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Mathias Lechner

Co-founder and CTO, Liquid AI

Mathias Lechner is a co-founder and the CTO of Liquid AI and a research affiliate at MIT CSAIL, where Lechner works with Daniela Rus. Lechner's personal page describes Liquid AI as a company founded in 2023 to build efficient foundation models, including the LFM2 language models. Lechner's research covers robust and trustworthy machine learning, liquid neural networks and the verification of learned controllers.123

At a glance

Current roles
Co-founder and CTO +1 more
Companies
Liquid AI, MIT
Sector
Company
Work listed
3
Honors
3
Sources cited
7
Profile reviewed

Career

Lechner received bachelor's (2016) and master's (2017) degrees in computer science from the Vienna University of Technology (TU Wien), and completed a PhD at the Institute of Science and Technology Austria (ISTA) in 2022, supervised by Tom Henzinger. Lechner became a research affiliate at MIT CSAIL, collaborating with Daniela Rus.12

Lechner co-founded Liquid AI with Ramin Hasani, Alexander Amini and Daniela Rus, and serves as its CTO. Lechner's page states that the company builds and releases LFM2 language models designed to run efficiently on CPUs and edge devices.321

Research

With Hasani, Lechner co-authored the 2020 papers on liquid time-constant networks and neural circuit policies, and the follow-up work on closed-form continuous-time models. Lechner's publication list also covers safety verification of stochastic and neural control systems, robot learning and multi-agent reinforcement learning.4561

Work and contributions

  • LFM (Liquid Foundation Models) Open weights

    Listed among the authors of the LFM2 technical report, which documents Liquid AI's LFM2 family of foundation models.71

  • Neural circuit policies Published research

    First author of "Neural circuit policies enabling auditable autonomy", published in Nature Machine Intelligence in 2020.5

  • Liquid Time-constant Networks Published research

    Second author, with Ramin Hasani as first author, of the paper introducing liquid time-constant networks.4

Timeline

  1. Received the Distinguished Young Alumni award at TU Wien for a master's thesis.12
  2. Co-authored "Liquid Time-constant Networks" with Ramin Hasani.4
  3. Published "Neural circuit policies enabling auditable autonomy" in Nature Machine Intelligence as first author.5
  4. Completed a PhD at the Institute of Science and Technology Austria, supervised by Tom Henzinger.12
  5. Co-founded Liquid AI and became its CTO.13
  6. Co-authored the LFM2 technical report describing Liquid AI's LFM2 models.7

Honors and recognition

  • Distinguished Young Alumni Award · Vienna University of Technology (TU Wien), 201812
  • HPC Innovation Excellence Award (with Ramin Hasani) · Hyperion Research, 202212
  • Outstanding Scientific Achievement Award (with Djordje Zikelic) · Institute of Science and Technology Austria (ISTA), 202312

Where they work

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References

7 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026

  1. Mathias Lechner — Personal PageMathias Lechner · Official page · published Jul 11, 2025 · accessed Oct 22, 2026
  2. Liquid AI — TeamLiquid AI · Official page · accessed Oct 22, 2026
  3. Liquid AI — CompanyLiquid AI · Official page · accessed Oct 22, 2026
  4. Liquid Time-constant Networks (arXiv 2006.04439)arXiv · Paper · published Jun 8, 2020 · accessed Oct 22, 2026
  5. Neural circuit policies enabling auditable autonomy (Nature Machine Intelligence)Nature Machine Intelligence · Paper · published Oct 13, 2020 · accessed Oct 22, 2026
  6. Closed-form Continuous-time Neural Models (arXiv 2106.13898)arXiv · Paper · published Jun 25, 2021 · accessed Oct 22, 2026
  7. LFM2 Technical Report (arXiv 2511.23404)arXiv · Paper · published Nov 28, 2025 · accessed Oct 22, 2026