Summary
Kumar Ayush is a research-focused engineer blending 9 years of industry and academic experience in computer vision and machine learning, currently driving multimodal Health AI and foundation-model applications at Google. A Stanford MS/PhD researcher working with Stefano Ermon and Jure Leskovec, he has authored papers in top venues (ICLR, CVPR, ICCV, Nature Communications, Science) on self-supervised image/video representation learning, generative modeling, and data-efficient methods. Prior to Stanford he spent 2+ years at Adobe producing product-facing ML systems, 15 patents, and multiple publications applied to fashion, AR, and digital marketing. His work spans on-device computational imaging for Pixel phones to leading generative-AI efforts for consumer health, showing a rare mix of deployable systems and high-impact research. Award-winning since his IIT Kharagpur undergraduate thesis, he is particularly drawn to unsupervised learning in low-data regimes and simulation-to-real transfer. Open to conversations about research-driven roles that bridge foundational models and real-world product impact.
9 years of coding experience
4 years of employment as a software developer
English Physics Chemistry Mathematics Computer Science, English Physics Chemistry Mathematics Computer Science at Rajendra Vidyalaya, Jamshedpur
Bachelor of Technology (Honours) Computer Science and Engineering (Best Bachelor's Thesis), Bachelor of Technology (Honours) Computer Science and Engineering (Best Bachelor's Thesis) at Indian Institute of Technology, Kharagpur
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at Stanford University
English, Hindi