This list will be updated periodically.

Adam Gormley

Adam Gormley

Rutgers University

Adam Gormley is an Associate Professor of Biomedical Engineering at Rutgers University, Executive Editor of Advanced Drug Delivery Reviews, and co-founder of Plexymer, Inc. His group is developing a self-driving lab for polymer biomaterials.

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Antonio Helio Castro Neto

Antonio Helio Castro Neto

National University of Singapore

Prof. Antonio H. Castro Neto got his Ph.D. in Physics at University of Illinois at Urbana-Champaign in 1994. His thesis studied the fundamentals of the theory of metals. In 1994, he moved to the Institute for Theoretical Physics at the University of California at Santa Barbara as a postdoctoral fellow where he dedicated his attention to low dimensional materials such as high temperature superconductors and conducting polymers. In 1995, he became an Assistant Professor at University of California at Riverside where he wrote fundamental work on the theory of disordered magnetic materials. In 2000, he moved to Boston University as Professor of Physics. At Boston, Prof. Castro Neto became one of the leading theorists in the study of graphene and other two dimensional materials. Since 2010, Prof. Castro Neto is the Director of the Graphene Research Center and in 2014 he became Director of the Centre for Advanced 2D Materials funded by the National Research Foundation of Singapore.

Prof. Castro Neto is a Distinguished Professor in the Department of Material Science Engineering and Physics, he is also Professor at the Department of Electrical and Computer Engineering, at the National University of Singapore. In 2003, Prof. Castro Neto was elected a fellow of the American Physical Society (APS) and in 2011 he was elected a fellow of the American Association for the Advancement of Science (AAAS). He is the Colloquia Editor for Reviews of Modern Physics, and member of the Editorial Board of “Chinese Physics B” and “Acta Physica Sinica”.

Prof. Castro Neto was awarded the 11th Ross J. Martin Award by the University of Illinois at Urbana-Champaign; the University of California Regent Fellowship; the Alfred P. Sloan Research Fellowship; the visiting Miller Professorship by the University of California, Berkeley; the visiting Gordon Godfrey Professorship by the University of New South Wales, Australia; the Distinguished Visiting Chair Professor at the SKKU Advanced Institute of Nano-Technology (SAINT), South Korea; the Hsun Lee Lecture Award by the Institute of Metal Research at the Chinese Academy of Sciences; and Kramers Professorship at the University of Utrecht, the Netherlands.

In 2016, Prof. Castro Neto founded 2D Materials (2DM) Pte Ltd in Singapore for the development of high quality graphene, in 2017 he founded MADE Advanced Materials Pte Ltd for the development of graphene composites with carbon and glass fibers, in 2108 he founded PHASE Events Pte Ltd with the objective of scientific events in order to educate industry and academia on nano-materials and nano-technology, in 2019 he founded Graphene Watts Pte Ltd for the development and commercialization of graphene-based, Lithium-Sulfur, batteries.

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Artem Mishchenko

Artem Mishchenko

University of Manchester • Google DeepMind • EPFL • Collegium Helveticum

Artem Mishchenko works at the intersection of machine learning and scientific discovery, with interests spanning physics- and materials-related applications.

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Bartosz Grzybowski

Bartosz Grzybowski

Ulsan National Institute of Science and Technology • IBS Center for Algorithmic and Robotized Synthesis • Institute of Organic Chemistry • OPCW - Scientific Advisory Board

Bartosz Grzybowski works on chemistry and automated synthesis, including data-driven approaches aligned with self-driving laboratories.

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Bingqing Cheng

Bingqing Cheng

UC Berkeley • ISTA

Bingqing Cheng develops computational and AI-enabled approaches for chemistry and materials science.

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Bin Ouyang

Bin Ouyang

Florida State University

Bin Ouyang is an assistant professor in the Department of Chemistry and Biochemistry at Florida State University. His research focuses on high-throughput computation, data mining, and machine learning to understand structure–property relationships and predictive synthesis of disordered energy materials.

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Carlo Vittorio Cannistraci

Carlo Vittorio Cannistraci

Tsinghua University • TU Dresden

Carlo Vittorio Cannistraci is a Professor of Biomedical Cybernetics whose research spans AI for biology, algorithmic network science, and unconventional computing inspired by neural topologies.

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Curtis Berlinguette

Curtis Berlinguette

University of British Columbia • CIFAR • SBQMI

Curtis Berlinguette is a global leader in self-driving labs, AI-enabled chemical discovery, and accelerated materials research for energy technologies.

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Eun-Ah Kim

Eun-Ah Kim

Cornell University

Eun-Ah Kim is a theoretical physicist whose work includes quantum many-body systems and related computational approaches.

