I am a Full Professor (W3) of “Machine Learning in Science” at the University of Tübingen where I lead the Artificial Scientist Lab.

Several Postdoc and PhD positions available: Details; Master and Bachelor thesis for students at University of Tuebingen are also available.

I am excited about the potential of artificial intelligence-inspired and -augmented science, and how we can use algorithms in a more “creative” way. To make progress, I believe it will be important to learn what humans mean by crucial scientific concepts such as surprising, creativity, understanding or interest. I have created AIs for designing quantum experiments and hardware (several actually build in labs) and inspiring novel ideas for quantum technologies. (Part of this research has recently been summarized in a nice article in Scientific American, a feature by the National Academy of Science, a video interview with QuantaMagazine and in German in derStandard or SPIEGEL). I also build autonomously semantic network from scientific publications, and use machine learning to predict and suggest personalized future research questions and ideas. In that sense, we use the machine as a source of inspiration to accelerate scientific progress. Ultimately, I want to create algorithms that help us to uncover the secrets of the Universe. More about the research philosophy and ideas can be read in this 2022 Nature Review Physics perspective. Our work was awarded an ERC Starting Grant 2024.

More: e-Mail, Twitter, BlueSky, google scholar, arXiv, GitHub, youtube, full CV.

News

• 2025.12.01: Talk at the Science Week conference of the ORIGINs excellence cluster (Seeon close to Munich, Germany), about the coming era of artificial scientists.
• 2025.11.21: New paper preprint: Analytical Fock Representation of Two-Mode Squeezing for Quantum Interference. This article contains a very useful mathematical derivation and exact closed-form solution of the action of squeezing operator applied to arbitrary photon number input states — mostly done by Xuemei Gu, together with Carlos Ruiz-Gonzalez and myself. We use it to find new interpretations of previously known nonlinear interference effects, and theoretically discover a new, very unexpected interference effect in a four-photon system that is — at least to me — highly unintuitive. We are interested in this because the results in the article can be used as a generalized representation for our AI-driven discovery tools in quantum physics (e.g. Melvin or PyTheus).
• 2025.11.18: New paper preprint Towards autonomous quantum physics research using LLM agents with access to intelligent tools, spearheaded by Soeren Arlt and Xuemei Gu. In this paper, we introduce AI-Mandel, our first AI-physicist prototype. AI-Mandel (name inspired by the legendary quantum optics researcher Leonard Mandel) can create new ideas in quantum physics (using OpenAI’s GPT and access to arXiv), and then can execute this idea with our domain-specific AI PyTheus. The quality of ideas and implementation of AI-Mandel are surprisingly high, we found many new ideas and creations, and we wrote two papers directly inspired by the creations of AI-Mandel recently, which are on arXiv: New forms of generating entanglement of photons that never interacted, and new photonic non-local quantum gates (here, AI-Mandel found a surprising solution that uses an analoge structure to quantum teleportation, but using very different resources). This work asks important questions about the impact of human creativity in the creation of scientific ideas — how far it can be removed, and where the human contribution remains crucial.
• 2025.11.15: Interview in SPIEGEL about AI-driven discoveries and Artificial Scientists, by Marc Hasse und Martin Schlak.
• 2025.11.07: New paper preprint Automated Discovery of Non-local Photonic Gates, where we discover new ways to create photonic gates using path identity — an accidentally discover a new form opertation that strongly mimicks quantum teleportation. This is the second of three articles, the other one was on arXiv 2 weeks ago. All examples have been discovered by PyTheus. One more text will appear in a few days.
• 2025.10.28: Talk at the Max Planck Institute for Multidisciplinary Sciences in Goettingen (Germany) about designing physics experiments with AI.
• 2025.10.14: New paper preprint Automated discovery of high-dimensional multipartite entanglement with photons that never interacted. Surprisingly complex entanglement can be generated even though the photons never interacted, no entanglement source is used, and no Bell-State-Measurement is used. This was discovered using PyTheus and is the first of a series of three results that make up an exciting story. The other two will be released soon (papers are being written).
• 2025.09.30: Talk at ML4Science Cluster Conference — locally in Tuebingen.
• 2025.09.09: Talk at AIMat Summer School 2025 ML4Materials, KIT, Karlsruhe about AI-driven idea generation.
• 2025.09.04: Podcast discussion on AI for predicting the future of Science in physicsworld by Hamish Johnston with my co-author Felix Frohnert, on our recent paper that uses 600,000 quantum physics papers and word embedding to predict what will happen in the next few years.
• 2025.08.22: Keynote talk at HAMLET-Physics (Copenhagen, Denmark) about AI for Physics.
• 2025.08.10: Story about AI in Science and our work in Neue Zuericher Zeitung, called ‘Ein Jahrhundert an Fortschritt in nur fünf Jahren: Künstliche Intelligenz soll es möglich machen‘ by Anna Weber.
