Short Bio

Dr. Johannes Otterbach is the CTO of nyonic — an AI startup at the cutting edge of Foundation and Large Language Models. He has decades of experience in the field of AI, big data and computational sciences, aquired through his work as VP of Machine Learning Research at Merantix Momentum, researcher at OpenAI, quantum engineer at Rigetti, data scientist at LendUp / Mission Lane and software engineer at Palantir.

He received his Ph.D. in Physics from the University of Kaiserslautern, Germany while studying light particle interactions in the context [Many-Body properties of Dark-State Polaritons] in the group of Prof. Dr. M. Fleischhauer. Subsequently, he held a postdoctoral fellowship at the Harvard Quantum Optics Center

More details can be found in the (more or less up-to-date) resume

Publications & Patents


  • M. Schambach, D. Paul, J. Otterbach
    Scaling Experiments in Self-Supervised Cross-Table Representation Learning
    Accepted at TRL @ NeurIPS 2023
    arxiv:2309.17339, openreview

  • J. Siems, K. Ditschuneit, W. Ripken, A. Lindborg, M. Schambach, J. S. Otterbach, M. Genzel
    Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
    Accepted at IMLH @ ICML 2023
    arxiv:2305.11475, openreview

  • O. Kondrateva, S. Dietzel, M. Schambach, J. S. Otterbach & B. Scheuermann
    Filling the Gap: Fault-Tolerant Updates of On-Satellite Neural Networks Using Vector Quantization
    Accepted at IFIP Networking 2023

  • A. Koenig, M. Schambach & J. S. Otterbach
    Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation
    Accepted at SAIAD @ ICCV 2023 arxiv:2304.07314

  • J. Siems, M. Schambach, S. Schulze & J. S. Otterbach
    Interpretable Reinforcement Learning via Neural Additive Models for Inventory Management
    Accepted at AI4ABM @ ICLR 2023 workshop
    arxiv:2303.10382, openreview

  • K. Ditschuneit, A. Frenk, M. Frings, V. Rudel, S. Dietzel & J. S. Otterbach
    NAM-CAM: Neural-Additive Models for Semi-Analytic Descriptions of CAM Simulations
    Accepted at the FAIM 2023
    Link to the pdf

  • LEAM:AI consortium
    Große KI-Modelle für Deutschland (pdf in German only)
    On behalf of the Federal Ministry for Economic Affairs and Climate Action (BMWK)

  • J. S. Otterbach, C. M. Wilson, M. P. da Silva, N. A. Tezak, G. E. Crooks
    Using a quantum processor unit to preprocess data
    Patent number: US-11551127-B1



  • D. Sreenivasaiah, J. Otterbach & T. Wollmann
    MEAL: Manifold Embedding-based Active Learning
    2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021, pp. 1029-1037, doi: 10.1109/ICCVW54120.2021.00120

  • S. v. Baußnern, J. Otterbach, A. Loy, M. Salzmann & T. Wollmann
    DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows

  • J. Otterbach & T. Wollmann
    Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs


  • J. Otterbach, J. Ward, M. P. da Silva, N. C. Rubin
    Selecting parameters for a quantum approximate optimization algorithm (QAOA)
    Patent number: US-10846366-B1

  • C. M. Wilson & Rigetti Computing
    Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers

  • M. Reagor & Rigetti Computing
    Demonstration of Universal Parametric Entangling Gates on a Multi-Qubit Lattice
    Science Advances, 4, eaao3603 (2018)




  • J. Otterbach, M. Moos, D. Muth, M. Fleischhauer
    Wigner Crystallization of Single Photons in Cold Rydberg Ensembles
    Phys. Rev. Lett. 111, 113001 (2013)

  • E. G. Dalla Torre, J. Otterbach, E. Demler, V. Vuletic, M. D. Lukin
    Dissipative Preparation of Spin Squeezed Atomic Ensembles in a Steady State
    Phys. Rev. Lett. 110, 120402 (2013)

  • S. D. Bennett, N. Y. Yao, J. Otterbach, P. Zoller, P. Rabl, M. D. Lukin
    Phonon-induced spin-spin interactions in diamond nanostructures: application to spin squeezing
    Phys. Rev. Lett. 110, 156402 (2013)


  • M. J. Edmonds, J. Otterbach, R. G. Unanyan, M. Fleischhauer, M. Titov, P. Öhberg
    From Anderson to anomalous localization in cold atomic gases with effective spin-orbit coupling
    New J. Phys. 14, 073056 (2012)





Public Appearances & Media

  • Hannah Schwär (Capital Magazin, 2023)
    KI - plötzlich sehen wir ganz schön alt aus

  • Impact of LLMs On Energy & Sustainability (youtube), NLP + Climate Tech Event by briink, AI Campus Berlin

  • Hanna Sissmann @ eco Verband
    Mit der LEAM-Initiative unterstützen wir Unternehmen, große KI-Sprachmodelle zu trainieren
    Link (German), Link (English)

  • KI Park Tech Talk - GPT-3 and OpenAI Dall-e

  • GovTech Session: Countering Manipulation & Fake News - AI, the Silver Bullet?

  • Gradient Dissent — The Weights & Biases Podcast with Lukas Biewald
    Unlocking ML for Traditional Companies

  • Applying AI in the Wild (pdf), Zentrum fuer Optische Quantentechnologien (ZOQ), University of Hamburg, March 2021

  • Philipp Lorenz @ Stiftung Neue Verantwortung
    Die 1-Milliarde-Dollar-Organisation, die ethische KI entwickelt
    Transcript (German only)

  • Unsupervised Machine Learning on a Hybrid Quantum Computer (pdf, pptx), Bay Area Quantum Computing Meetup, YCombinator, February 2018

  • Quantum Cloud Computing (pdf, pptx), TU Kaiserslautern, Germany, January 2018

  • OQaml - A OCaml-based QASM, (pdf, pptx), Bay Area Quantum Computing Meetup, Rigetti, August 2017

  • The Curse Of Dimensionality - Visualizing High-Dimensional Datasets using t-SNE, MemSQL, June 2016

  • AI - En Route to Passing Turing's Test, TU Kaiserslautern, April 2016

  • Data Science - WTH?, TU Kaiserslautern, April 2016

Honorable Mentions:

In this section, I want to collect pieces of work of other scientist with some honorable mention of mine. All credit goes to the authors and I claim no contribution to their work. It is merely intended as a ongoing list of topics I have had exchanges with the authors.

  • P. Hacker, A. Engel, M. Mauer
    Regulating ChatGPT and other Large Generative AI Models

  • M. Kiefer-Emmanouilidis, R. Unanyan, M. Fleischhauer, and J. Sirker
    Evidence for Unbounded Growth of the Number Entropy in Many-Body Localized Phases
    Phys. Rev. Lett. 124, 243601 (2020)

  • P. Lorenz & K. Saslow (2019)
    Demystifying AI & AI Companies — What foreign policy makers need to know about the global AI industry