Samuel Kriman
Applied Research Scientist - AI Applications
California, United States
Summary
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Rockstar🎓
Top SchoolSamuel Kriman is an applied research scientist at NVIDIA with nine years of experience building and integrating speech and generative AI models. He specializes in text-to-speech and multimodal systems, contributing notable implementations like GlowTTS into the widely used NVIDIA NeMo framework and shipping compact end-to-end speech networks with state-of-the-art quality. An alum of UIUC’s combined BS-MS program, he blends academic rigor from research labs with practical engineering at scale across multiple NVIDIA internships and full-time roles. Samuel’s work leans toward production-ready research—bridging model architecture, efficient inference, and framework integration—rather than purely theoretical advances. Based in California, he brings a track record of turning novel model ideas into maintainable code used by researchers and developers.
9 years of coding experience
3 years of employment as a software developer
University of Illinois Urbana-Champaign
Github Skills (8)
neural-network10
pytorch10
deep-learning10
large-language-models10
generative-ai10
asr9
machine-learning-models9
python8
Programming languages (2)
Github contributions (5)
NVIDIA/NeMo
Aug 2020 - Dec 2022
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Role in this project:
ML Engineer
ML EngineerContributions:76 reviews, 18 commits, 54 PRs in 2 years 4 months
Contributions summary:Samuel primarily contributed to the development of the GlowTTS model within the NVIDIA NeMo framework, a repository focused on generative AI, particularly for speech applications. Their contributions included the addition and refinement of the GlowTTS model, encompassing code additions for modules like `glow_tts.py`, along with several supporting files. The commits demonstrate a focus on model architecture, configurations, and ensuring the model's proper function within the NeMo ecosystem.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
sam1373/NeMo
Jul 2020 - Mar 2024
NeMo: a toolkit for conversational AI
Contributions:3 reviews, 13 PRs, 1691 pushes in 3 years 8 months
nlpconversationalconversational-aichatbotnemo
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