Alexander Del Toro Barba

Alexander Del Toro Barba, PhD

Alexander is passionate about two topics: machine learning and quantum computing. During his PhD about machine learning in finance he worked in financial asset management to determine where machine learning can contribute add-value over classical methods. 

After earning his PhD in 2018, he joined Google Cloud as machine learning specialist where he supports industry customers in building custom, large-scale AI. In 2020, Alexander became practice lead for AI/ML in DACH, in 2021 for EMEA North, and from 2023 to 2024 interim manager for the machine learning specialists team, before he moved back into a senior IC role as machine learning specialist (Github).

Alexander is working closely with Google engineering, product and customers to steer new AI solutions into production. He is driving a large community of ML engineers and supports management in prioritizing and reviewing expert requests for AI engagements. Additionally, Alexander contributed to DeepMind applied research for energy optimization.

Since 2021, Alexander also collaborates closely with the Google Quantum AI research team. He built up and leads a global quantum computing practice to cover customer requests and lead engagements, and he contributed to scientific research such as for quantum topological data analysis and for quantum machine learning. He publishes technical articles about quantum algorithms on medium and GithubAlexanders long-term goal is to unify classical machine learning with quantum computing.

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RESEARCH

🔭


quantum algorithms quantum machine learning

My passion are quantum algorithms, particularly quantum machine learning, searching for exponential separations between classical and quantum learners. My favorite topics are quantum linear algebra, dequantization and topological data analysis.

PUBLICATIONS

American Physical Society

Analyzing Prospects for Quantum Advantage in Topological Data Analysis,

PRX Quantum 5 (1), 010319 (2024)

Science

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Science 384, 48-53  (2024)

Stable quantum-correlated many-body states through engineered dissipation 

Science 383, 1332-1337 (2024)

Nature

Thermalization and criticality on an analogue–digital quantum simulator

Nature 638, 79-85 (2025)

Phase transitions in Random Circuit Sampling

Nature 634, 328-333 (2024)

Measurement-induced entanglement and teleportation on a noisy quantum processor

Nature 622, 481–486 (2023)


Non-Abelian braiding of graph vertices in a superconducting processor

Nature 618, 264–269 (2023)


Suppressing quantum errors by scaling a surface code logical qubit

Nature 614, 676–681 (2023)


Formation of robust bound states of interacting microwave photons 

Nature 612, 240–245 (2022)

arXiv

Demonstrating Dynamic Surface Codes 

arXiv: 2412.14360 (2024)

Observation of disorder-free localization and efficient disorder averaging on a quantum processor 

arXiv:2410.06557 (2024)


This publication list from Google Scholar include Google Quantum AI research milestone papers as a team collaborator, as well as focus papers with direct contributions as an author.

SPEAKER

(2024) Keynote about Quantum Machine Learning at ML Prague conference

(2023) Podcast about quantum computing on Spotify, Google or Apple

(2022) Conference on Quantum Technologies for High-Energy Physics  at CERN

CURRICULUM

(2023-24) Interim Manager Machine Learning Specialists EMEA-North

(2022) Global practice lead for quantum computing at Google Cloud

(2022) Practice lead Machine Learning EMEA-North

(2020) Practice lead Machine Learning DACH

(2020) Contributing to DeepMind on AI research for Google Cloud

(2018) Machine learning specialist at Google Cloud

(2018) PhD in computational finance (economics) on machine learning for financial market stability at  University of Münster


2025 © Alexander Del Toro Barba