Researcher

Pavankumar Reddy Muddireddy

Also known as Pavan Kumar Reddy, Pavan Muddireddy

Pavankumar Reddy Muddireddy is a research scientist who leads audio research at Mistral AI and is the Voxtral lead. After co-authoring a 2017 Interspeech paper on zero-shot text classification, he completed an M.S. in electrical and computer engineering at the University of Illinois at Urbana-Champaign in 2018 under Dan Roth. He was among the authors of Pixtral 12B in October 2024, Magistral in June 2025 and Voxtral in July 2025, and of Ministral 3, Voxtral Realtime and Voxtral TTS in 2026. In March 2026, he spoke on the Latent Space podcast about the Voxtral TTS launch.

Works
10
Citations
49
h-index
3
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2017

    A zero-shot domain classifier

    In 2017, he co-authors the Interspeech paper "Zero-Shot Learning Across Heterogeneous Overlapping Domains" with Anjishnu Kumar, Markus Dreyer and Björn Hoffmeister. The text classification approach predicts which natural language understanding domain can handle a given utterance, including domains that did not exist at training time.

  2. 2018

    Entity typing thesis at Illinois

    He completes an M.S. in electrical and computer engineering at the University of Illinois at Urbana-Champaign in 2018, advised by Dan Roth. His thesis, "Fine-grained entity typing system - design and analysis", introduces a modular architecture for fine-grained typing of entities.

  3. 2021

    Updating a neural semantic parser

    In 2021, he co-authors "Overcoming Conflicting Data when Updating a Neural Semantic Parser" with David Gaddy, Alex Kouzemtchenko, Prateek Kolhar and Rushin Shah for the Workshop on Natural Language Processing for Conversational AI. The best method closes 86% of the accuracy gap between a naive data-mixing baseline and an oracle upper bound.

  4. October 2024

    Co-authoring Pixtral 12B

    In October 2024, he is among the authors of Pixtral 12B, a 12-billion-parameter multimodal language model trained to understand both natural images and documents. The model surpasses a number of larger models on multimodal benchmarks.

  5. June 2025

    Mistral's first reasoning model

    In June 2025, he is among the authors of Magistral, Mistral's first reasoning model. Magistral Medium is trained for reasoning on top of Mistral Medium 3 with reinforcement learning alone, and the open-source Magistral Small is released under Apache 2.0.

  6. July 2025

    Co-authoring the Voxtral models

    In July 2025, he is among the authors of Voxtral, which presents Voxtral Mini and Voxtral Small, two multimodal audio chat models trained to comprehend both spoken audio and text documents while preserving strong text capabilities.

  7. January 2026–March 2026

    Ministral 3 and Voxtral TTS

    In January 2026, he is among the authors of Ministral 3, a family of parameter-efficient dense language models in 3B, 8B and 14B sizes. In February 2026, he is among the authors of Voxtral Realtime, a natively streaming speech recognition model with sub-second latency. In March 2026, he is among the authors of Voxtral TTS, a multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio.

  8. As of October 2026

    Audio research lead at Mistral

    He is a research scientist at Mistral AI and leads its audio research. In March 2026, as the Voxtral lead, he talks with the Latent Space podcast about the Voxtral TTS launch, and in September 2026, he joins Tim Scarfe on Machine Learning Street Talk for a technical tour of Voxtral.

Career

  1. NowMistral AIResearch Scientist and Audio Research Lead

Education

  1. 2018University of Illinois Urbana-ChampaignM.S. in electrical and computer engineering

Most-cited works

  1. Zero-Shot Learning Across Heterogeneous Overlapping Domains2017 · Interspeech (USB) · 33 citations
  2. Pixtral 12B2024 · 8 citationsWith Alexandre Sablayrolles, Amélie Héliou, Diego de las Casas, Emma Bou Hanna, Nikhil Raghuraman and Romain Sauvestre
  3. Ministral 32026 · 4 citationsWith Abhinav Rastogi, Alexander H. Liu, Alexandre Sablayrolles, Amélie Héliou, Andy Ehrenberg and Andy Lo
  4. Magistral2025 · 3 citationsWith Alexander H. Liu, Alexandre Sablayrolles, Amélie Héliou, Andy Ehrenberg, Baptiste Bout and Baudouin De Monicault
  5. Overcoming Conflicting Data when Updating a Neural Semantic Parser2021 · 1 citations

Sources and credits

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  1. ISCA Archive - Zero-Shot Learning Across Heterogeneous Overlapping Domains isca-archive.org. Checked 20 October 2026.
  2. Fine-grained entity typing system - design and analysis | IDEALS ideals.illinois.edu. Checked 20 October 2026.
  3. Overcoming Conflicting Data when Updating a Neural Semantic Parser - ACL Anthology aclanthology.org. Checked 20 October 2026.
  4. [2410.07073] Pixtral 12B arxiv.org. Checked 20 October 2026.
  5. [2506.10910] Magistral arxiv.org. Checked 20 October 2026.
  6. [2507.13264] Voxtral arxiv.org. Checked 20 October 2026.
  7. [2601.08584] Ministral 3 arxiv.org. Checked 20 October 2026.
  8. [2602.11298] Voxtral Realtime arxiv.org. Checked 20 October 2026.
  9. [2603.25551] Voxtral TTS arxiv.org. Checked 20 October 2026.
  10. Pavankumar Reddy Muddireddy - Google Scholar scholar.google.com. Checked 20 October 2026.
  11. Mistral: Voxtral TTS, Forge, Leanstral, & what's next for Mistral 4 — w/ Pavan Kumar Reddy & Guillaume Lample latent.space. Checked 20 October 2026.
  12. Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy | Machine Learning Street Talk (MLST) — transcript | TrackPodcasts.com trackpodcasts.com. Checked 20 October 2026.