• 2025.08.04: Portrait about our work in Max Planck Society’s magazine for students and teachers MAX, on “KI in der Wissenschaft — Mit künstlicher Intelligenz Neues entdecken“.
• 2025.08.01: New paper published in Science Advances: Violation of Bell inequality with unentangled photons (arXiv), experimentaly implemented in the Nanjing Lab of Xiaosong Ma. This provocative text is a step towards understanding the origins of nonlocal interference in multi-photon frustrated down-conversion experiments better (first theory proposal in 2019, first implementations by Xi-Feng Ren’s and Xiaosong’s group in 2023). The work originated from years-long discussions of the authors and numerous other people in the field. It’s my first paper with Markus Aspelmeyer and my first with Anton Zeilinger after his Nobel prize (humorously, for violations of Bell inequalities with entangled photons). This is for sure not the last word on the topic, and i am looking forward to further theoretical and experimental understanding of nonlocal interference by path identity and quantum indistinguishability.
• 2025.07.31: Keynote talk at the Scholarly Document Processing workshop at ACL 2025, about predicing what scientists could (and maybe should) do in future, from millions of papers..
• 2025.07.21: Wonderful Quanta-article by Anil Ananthaswamy called AI Comes Up with Bizarre Physics Experiments. But They Work. It discusses some of our recent AI-driven experimental design papers, such as the work on discovery of new graviational wave detectors (with a wonderful portrait of Rana Adhikari from LIGO) and new entanglement of independent particle ideas discovered by PyTheus.
• 2025.07.17: Seminar talk in the Autonomous Vision Group in Tuebingen, on artificial muses.
• 2025.07.11: Talk at the IQST Workshop at KIT (Karlsruhe, Germany) on AI-driven experimental design.
• 2025.07.09: Colloquium talk at University Stuttgart (SimTech Colloquium) about artificial muses.
• 2025.07.07: Keynote talk at Symposium ML4QT in Heilbronn, Germany — about de-novo design of physics experiments.
• 2025.06.25: My first radio interview, on the occasion of the start of my professorship in Tübingen, in ORF’s Ö1, with Barbara Zeithammer, Punkt Eins: Neues aus dem Labor für künstliche Wissenschaftler (german, 54mins)
• 2025.06.19: Plenary talk at EuCAIFCon on Artificial Muses for Physics.
• 2025.06.16: Short talk at roundtable of Santa-Fee-Institute/DeepMind about preventing the dystopia of science without understanding.
• 2025.06.04: Talk at Physics Colloquium at the University Duisburg-Essen about artificial muses.
• 2025.06.02: New paper preprint is online (a large-scale collaboration that started 3 years ago): Quantum computing and artificial intelligence: status and perspectives
• 2025.06.02: Seminar talk at University of Oxford, on AI for physics.
• !!! 2025.06.01: Starting as a Full Professor for “Machine Learning in Science” at the University of Tübingen TODAY 🙂
• 2025.05.30: Invited Talk and Panel Discussion at SciFM25: Scientific Discovery in the Age of AI in Ann Arbor, Michigan, USA — about AI discovery in physics.
• 2025.05.28: We have numerous open PhD and Postdoc positions, see here.
• 2025.05.22: Talk at Anton Zeilinger’s 80th birthday symposium, on new ideas from machines for physics.
• 2025.05.19: Talk at Aston University (Birmingham, UK), workshop “AI meets photonics”, on de-novo design of physics experiments.
• 2025.05.13: Keynote talk at Quantum Photonic Messe 2025 in Erfurt, Germany.
• 2025.05.10: Paper accepted in MLST on the prediction of impacts of scientific ideas before they have generated. I believe this is an important component of a future system that helps us design new impactful and personalized research directions, like an artificial Muse.
• 2025.04.30: A quanta article by Gregory Barber on creative AI in science covers some of our works in AI-designed experiments and large-scale AI-driven idea creation.
• 2025.04.28: Talk at the Bristol Quantum Info Technology workshop about de-novo design of experiments.
• 2025.04.24: My podcast interview (in german) with “inspirierend anders – forscht” (by Luca Beutel) is online, about AI, quantum physics and artificial scientists (90mins).
• 2025.04.23: Talk at the Quantum Machine Learning Workshop at University of Vienna, about designing new physics experiments with AI.
• 2025.04.11: De-novo design of Gravitational Wave Detectors published in PRX 🙂 Extremely happy to see this paper online after 3.5 years of work. We show that AI can discover new GW detector ideas that are more sensitive than those designed by humans.
  It profoundly changed my perspective on what’s possible: I now firmly believe that nearly all areas of experimental physics could greatly benefit from entirely de-novo, tabula rasa discovery of experimental hardware through AI — with huge potential to find entirely new ways for observing the universe. I am extremely grateful that ERC and Uni Tübingen recognize these potentials and support us to push these techniques much further.