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Felix Hanke

Felix Hanke

CuspAI

Felix Hanke is a distinguished researcher and software engineer with extensive experience enabling materials simulations across multiple industries.

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Giacomo Indiveri

Giacomo Indiveri

University of Zurich • ETH Zurich

Giacomo Indiveri is a Professor of Neuromorphic Cognitive Systems at the University of Zurich and ETH Zurich. His work spans neuromorphic mixed-signal circuits, brain-inspired computing, and real-world intelligent systems.

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Haizhao Yang

Haizhao Yang

University of Maryland • UMIACS • AIM • Center for Machine Learning

Haizhao Yang develops mathematical and machine-learning methods with applications in scientific modelling and computational physics.

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Helge Stein

Helge Stein

Technical University of Munich • Munich Center for Machine Learning

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Jacqueline Cole

Jacqueline Cole

University of Cambridge

Jacqueline Cole applies computation and machine learning to chemistry and materials, including structure–property modelling and discovery workflows.

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Jonathan Schmidt

Jonathan Schmidt

ETH Zurich

Jonathan Schmidt develops AI-driven materials science methods and data-centric approaches for physical modelling.

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Jun Jiang

Jun Jiang

USTC • Hefei National Laboratory

Jun Jiang works on AI agents, intelligent chemistry automation, and self-driving laboratory systems for accelerated molecular discovery.

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Karsten Reuter

Karsten Reuter

Fritz Haber Institute • Max Planck Society

Karsten Reuter directs the Theory Department at the Fritz Haber Institute, developing multiscale and AI-accelerated models for catalysis and energy technology.

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Keith Brown

Keith Brown

Boston University

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Kourosh Darvish

Kourosh Darvish

Acceleration Consortium • University of Toronto

Kourosh Darvish is a robotics and AI researcher working at the intersection of reinforcement learning and control, computer vision, and reasoning and planning. He is currently a Staff Scientist and Principal Investigator at the AI and Automation Lab at the Acceleration Consortium, University of Toronto, developing autonomous robotic systems for self-driving laboratories operating 24/7.

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Laura Matz

Laura Matz

Merck KGaA, Darmstadt, Germany

Dr. Laura Matz is the Chief Science and Technology Officer for Merck, driving innovation and digitalization across Life Science, Healthcare, and Electronics, with a focus on new digital business models and secure data sharing.

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Lauren Takahashi

Lauren Takahashi

Hokkaido University

Lauren Takahashi develops AI systems that incorporate meaning into chemical data and builds open-source 3D printed robots that can design, conduct, and evaluate experiments autonomously alongside human scientists.

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Liu Chong

Liu Chong

UCLA

Liu Chong works in electrochemistry and materials-related research, including directions connected to accelerated discovery and automation.

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Luis Camuñas-Mesa

Luis Camuñas-Mesa

IMSE-CNM • CSIC • University of Seville

Luis Camuñas-Mesa works on neuromorphic systems, unconventional computing, and event-driven hardware architectures.

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Marco Bernardi

Marco Bernardi

Caltech

Marco Bernardi develops computational and AI-driven methods for electronic transport, excitons, and quantum phenomena in advanced materials.

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Maria K. Chan

Maria K. Chan

Argonne National Laboratory

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Melodie Christensen

Melodie Christensen

Merck

Melodie Christensen is a scientific leader with expertise in automation, data science, catalysis, and process chemistry. Proven track record in developing and implementing data-rich technologies in pharmaceutical process development. Skilled in driving technology investment and adoption. Exceptional in key talent identification and development. Excellent collaborator who thrives in multidisciplinary team environments. Effective communicator with a strong interest in organizational psychology.

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Milad Abolhasani

Milad Abolhasani

North Carolina State University • University of Toronto

Milad Abolhasani develops autonomous chemical discovery platforms combining AI, robotics, and flow chemistry.

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Mohamad Moosavi

Mohamad Moosavi

Vector Institute

Mohamad Moosavi is an Assistant Professor of Chemical Engineering and Applied Chemistry at the University of Toronto and a Faculty Affiliate of the Vector Institute. Mohamad directs the Artificial Intelligence for Chemical Science (AI4ChemS) research group, focusing on leveraging AI and computational methods for the discovery of advanced materials. His team’s current research is concentrated on developing MOFs and nanoporous materials for carbon capture and conversion, aiming to contribute to technology development for our sustainable future. Mohamad’s academic journey began with an undergraduate degree in Mechanical Engineering from Sharif University of Technology, Iran, followed by a PhD in Chemistry and Chemical Engineering from EPFL Switzerland, and a Postdoctoral Fellowship in Mathematics and Computer Science at the Free University of Berlin, Germany.

