Aman Chadha is a senior tech leader in GenAI and multimodal systems, currently leading post-training efforts for Gemini at Google DeepMind. With 13+ years of experience across Apple, AWS, Amazon Alexa, NVIDIA, and Qualcomm, he blends hands-on model development (LLMs, VLMs, agentic AI, RAG) with product-scale deployment and evaluation. He has an unusual combination of deep research impact—100+ papers, 5K citations, top conference awards—and practical engineering that powers on-device and cloud AI features. Aman has repeatedly built and managed cross-functional teams to deliver end-to-end ML lifecycles from data curation and synthetic data generation to fine-tuning and evaluation. His work has been recognized in mainstream outlets like Nature and The Washington Post, and he teaches and advises at multiple universities while maintaining public AI portfolios (aman.ai, aman.info). Based in Cupertino, he pairs rigorous academic credentials with a proven track record of shipping production GenAI at scale.
Software RAID Manager | C | Supports RAID 0, 1, 4, 5 and 10 | Capable of normal mode operation (no failures), working with one failed disk and restoring normal mode with a new disk
Contributions:21 commits, 16 pushes, 1 branch in 10 months
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Contributions:50 commits, 12 PRs, 107 pushes in 1 year 4 months
pythonpytorchsuper-resolutiongansgan
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