  This work highlights an important challenge we’ll increasingly face in the near future: How can we understand super-human discoveries by non-human intelligence? We spent at least 6 months trying to understand the new solutions — but many of the tricks are still alien to us. It actually feels like exploring alien-technology at times. I have no good answer yet.
  Lastly, i want to thank Anil Ananthaswamy for indirectly connecting us. Rana and Yehonathan contacted me after reading Anil’s text about our work on quantum experiment design in 2021, and have already suspected that very similar ways of thinking can be applied in more generality, for instance in gravitational wave detector design.
• 2025.04.03: Talk at optics seminar at University of Warsaw.
• 2025.03.26: Virtual seminar talk at First Principles.
• 2025.03.24: Colloquium talk at the Vienna Center for Quantum Science and Technology. Always great to be back in Vienna and see so many familiar faces and hear about the wild recent results in quantum!
• 2025.03.18: My video interview with Quanta Magazine is online, about AI-driven experimental design and inspirations from huge amount of scientific literature. Thank you Emily Buder for this – was great fun!
• 2025.03.18: Keynote talk at 2025 AI in Science and Engineering Symposium at the University of Michigan, about artificial muses in science.
• !!! 2025.03.15: Very happy to announce that I’ll be joining the University of Tübingen as a Full Professor (W3) of “Machine Learning for Science” in the Computer Science Department within the Faculty of Science and the Cluster of Excellence ML4Science.
  Tübingen is an exceptionally exciting place for AI/ML, many many great groups and initiatives, with very strong applications in the natural sciences. Couldn’t be happier; can’t wait to start and meet all future colleagues, and building new and more powerful AI tools for understanding the universe.
  We have numerous open positions (also within my ERC StG Grant), for post-docs and PhDs. If you are excited to build AI-driven discovery of physics, especially physics experiments for new ways to observe the universe (super-fast physics simulators, AI-driven exploration of large complex spaces, etc) and agent-based idea generations, send me an e-Mail.
• 2025.03.13: Talk at Liverpool Virtual Seminar Series on Data Intensive Science about artificial muses.
• 2025.03.10: Talk at the Wissenschaftsrat (Fokusgruppe Künstliche Intelligenz) about AI in Physics (and Science in general).
• 2025.03.04: Talk at QTLabs about automated design of physics experiments.
• 2025.02.21: Our paper on automated discovery of new gravitational wave detectors (in collaboration with design-experts from LIGO) has been accepted in Phys. Rev. X (see GitHub)!! 🙂 To me this shows that our computational technology that we have invented for quantum experiments over the last 10years can be applied much more general for physics experiments. More to come soon!
• 2025.01.29: Talk at the CIRSS Speaker Series, Spring 2025: Generative AI and the Future of Research (virtual seminar at University of Illinois at Urbana-Champaign) about Artificial Scientists.
• 2025.01.28: Wrote a tutorial on photons with complex spatial modes in optical networks with the group of Ebrahim Karimi. This started as a question of how to expand our physical simulators (for AI-driven discovery of physics experiments) to cover the interesting physical effects that emerge there. Literature was sparse, so we wrote down our findings. Best: Found some analytical expressions that can replace numerical integrations in some cases, making our simulators much faster.
• 2024.12.10: Very happy to see our super-fast JAX framework for simulating optics (XLuminA), with an application to automated design of microscopy — published in Nature Communications. See more details here and the beautiful GitHub repo here.
• 2024.12.03: New paper published in Physical Review Letters on Entangling Independent Particles by Path Identity, in collaboration with the experimental quantum optics lab of Xiaosong Ma. I am very excited about this work — it is an experimental implementation of an idea we have previously discovered with our AI-driven design tool PyTheus (example 76). This work shows how to entangle two independent, distant particles without starting with entanglement, without Bell state measurements and even without measuring all ancilla photons. As an alterative, the experiment employs a superposition of the origins of a multi-photon state, described for the first time here, and observed for the first times here and here. This work changed my understanding which resources are necessary (or better, which are not necessary) to create entanglement.
• 2024.11.29: Talk at the workshop “Connecting Physics and Computer Science: A Workshop on Data-Driven Approaches” at University Augsburg on de-novo design of physics experiments.
• 2024.11.26: Talk at the Physics Colloquium at University Muenster on artificial muses.
• 2024.11.21: Talk at workshop for AI and the Future of Science, Lingnan University, Hong Kong on artificial muses.
• 2024.11.14: Talk at Physics Colloquium at Uni Greifswald about ideas for physics generated by clever algorithms.
• 2024.11.12: New paper preprint: Using dynamic word embedding on 66,000 quantum physics papers helps to predict what quantum physicists will work on in the future. Using the dynamics of word embedding beats all methods that do not use hand-crafted features. A step closer to end-to-end prediction of the future of physics :). Collaboration with Felix Frohnert and Evert van Nieuwenburg from aQa Leiden.