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Nasim Abdollahi

Nasim Abdollahi

Acceleration Consortium • University of Toronto

Nasim Abdollahi is an ML and AI specialist at the Acceleration Consortium, University of Toronto, supporting self-driving laboratory efforts.

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Ray Meng Gao

Ray Meng Gao

Meta

Ray Meng Gao works on AI methods and their applications across scientific problems, including chemistry, materials science, and physics.

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Santiago Miret

Santiago Miret

Lila Sciences

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Shoichi Matsuda

Shoichi Matsuda

NIMS

Shoichi Matsuda works on autonomous robotic experimentation in the field of rechargeable batteries, establishing closed-loop experimental workflows that enable the discovery and optimization of electrolyte compositions to maximize battery performance.

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Shyue Ping Ong

Shyue Ping Ong

National University of Singapore (NUS)

Prof Shyue Ping Ong is the Provost's Chair Professor in Materials Science and Engineering at the National University of Singapore. He leads the Materialyze.AI lab, a materials informatics research group focused on the integration of materials science with data science and artificial intelligence to accelerate the discovery and design of materials. He is widely recognized as one of the pioneers of foundation potentials, i.e., machine learning interatomic potentials with near-complete coverage of the periodic table that has broad applications in materials discovery and design. Prof Ong is also the founder and lead developer of pymatgen, one of the most popular open-source libraries for materials analysis, and a core contributor to the Materials Project, a public platform that provides computed properties of tens of thousands of inorganic compounds. Ong earned his PhD in Materials Science and Engineering from the Massachusetts Institute of Technology in 2011, and an MEng and BA in Electrical and Information Science from the University of Cambridge in 1999. He has authored more than 150 peer-reviewed publications, and has been recognized as a Clarivate Highly Cited Researcher since 2021.

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Simon J. L. Billinge

Simon J. L. Billinge

Columbia University • Brookhaven National Laboratory

Simon J. L. Billinge is a Professor of Materials Science, Applied Physics and Applied Mathematics at Columbia University and a physicist at Brookhaven National Laboratory. He develops advanced diffraction and data-science methods, including AI- and ML-driven analysis, to reveal local structure in complex materials.

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Tapio Schneider

Tapio Schneider

Caltech • Google Research

Tapio Schneider leads the Climate Modeling Alliance (CliMA), building next-generation Earth system models integrating physics and machine learning.

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Tommaso Dorigo

Tommaso Dorigo

INFN • University of Padova

Tommaso Dorigo is a senior scientist at INFN specialising in particle physics and machine learning, contributing to major projects including CMS at CERN.

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Torsten Hoefler

Torsten Hoefler

ETH Zurich • CSCS • Microsoft • Axelera AI • ELLIS • ADIA Lab

Torsten Hoefler works on high-performance computing and scalable machine-learning systems that enable next-generation scientific computing.

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Truyen Tran

Truyen Tran

Deakin University

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Ulrich S. Schubert

Ulrich S. Schubert

Friedrich Schiller University Jena

Ulrich S. Schubert is a full professor of Organic and Macromolecular Chemistry at Friedrich Schiller University Jena, head of the Laboratory of Organic and Macromolecular Chemistry and director of the Center for Energy and Environmental Chemistry Jena. His research focuses on functional and supramolecular polymers, polymer-based energy storage, and digitally assisted, high-throughput materials discovery.

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Vivek Natarajan

Vivek Natarajan

Google DeepMind

Vivek Natarajan is a Research Scientist at Google DeepMind leading research at the intersection of AI, science and medicine. He is the lead researcher behind Med-PaLM (Nature, 2023) and Med-PaLM 2 (Nature Medicine, 2025), and co-leads Project AMIE and the AI co-scientist program to accelerate scientific discovery.

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Wei Liu

Wei Liu

Changchun Institute of Applied Chemistry • Chinese Academy of Sciences

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Wen Jie Ong

Wen Jie Ong

NVIDIA

Wen Jie Ong is the Senior Product Manager for NVIDIA ALCHEMI. A chemist by training, he earned his PhD at MIT and previously advised chemicals and technology companies at McKinsey.

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Yuehaw Khoo

Yuehaw Khoo

University of Chicago

Yuehaw Khoo is an assistant Professor at the University of Chicago. He works in computational math, focusing on high-dimensional problems in many-body physics and structural biology. He did his postdoctoral study at Stanford University and graduate study at Princeton University.

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Yimu Zhao

Yimu Zhao

Acceleration Consortium • University of Toronto

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