Ranganath Krishnan
Distinguished ML Engineer And Director - AI Labs at Capital One
Hillsboro, Oregon, United States
Summary
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Senior🎓
Top SchoolRanganath Krishnan is a Distinguished ML Engineer and Director leading AI Labs at Capital One, with a 12-year industry research and engineering career focused on safe, robust, and trustworthy agentic AI. He previously spent over a decade at Intel Labs as a Senior Staff AI Research Scientist, driving uncertainty-aware LLM/VLM fine-tuning, RAG methods, and Bayesian XAI work that produced 20+ publications, 15+ patents, and an open-source Bayesian-Torch project with strong community traction. His methods have demonstrable impact—reducing hallucinations by ~24%, improving trustworthiness by ~30%, and delivering large gains in adaptation and compute efficiency for real-world deployments. Early systems work spans Android multimedia stacks, computer vision for 3D reconstruction, and embedded signal-processing sensors, reflecting a rare blend of low-level engineering and applied ML research. Based in Hillsboro, Oregon, he combines academic collaborations with product-focused delivery across finance and hardware platforms. Notably, his Bayesian-Torch framework introduced low-precision Bayesian modules, bridging practical performance needs with principled uncertainty quantification.
12 years of coding experience
17 years of employment as a software developer
MS in Electrical Engineering, Signal Processing and Communications, MS in Electrical Engineering, Signal Processing and Communications at Arizona State UniversityBachelor of Engineering (B.E.), Electronics & Communications Engineering, Bachelor of Engineering (B.E.), Electronics & Communications Engineering at B. M. S. College of Engineering
Github Skills (18)
uncertainty-quantification10
bayesian-deep-learning10
bayesian10
uncertainty10
bayesian-inference10
pytorch9
deep-learning9
bayesian-methods9
machine-learning8
statistics8
probabilistic-programming8
neural-network7
deep-neural-networks7
tensorflow7
data-science6
Programming languages (1)
Github contributions (5)
IntelLabs/bayesian-torch
Jan 2021 - Jan 2023
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
Contributions:6 releases, 4 reviews, 44 commits in 2 years
bayesian-layersbayesian-inferenceuncertainty-quantificationbayesian-neural-networkbayesian-neural-networks
ranganathkrishnan/bayesian-torch
Jan 2025 - Jan 2025
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks
Contributions:2 pushes in 1 day
pytorchdeep-learninginferenceneural-networkstorch
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