• 2024.11.07: Talk at the ML for quantum technology workshop at MPL Erlangen, about automated design of physics experiments.
• 2024.10.25: Talk at the mini symposium on AI and quantum physics at Chalmers (Goethenburg, Sweden), and PhD opponent of Dr. David Fritzek.
• 2024.10.16: Talk at the AI goes MAD^2 workshop in Madrid, Spain, about AI as a source of inspiration
• 2024.09.24: Talk at the MODE (for Machine-learning Optimized Design of Experiments) in Valencia, Spain – about designing physics experiments with AI.
• 2024.09.20: Talk at the CroCoDays 2024, Zagreb, Croatia, on a graph theory question that emerged from quantum physics.
• 2024.09.12: I’ve been involved in the red-teaming of OpenAI’s GPT o1 model.
• !!! 2024.09.05: I have been awarded the ERC Starting Grant for my project ArtDisQ (Artificial Scientific Discovery of advanced Quantum Hardware with high-performance Simulators), for 1.5Mio€. We will develop new AI methods for discovering advanced quantum-enhanced physics experiments, including optical telescopes and gravitational wave detectors. The goal is to find new ways to observe the universe. More here.
• 2024.09.04: Talk at the Gutenberg Workshop on AI for Scientific Discovery about artificial muses in physics.
• 2024.09.02: Talk at the Como Summer School for Machine Learning Photonics, about artificial muses in physics.
• 2024.08.15: I joined the Editorial Board of the great open-access, non-profit, community-driven Machine Learning: Science and Technology (MLST).
• 2024.08.14: Paper published in MLST about Virtual Reality for understanding AI-discovered quantum experiments.
• 2024.07.05: Talk at Uni Muenster (Department for quantum technology) about AI-designed quantum experiments.
• 2024.06.26: Talk at the Future of Materials Discovery (London, UK) on artificial muses in Science.
• 2024.06.24: New paper preprint: The group of Ebrahim Karimi collected 9 months worth of weather data for a QKD link in Ottawa, and uses machine learning to forcast the weather quality and its consequence for the quantum communication link quality. Spearheaded by our joint student Tareq Jaouni.
• 2024.06.13: Lecture at STER Summer School in Warsaw, Poland, on Artificial Muses in Science.
• 2024.06.05: New paper preprint: Meta-Designing Quantum Experiments with Language Models. Instead of using AI to design a specific experimental setup, we use AI (specifically, a sequence-to-sequence transformer) to generate a Python code which designs a whole class of quantum experiments. The code direcly shows the underlying design principles and ideas.
• 2024.05.28: New paper preprint: Generation and human-expert evaluation of interesting research ideas using knowledge graphs and large language models. Here we generated ideas using knowledge graphs from 50+ million scientific papers and GPT4, and then evaluate them with more than 100 research group leaders within the Max Planck Society.
• 2024.05.22: Talk at Konferenz der Fachbereiche Physik (KFP) about AI in Physics.
• 2024.05.13: Talk at the Tuebingen AI Symposium about Artificial Muses in Physics.
• 2024.04.26: Talk and panel discussion at EU-LIFE Utopia Conference 2024: A Social Innovation Experiment with Artificial Intelligence (CeMM, Vienna) – about predicting and suggesting future ideas in science.
• 2024.04.25: Talk at the Uni Wien/Uni Wuppertal Philosophy series “Digitality and Transcendental Philosophy“, on Artificial Muses in Science.
• 2024.03.27: Talk at ML for Quantum Physics workshop in Obergurgl, Austria – on artificial muses in science.
• 2024.03.18: Paper published in Phys. Rev. Research on an long-distance frustrated interference experiment.
• 2024.03.18: Talk at DPG Condensed Matter Section in Berlin on AI for designing physics experiments.
• 2024.03.15: Talk at DPG Atom, Molecules, Quantum Optics & Photonics in Freiburg on AI for designing physics experiments.
• 2024.03.05: New paper preprint on how to use virtual reality for understanding AI-generated ideas and designs in physics.
• 2024.02.28: Talk at Workshop for Epistemological Issues of Machine Learning in Science in Dortmund (Germany), about Artificial Muses in Physics.
• 2024.02.15: Paper on deep dreaming on quantum-graphs published in Machine Learning: Science & Technology.
• 2024.02.14: New paper preprint: Forecasting high-impact research topics via machine learning on evolving knowledge graphs. I believe this is a crucial step towards a big picture goal of artificial muses that can inspire new, interesting high-impact ideas.
• 2024.01.24: Talk at Workshop for Scientific Understand and AI in Leiden, Netherlands, about Artificial Muses in Physics.
• 2023.12.12: Paper on AI-driven design of 100 new (!) quantum experiments (for state generation, quantum communication, condensed matter physics, multi-photon control, etc) just published in Quantum, see the full PyTheus code package.
