PeopleofSuperintelligence

Researcher

Juan Felipe Carrasquilla Álvarez

Juan Felipe Carrasquilla Álvarez is a physicist who combines machine learning and quantum simulation to study quantum matter. He earned a physics PhD at SISSA in 2010 and held postdoctoral fellowships at Georgetown and Perimeter. His work used neural networks to study phases of matter and reconstruct quantum states; he also worked as a research scientist at D-Wave Systems and the Vector Institute. He joined ETH Zürich in 2024 and is an Associate Professor of Computational Physics there, where his group studies quantum many-body systems with machine learning.

Timeline

  1. 2010

    A PhD at SISSA

    In 2010, he completes a PhD in Physics at SISSA with a thesis on the Bose-Hubbard model with disorder in low-dimensional lattices.

  2. 2011–2016

    Postdoctoral work at Georgetown and Perimeter

    He is a postdoctoral fellow at Georgetown University from 2011 to 2013 and at the Perimeter Institute from 2013 to 2016.

  3. August 2016

    Machine learning phases of matter

    In August 2016, he presents Machine Learning Phases of Matter at Perimeter's Quantum Machine Learning conference. His research uses neural networks to learn representations of ordered and topologically ordered states of matter.

  4. November 2022

    Recurrent neural networks for many-body physics

    In November 2022, he presents recurrent neural-network approaches to quantum many-body physics at the Perimeter Institute. The methods support quantum-state reconstruction and real-time simulation in open systems. The talk also covers many-body ground states with long-range order, frustration and topological order.

  5. September 2023–January 2024

    Appointment at ETH Zürich

    In September 2023, ETH appoints him Associate Professor of Computational Physics; he is then an Assistant Professor at the University of Toronto. He starts at ETH on 1 January 2024 after research scientist roles at D-Wave Systems and the Vector Institute.

  6. April 2024

    Language models for Rydberg atoms

    In April 2024, he presents language models for solving quantum Hamiltonian ground states, including arrays of Rydberg atoms on a Kagome lattice. His results align with quantum Monte Carlo work and support a highly frustrated paramagnetic phase.

  7. May 2026

    Quantum machine learning for simulation

    In May 2026, he presents methods to simulate and compress out-of-equilibrium dynamics in two-dimensional quantum systems. His compression strategies use quantum machine learning to reduce gate counts and support simulations of lattice fermions.

  8. As of October 2026

    Associate professor and group leader

    As of October 2026, he is an Associate Professor and Group Leader in ETH Zürich's Institute for Theoretical Physics, within the Computational Physics unit. His research combines quantum Monte Carlo and machine learning to study collective behaviour in quantum many-body systems and identify phases of matter.

Career

  1. NowETH ZurichAssociate Professor and Group Leader
  2. Until 2023University of TorontoAssistant Professor
  3. 2013–2016Perimeter Institute for Theoretical PhysicsPostdoctoral fellow
  4. 2011–2013Georgetown UniversityPostdoctoral fellow
  5. D-Wave SystemsResearch scientist
  6. Vector InstituteResearch scientist

Education

  1. 2010International School for Advanced StudiesPhD in Physics

From the biography.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes ETH Zurich. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes ETH Zurich. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes ETH Zurich. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Universities had a net outflow of 2,068 moves in AI careersIncludes ETH Zurich. Our estimates of career flows and median h-index across universities and companies in AI, including the role of joint appointments and earlier academic jobs.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Juan Felipe Carrasquilla Álvarez yet. Send us a free-licensed photo.

  1. Juan Felipe Carrasquilla Álvarez — Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.
  2. Alumni — Condensed Matter Theory cm.sissa.it. Checked 21 October 2026.
  3. Machine Learning Phases of Matter | PIRSA pirsa.org. Checked 21 October 2026.
  4. Juan Felipe Carrasquilla Alvarez carrasqu.github.io. Checked 21 October 2026.
  5. Quantum Matter Workshop: Recurrent neural networks for many-body physics | Perimeter Events events.perimeterinstitute.ca. Checked 21 October 2026.
  6. Five professors appointed | ETH Zurich ethz.ch. Checked 21 October 2026.
  7. New year, new professors – Department of Physics | ETH Zurich phys.ethz.ch. Checked 21 October 2026.
  8. QSE Quantum Seminar: Language Models for the Simulation of Quantum Many-Body Systems | EPFL memento.epfl.ch. Checked 21 October 2026.
  9. Heisenberg picture simulation of two-dimensional dynamics and its compression | PIRSA pirsa.org. Checked 21 October 2026.
  10. D-PHYS phonebook phonebook.phys.ethz.ch. Checked 21 October 2026.
  11. Juan Felipe Carrasquilla Álvarez — Acceleration Consortium acceleration.utoronto.ca. Checked 21 October 2026.