Javier Heras-Domingo

I am a chemist from Barcelona with a strong interest in materials science, catalysis, and artificial intelligence (AI). My work lies at the intersection of computational chemistry and machine learning, with a growing focus on the Digital Chemistry field, using data-driven and automated approaches to accelerate chemical discovery.

I earned my degree in chemistry with a specialization in Materials Science from the Universitat Autònoma de Barcelona, and later completed my Ph.D. in the Computational BioNanoCat research group under the supervision of Prof. Mariona Sodupe and Prof. Xavier Solans-Monfort. My doctoral research focused on comparing the catalytic performance of Ruthenium Oxide (RuO2) surfaces and nanoparticles for the oxygen evolution reaction (OER).

As part of my Ph.D., I conducted a research staty at ETH-Zurich in collaboration with Prof. Christophe Copéret, where I investigated supported iridium single-atom catalysts (SACs) on indium tin oxide (ITO). This collaboration contributed to the international mention of my Ph.D.

In 2020, I joined Prof. Zachary Ulissi’s group at Carnegie Mellon University as a postdoctoral researcher. There, I focused on the discovery of multi-metallic oxide catalysts for clean energy technologies, combining high-throughput computations, machine learning models, and autonomous workflows. This work was carried out in collaboration with the FAIR team at Meta AI and Prof. Edward Sargent’s group at the University of Toronto.

From January 2023 to mid-2025, I have been a postdoctoral researacher in the group of Prof. Núria López’s at the Institute of Chemical Research of Catalonia (ICIQ), where I focused on developing AI-powered approaches for catalysis. As of mid-2025, I have begun a new position as Lecturer (Assistant Professor) at the University of Barcelona, where I continue to pursue research at the intersection of chemistry, data science, and automation, while also contributing to academic teaching and mentoring.