• 2023.12.08: New paper preprint: Digital Discovery of interferometric Gravitational Wave Detectors with Yehonathan Drori, Rana X Adhikari from Caltech and LIGO. Discovered 50 new detector designs (many are very exotic but superior) for supernovae, neutron star mergers, cosmological events, broad band detectors etc. See the Gravitational Wave Detector Zoo.
• 2023.12.07: Talk at the Google Research Science & AI Seminar on AI-driven discovery of new physics experiments, specifically new super-resolution microscopes.
• 2023.12.01: Talk at the Lingnan-Cambridge Workshop on AI in Science on concrete AI-inspired scientific discoveries in Cambridge, UK.
• 2023.12.01: Keynote talk at the Artificial Intelligence for Science of Science (AI4SciSci) workshop of IEEE ICDM 2023 [virtual], on predicting and suggesting future research directions with knowledge graphs and semantic networks (e.g. in quantum and AI).
• 2023.11.28: Participate in Panel Discussion about AI/GPT in Research & Higher Education at University of Vienna.
• 2023.11.15: Talk at MIT’s Optics and Quantum Electronics Seminar on AI-driven design of new (quantum) experiments.
• 2023.10.31: Our XLuminA paper on a JAX-based superfast simulator for automated discovery in superresolution microscopy got accepted as an Oral Presentation (with a score of 10/10: “10: Top 5% of accepted papers, seminal paper”) at NeurIPS AI4Science workshop.
• 2023.10.16: Paper published in Nature Machine Intelligence about the prediction of future research directions in Artificial Intelligence. This is a combination of all insights we gained in our Science4Cast AI-competition (within IEEE BigData 2021). See our GitHub for all details.
• 2023.10.13: New paper preprint, on AI-driven discovery for superresolution microscopy. XLuminA is an autodifferentiating discovery framework which can discover techniques involving STED microscopy and vector-beam based superresolution.
• 2023.10.12: Talk and panel discussion at National Academy of Science’s AI for Scientific Discovery workshop, Washington DC, USA.
• 2023.10.06: Talk about Artificial Muses in Quantum Physics at CIFAR Quantum Information Science Meeting, Banff (Calgary), Canada.
• 2023.10.03: Lecture about Artificial Muses in Physics at CIFAR Quantum Information Science Fall 2023 School, Banff (Calgary), Canada.
• 2023.09.22: Talk at IEEE Quantum Week: Quantum Algorithm Design Automation about AI-based design of quantum optics.
• 2023.09.14: New paper preprint: Deep Quantum Graph Dreaming: Deciphering Neural Network Insights into Quantum Experiments. Trying to understand what strategies neural networks learn to manipulate quantum states.
• 2023.09.13: Talk at the European Optical Society Annual Meeting 2023, Dijon, France, in the Focused Session for AI and Photonics, on AI designed quantum experiments.
• 2023.07.25: New paper preprint: Experimental Solutions to the High-Dimensional Mean King’s Problem. Using our digital discovery framework PyTheus, we discover and generalize strategies for experimental blueprints of a quantum communication protocol called “The Mean King Problem”. In Collaboration with the experimental quantum optics group of Ebrahim Karimi in Ottawa.
• 2023.07.18: Talk in the Theoretical Physics Seminar at University of Augsburg, Germany, on AI as a muse for new ideas in physics.
• 2023.07.06: Talk about Scientific Understanding with AI at the Annual Conference of the British Society for the Philosophy of Science, Bristol, UK.
• 2023.07.01: Paper published in Digital Discovery on the recent code advanced of the code-base of the 100% robust molecular string representation SELFIES, which has been adopted in machine-learning for chemistry and material science since we published it 3 years ago.
• 2023.06.30: Lecture about AI as a Muse in Science at the summer school “Machine Learning Summer School on applications in Science” in Krakau, Poland. Video of lecture online.
• 2023.06.26: Talk and participation at panel discussion “AI for Science” at the amazing International Conference for Science of Science and Innovation, Chicago, USA.
• 2023.05.04: Talk at the Vienna Bio Center (Max Peruty Labs) about AI as an artificial muse for new ideas in Science.
• 2023.04.21: Talk at the Philosophy of Contemporary and Future Science group (Lingnan University, Hongkong) about scientific understanding with AI: video.
• 2023.04.10: Talk at the Machine Learning and (Quantum) Physics Workshop in Obergurgl, Austria on artificial muses.
• 2023.04.10: New paper preprint: Quantum interference between distant creation processes.
• 2023.04.07: The group of Jianwei Wang (Peking University) has implemented a very large scale quantum graph in integrated photonics, published today in Nature Photonics. The bridge between quantum optics and graph theory has been discovered by us over several years and has now become the standard representation for our Artificial-Intelligence-based Discovery algorithms. Jianwei’s implementation is a new framework for quantum information processing with photons, and also brings our and others (past and future) theory and AI results into the real world. Exciting — congratulations!
