked as a researcher at Google,^[12] where he was part of the Google Brain team. He was a co-founder of Adept AI Labs but has since left the company.^[13][14]

Vaswani's most notable work is the paper "Attention Is All You Need", published in 2017.^[15] The paper introduced the Transformer model, which eschews the use of recurrence in sequence-to-sequence tasks and relies entirely on self-attention mechanisms. The model has been instrumental in the development of several subsequent state-of-the-art models in NLP, including BERT,^[16] GPT-2, and GPT-3.