Shivam Mehta
Research Scientist - Gen AI at KTH Royal Institute of Technology
Los Gatos, California, United States
Summary
🤩
Rockstar🎓
Top SchoolShivam Mehta is a research scientist and PhD candidate specializing in probabilistic machine learning for speech synthesis, currently applying generative AI at Netflix after research internships at Meta and Microsoft Research. With a decade of experience spanning academic research at KTH, Ghent, and ITMO, he bridges rigorous probabilistic modeling with practical system engineering from earlier Java/ETL and security roles. His recent work extends unimodal LLMs to multimodal audio understanding using novel discrete audio codebooks and contributed to an ICASSP paper, highlighting a knack for turning theoretical ideas into reproducible experiments. Based in Los Gatos, he combines deep academic training in applied mathematics with production-oriented productization of speech generative models, and maintains an active GitHub showcasing his research prototypes.
10 years of coding experience
2 years of employment as a software developer
Vivekanand SchoolDoctor of Philosophy - PhD Applied Mathematics, Doctor of Philosophy - PhD Applied Mathematics at KTH Royal Institute of TechnologyBachelor's Degree Computer Science, Bachelor's Degree Computer Science at Amity University, Greater Noida CampusResearch Natural Language Processing, Research Natural Language Processing at Ghent UniversityMasters Machine Learning And Data Analysis, Masters Machine Learning And Data Analysis at ITMO University
English, Swedish, Hindi, Russian
Github Skills (98)
mixing10
python10
diffusion-models10
mxnet10
text-to-speech10
voice-conversion10
deep-learning10
speech10
variational-autoencoder10
autoencoder10
paddlepaddle10
computer-vision10
nlp10
translation10
speech-synthesis10
Programming languages (6)
Github contributions (5)
shivammehta25/Matcha-TTS
Sep 2023 - Jan 2025
[ICASSP 2024] 🍵 Matcha-TTS: A fast TTS architecture with conditional flow matching
Contributions:6 releases, 14 reviews, 23 PRs in 1 year 4 months
deep-learningdiffusion-modeldiffusion-modelsflow-matchingmachine-learning
shivammehta25/Neural-HMM
Oct 2021 - Dec 2023
Neural HMMs are all you need (for high-quality attention-free TTS)
Contributions:1 release, 7 reviews, 23 PRs in 2 years 2 months
pytorchtext-to-speechdeep-learningmachine-learninghigh-quality
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