• 2023.03.17: Talk at Tampere University, Finland in Physics Colloquium, on AI-inspired science.
• 2023.03.17: Paper published in Nature Communications about a new multi-photon interference, derived from a graph-theoretical representation (discovered using AI).
• 2023.02.22: Our research covered by dutch news paper NRC: Will the next Einstein be an AI?
• 2023.02.08: New paper preprint on code-details of SELFIES library for AI in chemistry.
• 2023.01.27: Talk at ICFO (Barcelona, Spain) on an Artificial Muse for physics.
• 2023.01.19: Talk at aQa Leiden (Netherlands) University on an Artificial Muse for physics.
• 2023.01.16: New paper preprint: Roadmap on Structured Light (our contribution: Artificial intelligence for structured waves).
• 2023.01.13: Paper published in Optica on the observation of a new multi-photon quantum interference effect, first proposed using Graph Theory for quantum optics.
• 2023.01.11: Talk at the ELLIS unconference 2023 (La Palma, Spain) on AI as a source of inspiration in physics.
• 2023.01.03: Invited Perspective article on “Artificial intelligence and machine learning for quantum technologies” published in APS Phys.Rev.A.
• 2022.12.15: Talk at University of Stuttgart, Quantum Info & Technology on Computer-Designed Quantum Experiments.
• 2022.12.03: Participating at panel discussion on “Philosophy of Science in the AI Era” at the ML&Physical science workshop at NeurIPS 2022.
• 2022.11.23: Talk at the New Frontiers in Machine Learning and Quantum workshop in Watterloo, Canada on an Artificial Muse in Physics (video online).
• 2022.11.11: Talk at QTML 2022 (Naeples, Italy) about an Artificial Muse in Physics.
• !!! 2022.10.19: First two publications of my group — and they are HUGE. Release of PyTheus, a highly-efficient open-source discovery framework for quantum optics. We showcase PyTheus to discover 100 (!!) diverse new quantum experiments (state generation, quantum communication, quantum measurements, quantum gates, quantum simulation), and use it to extract a new very surprising scientific concept in experimental quantum optics.
• 2022.10.17: Paper published in Cell’s Patterns about a robust representation of molecules for AI in chemistry, with 30 co-authors from 14 countries.
• 2022.10.13: Paper published in Quantum about logical AI for desinging quantum experiments.
• 2022.10.11: Paper published in Nature Review Physics On Scientific Understanding with Artificial Intelligence. A wild view into the future of how AI could contribute to the essentail aims of science.
• !!! 2022.10.04: Congratulations to my former PhD advisor Anton Zeilinger for winning the Nobel Prize in Physics 2022!
• 2022.10.04: New paper preprint on Predicting the Future of AI with AI.
• 2022.09.27: Talk at Galileo Galilei Institute (Florence) ML workshop on AI as an artificial Muse in Physics.
• 2022.09.22: Talk at ML for Natural Sciences workshop (University Hamburg) on AI as an artificial Muse in Physics.
• 2022.09.06: Talk at DPG Tagung on AI as an artificial Muse in Physics.
• 2022.08.09: New paper preprint on Artificial Intelligence in Quantum Technology.
• 2022.07.26: Paper published in Machine Learning: Science and Technology on a curious agent that explores the space of molecules.
• 2022.07.20: Work on interpretable VAE for Quantum Optics featured as Research Highlight in Nature Computational Science.
• 2022.07.06: Talk at University of Exeter (Quantum Non-Equilibrium Group) about AI-desinged Quantum Experiments.
• 2022.07.06: Talk at FAU Physics Colloquium about Artificial Scientists.
• 2022.06.24: Talk at ESA’s Advanced Concepts Team about Artificial Scientists.
• 2022.06.21: Paper published in Reviews of Modern Physics on Quantum indistinguishability by path identity and with undetected photons.
• 2022.06.16: Paper published in Nature Machine Intelligence on unsupervised learning of interpretable representations of quantum optics experiments.
• 2022.06.13: Talk at Bayer about Scientific Understanding from AI.
• 2022.06.06: Talk at meeting of Young German Physical Society about “Von Kuenstlicher Intelligenz zu Kuenstlichen Wissenschaftern”.
• 2022.05.26: Invited Talk at Photonics North 2022, Photonics&AI Session on Understanding through AI in Quantum Optics.
• 2022.05.22: Public Talk at “Lange Nacht der Forschung” about “Von Kuenstlicher Intelligenz zu Kuenstlichen Wissenschaftern“.
• !!! 2022.04.05: New paper preprint on Scientific Understanding with Artificial Intelligence. Perspective towards an essential aim of science – IMO crucial for the creation of a true Artificial Scientist.
• 2022.04.04: New paper preprint on SELFIES and the future of molecular string representations for AI in chemistry and material science (collaborations with 31 coauthors from 10 different countries).
