Manjunath Kudlur
Manjunath Kudlur is an AI systems builder whose work spans machine-learning infrastructure and speech recognition. He earned a computer science and engineering PhD at the University of Michigan in 2008 for Streamroller, a compilation and synthesis framework for streaming applications. At Google Brain, he worked on TensorFlow, whose team released it as open source in 2015; a coauthored systems paper appeared at OSDI in 2016, and he coauthored a 2018 paper on dynamic control flow before leading Cerebras's compiler software project in 2019. In March 2023, he was CTO of Useful Sensors when it announced a global partnership with OKdo for low-cost modules for presence detection, hand gestures and voice interfaces. He coauthored Moonshine speech-recognition models in 2024, specialized models for underrepresented languages in 2025, and Moonshine v2 in 2026; as of October 2026, he is co-founder and CTO of Moonshine AI, whose Moonshine Voice toolkit uses speech-to-text models he and the team created.
- Now at
- Moonshine AI
- Links
- Google Scholar
Timeline
-
2008
A University of Michigan PhD
He earns a PhD in computer science and engineering at the University of Michigan in 2008. His thesis is Streamroller: A Unified Compilation and Synthesis Framework for Streaming Applications.
-
2015–2016
TensorFlow at Google Brain
Google Brain releases TensorFlow as open source in November 2015. He coauthors the system paper that appears at OSDI in 2016 and works on TensorFlow within Google Brain.
-
2018
Dynamic control flow in ML
In 2018, he coauthors a EuroSys paper presenting a programming model for distributed machine learning with dynamic control flow.
-
2019
Cerebras compiler lead
In 2019, he is the technical lead for Cerebras Systems’ compiler software project, which maps neural networks to a wafer-scale accelerator. Before Cerebras, he works on TensorFlow at Google Brain and on compilers and programming-language research at NVIDIA.
-
March 2023
CTO at Useful Sensors
In March 2023, he is CTO of Useful Sensors as it announces a global manufacturing and distribution partnership with OKdo. Its small, low-cost machine-learning modules support presence detection, hand gesture recognition and voice interfaces.
-
2024
Moonshine speech recognition
In 2024, he coauthors Moonshine, a family of speech-recognition models for live transcription and voice commands. Moonshine Tiny uses five times less compute than Whisper tiny-en for a 10-second transcription, with no increase in word error rates.
-
2025
Specialized Moonshine models
In 2025, he coauthors Flavors of Moonshine, a suite of tiny speech-recognition models specialized for underrepresented languages.
-
As of October 2026
Moonshine AI CTO
In 2026, he coauthors Moonshine v2, an ergodic streaming-encoder ASR model that uses sliding-window self-attention for bounded, low-latency inference. As of October 2026, he is co-founder and CTO of Moonshine AI. Moonshine Voice uses speech-to-text models he and the team created.
Career
- NowMoonshine AICo-founder and CTO
- 2015–2016Google Brain
- Cerebras SystemsCompiler lead
- Useful SensorsCTO
Education
- 2008University of MichiganPhD
Sources and credits
Photo: We have no published photo of Manjunath Kudlur yet. Send us a free-licensed photo.
- CCCP: People
- Research at Google
- Speaker: Manjunath Kudlur: O'Reilly TensorFlow World | Machine Learning Conference
- Dynamic Control Flow in Large-Scale Machine Learning
- Useful Sensors Selects OKdo as its Global Single Board Computer Solutions Partner - Edge AI and Vision Alliance
- [2410.15608] Moonshine: Speech Recognition for Live Transcription and Voice Commands
- [2509.02523] Flavors of Moonshine: Tiny Specialized ASR Models for Edge Devices
- [2602.12241] Moonshine v2: Ergodic Streaming Encoder ASR for Latency-Critical Speech Applications
- GitHub - moonshine-ai/moonshine-v2
- About Moonshine AI


