Litu Rout is a Senior Research Scientist at Google DeepMind with eight years of experience bridging foundational research and applied generative modeling. His work spans diffusion and rectified-flow generative models, optimal transport, and sampling/optimization for large-scale foundation models, building on a PhD in Machine Learning from UT Austin and a strong publication record including ICLR, NeurIPS workshops, CVPR, and TGRS. Prior to DeepMind he led research at ISRO on adversarial learning, super-resolution, and practical hyperspectral compression (including a granted patent), demonstrating an ability to translate theoretical insights into real-world remote sensing systems. He has repeatedly shown that optimal transport maps can serve as effective generative models in ambient image spaces and developed debiasing solvers that push state-of-the-art on unpaired super-resolution benchmarks. Based in Austin, he combines rigorous theory with hands-on engineering for scalable generative systems, often exploring underappreciated links between physical imaging problems and modern ML methods.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at The University of Texas at Austin
Bachelor of Technology, Electronics and Communication Engineering (Department of Avionics), Bachelor of Technology, Electronics and Communication Engineering (Department of Avionics) at Indian Institute of Space Science and Technology
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Litu Rout - Senior Research Scientist at Google DeepMind