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Kartik Bhat

Kartik Bhat

Kartik Bhat is a founding engineer at , where he serves on the core protocol team with a technical focus on distributed systems and database storage. He has a background in deep learning, with previous engineering roles at NVIDIA and Vicarious, where he contributed to autonomous vehicle systems and neural network research. [3]

Education

Bhat is a graduate of Carnegie Mellon University’s School of Computer Science. [1] [2]

Career

Bhat began his career in deep learning and autonomous systems, working from 2018 to 2020 as a Deep Learning Engineer at NVIDIA on the Autonomous Vehicles team, where he focused on path perception for self-driving systems. He joined Vicarious in 2020 as a Research Engineer on the Neural Networks Vision Team, remaining until 2022, during which time the company was acquired by Google and later integrated into its robotics division, Intrinsic. In 2022, he became a Founding Engineer at , contributing to the core protocol development of the with an emphasis on distributed systems and storage architecture. [1] [4]

Technical Contributions and Expertise

At , Bhat has focused on improving the performance and scalability of the core infrastructure. He has played a key role in the design and implementation of the Composite State Store, including development of a legacy database component to support -related keys that did not align with newer optimized data structures. His work has covered critical storage-layer pathways, including read and dual-write logic, Write-Ahead Log (WAL) integration, and pruning management to control long-term state growth. He has also contributed to performance enhancements such as parquet-based receipt storage leveraging DuckDB for efficient range queries, Pebble database compaction tuning, configurable I/O rate limiting for snapshot generation, and the introduction of asynchronous state snapshot pruning to reduce node performance degradation. In addition, he has contributed to updates supporting Inter-Blockchain Communication (IBC), strengthening the protocol’s cross-chain capabilities. Alongside his systems engineering, Bhat maintains involvement in AI and machine learning infrastructure, particularly in areas related to large-scale model training, inference optimization, and production deployment tooling. [2]

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