Nikhil Buduma
Co-Founder & CEO at Ambience Healthcare
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolNikhil Buduma is a founder and AI-driven healthcare leader with 11 years of experience building intelligent systems that accelerate the transition to value-based care. As Co-Founder and CEO of Ambience Healthcare (and previously its Chief Scientist), he blends product leadership with hands-on machine learning expertise to deliver autonomous capabilities for clinical workflows. He co-founded Remedy Health and Lean On Me Peer Support, reflecting a consistent focus on healthcare impact and community-driven solutions. Technically grounded with BS and MEng in Computer Science from MIT, he has implemented deep learning models in open-source projects, including contributions to the well-regarded "Fundamentals of Deep Learning" code companion. Nikhil is comfortable shipping both research prototypes and production systems, translating academic rigor into pragmatic, regulated healthcare products. He pairs entrepreneurial grit with a rare mix of ML engineering and domain fluency that helps teams operationalize clinical AI.
11 years of coding experience
9 years of employment as a software developer
Valedictorian, Valedictorian at Bellarmine College PreparatoryBachelor of Science (B.S.) Master's degree (M. Eng) Computer Science and Engineering, Bachelor of Science (B.S.) Master's degree (M. Eng) Computer Science and Engineering at Massachusetts Institute of Technology
Github Skills (8)
neural-network10
machine-learning10
deep-learning10
tensorflow10
python10
mnist10
theano10
convolutional-neural-networks9
Programming languages (5)
Github contributions (5)
darksigma/Fundamentals-of-Deep-Learning-Book
May 2015 - Aug 2017
Code companion to the O'Reilly "Fundamentals of Deep Learning" book
Role in this project:
ML Engineer
ML EngineerContributions:143 commits, 133 pushes, 1 branch in 2 years 3 months
Contributions summary:Nikhil contributed significantly to the "Fundamentals of Deep Learning" book's code companion by implementing and refining deep learning models, specifically a logistic regression network and a feedforward neural network for MNIST dataset classification. The contributions include creating and modifying Python scripts to train and evaluate these models, experimenting with various hyperparameters like learning rates and L2 regularization, and integrating the Theano library for model development. Furthermore, the user worked on developing a convolutional neural network for the CIFAR-10 dataset.
pythondeep-learningfundamentalsmachine-learningtensorflow
pratheeknagaraj/traceless
Apr 2015 - May 2015
Contributions:41 commits, 4 PRs, 32 pushes in 13 days
securechatchat-system
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