• 2022.02.24: Paper published in Phys.Rev.Applied on the first experimental qutrit-GHZ state in a superconducting device.
• 2022.01.14: Talks of Science4Cast AI competition are online!
• 2021.12.23: New paper preprint on the observation of a non-local interference effect and its control with undetected photons. The interference effect was discovered using several years ago by AI, see a detailed cover about some background in Scientific American.
• 2021.12.20: Review on Quantum Indistinguishability by Path Identity accepted in Rev.Mod.Phys.
• 2021.12.17: Chaired the IEEE BigData Competition Science4Cast session, with so many amazing contributions and special talks! Talks on youtube soon.
• 2021.12.10: Talk at Perimeter ML seminar (video online!) on predicting the future of science.
• 2021.12.01: Talk at Quantum Theory group at FAU on (quantum-)computer-inspired quantum experiments.
• 2021.11.26: Paper published in Photonics on using Deep LSTM networks to predict complex quantum entanglement properties. Collaboration with group of Sepp Hochreiter, the inventor of LSTMs.
• 2021.11.11: Talk at the Bavarian Graduate School of Computational Engineering on predicting the future of science.
• 2021.11.10: Guest lecture at the University of Rochester on ML in chemistry.
• 2021.11.02: Talk at IBM Zurich on ML in chemistry.
• 2021.10.26: Print version of Scientific American’s cover of our work, see here.
• 2021.09.29: New paper preprint on the useage of logic and SAT solvers in the design of quantum experiments.
• 2021.09.07: New paper preprint on the internal worldview of deep generative models in quantum experiments.
• !!! 2021.09.01: Start of my research group at Max Planck Institute for the Science of Light (MPL, Theory Division).
• 2021.08.26: THESEUS paper published in PRX 🙂
• 2021.08.25: Annouced the Science4Cast Machine Learning competition (to predict future research in the field of ML&AI). Related to SemNet, but much larger.
• 2021.08.13: Mini-workshop on SELFIES (100% robust molecular string representation) celebrating our paper being the most downloaded and cited one in the journal MLST.
• 2021.07.07: Talk about computer-inspired quantum experiments and scientific understanding at Machine Learning for Quantum X workshop.
• 2021.07.02: Scientific American article about our work on computer-designed quantum experiments.
• 2021.07.01: Paper accepted in Phys.Rev.X on getting conceptual understanding though AI in quantum physics.
• 2021.06.30: Talk about computer-inspired quantum experiments and scientific understanding at Artificial Scientific Discovery workshop at MPL.
• 2021.06.09: Paper published in Machine Learning: Science&Technology on Deep Molecular Dreaming.
• 2021.05.31-2021.06.02: Co-Chair of AI session at Photonics North 2021, see poster.
• 2021.04.30: Talk at ETH Zurich about computer-inspired quantum experiments.
• 2021.04.28: Paper published in Quantum Science&Technology on designing quantum optics using quantum computers.
• 2021.04.23: Talk at 4th University of Florida Drug Discovery Symposium on SELFIES and ML in chemistry.
• 2021.04.20: Paper published in Chemical Science on extremely efficient generative model for chemistry.
• 2021.04.13: New paper preprint on first high-dimensional GHZ in superconducting device, on IBM’s quantum computer.
• 2021.03.28: New paper preprint on experimental observation of new quantum interference effect (discovered in 2017 using graph theory).
• 2021.03.19: Uploaded Video of SELFIES talk.
• 2021.03.04: Talk at Carnegie Mellon University, Scientific Machine Learning Webinar Series, on SELFIES and ML in chemistry.
• 2021.02.23: Talk at Max Planck Research Group Symposium about Computer-Inspired Quantum Research.
• 2021.02.17: Talk at Max Planck Institute for the Science of Light (MPL in Erlangen) about Computer-Inspired Quantum Research.
• 2021.02.02: New paper Data-Driven Strategies for Accelerated Materials Design in ACS Accounts of Chemical Research.
• 2021.01.11: New extensive blog post on SELFIES, a 100% robust graph representation.
• 2021.01.07: New paper preprint, a review of quantum indistinguishability by path identity.
• 2020.12.25: New youtube video on our Conjecture in Graph Theory.
• 2020.12.21: New paper preprint on Curiosity-driven exploration in deep molecular reinforcement learning.
• 2020.12.17: New paper preprint on Deep Molecular Dreaming.
• 2020.12.16: Misc – The Vienna Technical Museum has realized a suggestion by me and built a real-world Neural Network for the public to understand basic concepts in Machine Learning.
• 2020.12.15: New paper preprint on surprisingly efficient, combinatorial exploration in the molecular universe with SELFIES.
• 2020.11.29: New youtube video (my talk of Quantum2020) on conceptual understanding from inverse-design for quantum experiments.
• 2020.11.24: Talk at Q-Turn 2020 on conceptual understanding from inverse-design for quantum experiments.
• 2020.11.20: View&Perspective on paper using graph theory for designing efficient GHZ experiments in Frontiers of Physics.
• 2020.11.18: Talk in QML Semniar at National University of Singapour on predicting and suggesting new research in quantum physics.
• 2020.11.12: Talk in Quantum Nanoscience Seminar at TU Delft on Computer-Inspired Quantum Research.
• 2020.11.10: Talk at QTML 2020 (conceptual understanding from inverse-design for quantum experiments).
• 2020.10.28: Paper published in Machine Learning: Science and Technology on SELFIES!
• 2020.10.19: Talk at Quantum2020 on conceptual understanding from inverse-design for quantum experiments, and IOP Quantum2020, International Quantum Technology Emerging Researcher Award, Highly Commended, “in recognition of significant achievement and exceptional promise for future contributions to the field of quantum science and technology.“.
• 2020.10.27: New paper preprint on machine-learning inspired scientific intuition.
• 2020.10.09: Misc – Elon Musk liked this tweet.
• 2020.10.01: Paper published in PNAS of first Experimental Entanglement by Path Identity.
• 2020.09.29: Paper published in Nature Review Physics on Computer-inspired quantum experiments
• 2020.09.19: Talk at NetSci MMXX, Machine Learning In Network Science Symposium on predicting and suggesting new research directions in quantum physics.
• 2020.07.27: Paper published in PRL on computer-inspired quantum gate concepts.
• 2020.06.26: Misc – The International Astronomical Union (IAU) decided to rename a number of moon craters because of my tipps. See Philip Ball’s article and the coverage in the Nature Podcast.
• 2020.06.25: Paper published in Nature Review Physics on high-dimensional quantum entanglement.
• 2020.06.30: Talk at A.I. Socratic Circles on conceptual understanding from inverse-design for quantum experiments.
• 2020.06.25: Talk at Photonics Online Meetup #POM20Ju on conceptual understanding from inverse-design for quantum experiments.
• 2020.06.19: Talk at Max Planck Institute for the Science of Light (Erlangen) on conceptual understanding from inverse-design for quantum experiments.
• 2020.06.04: New paper preprint on quantum-computer designed quantum hardware.
• 2020.05.26-28: Co-Chair of AI session at Photonics North 2020, see poster.
• 2020.05.18: Paper published in Physica Scripta on open physics questions in future. Our contribution: automation of physics; my A.I. Melvin is official co-author.
• 2020.05.13: New paper preprint on conceptual understanding from inverse-design for quantum experiments.
• 2020.04.23: Paper published in ICLR on Genetic Algorithm+Deep Learning for molecules.
• 2020.04.23: Talk at A.I. Socratic Circles on SELFIES.
• 2020.04.13: Paper published in Optics Express on Light Propagation in Turbulence.
• 2020.03.13: Paper published in PRA on quantum experiments and hypergraphs.
• 2020.02.29: New paper preprint on Computer-inspired quantum experiments.
• 2020.01.14: Paper published in PNAS on predicting and suggestion future of quantum physics.
• 2020.01.08: News&Views in APS’s Physics on Scientific Insights from Neural Nets.

Professional Experience

• Since 06.2025: Full Professor (W3) of “Machine Learning in Science” at the University of Tübingen.
• 09.2021-05.2025: Independent Research Group Leader (Artificial Scientist Lab) at Max Planck Institute for the Science of Light (MPL, Theory Division), Erlangen, Germany.
• 01.2019-08.2021: FWF Erwin Schrödinger Postdoctoral Fellow (group of Alan Aspuru-Guzik)
• University of Toronto (Department of Chemistry & Computer Science), Canada.
  • Vector Institute for Artificial Intelligence, Toronto, Canada.
  • (05.-09.2021: Institute for Advanced Research in Artificial Intelligence (IARAI), Vienna, Austria)
• 12.2017-12.2018: Postdoctoral Fellow (group of Anton Zeilinger)
  • University of Vienna (Faculty of Physics), Austria.
  • Institute for Quantum Optics and Quantum Information (IQOQI) Vienna, Austria.
• 10.2012 – 11.2017: Graduate research assistant (group of Anton Zeilinger)
  • University of Vienna (Faculty of Physics), Austria.
  • Institute for Quantum Optics and Quantum Information (IQOQI) Vienna, Austria.

Education

• 2012-11.2017: PhD in Physics at University of Vienna in the group of Anton Zeilinger:
  • Quantum experiments with spatial modes of photons in large real and Hilbert spaces.
  • Finished with distinction
• 2009-09.2012: Master studies at Vienna’s University of Technology.
  • Master thesis in the group of Anton Zeilinger.
  • Investigation of complex spatial mode structures of photons.
  • Finished with distinction.
• 2006-06.2009: Bachelor studies at Vienna’s University of Technology.
  • Bachelor thesis in the group of Manfried Faber.