This list will be updated periodically.
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.
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.
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.
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.
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.
Beatrice Soh
Department of Chemical and Biomolecular Engineering, National University of Singapore
Beatrice Soh is an assistant professor in the Department of Chemical and Biomolecular Engineering at the National University of Singapore (NUS). She works on integrating data-driven approaches with high-throughput single-molecule polymer experiments for applications in soft matter.
Berend Smit
EPFL • UC Berkeley • Lawrence Berkeley National Laboratory
Berend Smit is a Professor at EPFL. His work spans chemical engineering, physics, and computational chemistry.
Bingqing Cheng
UC Berkeley • ISTA
Bingqing Cheng develops computational and AI-enabled approaches for chemistry and materials science.
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.
Bowen Li
University of Toronto
Bowen Li is an Assistant Professor at the University of Toronto. His research combines pharmaceutical sciences with biomaterials, bioengineering, and immunology to develop nonviral delivery systems for nucleic acids, including RNA vaccines and therapeutics.
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.
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.
Eun-Ah Kim
Cornell University
Eun-Ah Kim is a theoretical physicist whose work includes quantum many-body systems and related computational approaches.
Felix Hanke
CuspAI
Felix Hanke is a distinguished researcher and software engineer with extensive experience enabling materials simulations across multiple industries.
Fernando Aguirre
Intrinsic Semiconductor Technologies Ltd.
Fernando Aguirre is a Senior Device Engineer at Intrinsic Semiconductor Technologies Ltd. His background includes electronic engineering, device research, and neuromorphic and memristor-related semiconductor technologies.
Gianmarco Mengaldo
Imperial College London
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.
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.
Ivor W. Tsang
CFAR
Professor Ivor W. Tsang is Director of the A*STAR Centre for Frontier AI Research (CFAR) and Adjunct Professor at the College of Computing and Data Science, Nanyang Technological University, Singapore. He has led Singapore’s national initiative on Trustworthy Foundation Models under the National Multimodal LLM Programme. He also leads research on Agentic World Models and oversees major national initiatives, including the AI Singapore Materials Design Grand Challenge and the Maritime AI Programme.
His research spans transfer learning, deep generative models, and big data analytics for ultra-high-dimensional data. His work has received international recognition, including the ARC Future Fellowship, the International Consortium of Chinese Mathematicians Best Paper Award, the IEEE TNN Outstanding 2004 Paper Award, the IEEE TMM 2014 Prize Paper Award, and recognition as the AI 2000 AAAI/IJCAI Most Influential Scholar in Australia in 2020. An IEEE Fellow, he is widely recognized for distinguished contributions to large-scale machine learning and transfer learning, and serves on the editorial boards of leading AI journals and program committees of top AI conferences.
His research spans transfer learning, deep generative models, and big data analytics for ultra-high-dimensional data. His work has received international recognition, including the ARC Future Fellowship, the International Consortium of Chinese Mathematicians Best Paper Award, the IEEE TNN Outstanding 2004 Paper Award, the IEEE TMM 2014 Prize Paper Award, and recognition as the AI 2000 AAAI/IJCAI Most Influential Scholar in Australia in 2020. An IEEE Fellow, he is widely recognized for distinguished contributions to large-scale machine learning and transfer learning, and serves on the editorial boards of leading AI journals and program committees of top AI conferences.
Jacqueline Cole
University of Cambridge
Jacqueline Cole applies computation and machine learning to chemistry and materials, including structure–property modelling and discovery workflows.
Jennifer Dodgson
Eigenform
Jennifer Dodgson is an AI researcher and CEO of Eigenform. Her work includes AI, LLMs, statistics, and related digital research applications.
Jonathan Schmidt
ETH Zurich
Jonathan Schmidt develops AI-driven materials science methods and data-centric approaches for physical modelling.
Jun Jiang
USTC • Hefei National Laboratory
Jun Jiang works on AI agents, intelligent chemistry automation, and self-driving laboratory systems for accelerated molecular discovery.
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.
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.
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.
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.
Lidong Bing
MiroMind AI • Shanda Group
Lidong Bing is the COO of MiroMind AI and Vice President of Shanda Group. Previously, Lidong was the Head of the Language Technology Lab at DAMO Academy of Alibaba Group. Lidong earned his Ph.D. from the Chinese University of Hong Kong and was a postdoctoral fellow at Carnegie Mellon University.
Currently, his research is centered on exploring new technological paradigms toward Artificial General Intelligence, with a focus on model architectures and training methods that enable strong generalization and autonomous learning. The key directions include self-evolving models and agents, non-autoregressive large language models, and multimodal pretraining.
He has published over 150 papers covering a wide range of topics, including large language models, vision-language models, and low-resource/multilingual NLP, garnering more than 23,000 peer citations. Additionally, he holds over 100 patents on cutting-edge techniques in artificial intelligence and machine learning.
Lidong serves as an Action Editor for Transactions of the Association for Computational Linguistics (TACL) and ACL Rolling Review (ARR), an Area Chair for AI conferences, and an Associate Editor for AI journals.
Currently, his research is centered on exploring new technological paradigms toward Artificial General Intelligence, with a focus on model architectures and training methods that enable strong generalization and autonomous learning. The key directions include self-evolving models and agents, non-autoregressive large language models, and multimodal pretraining.
He has published over 150 papers covering a wide range of topics, including large language models, vision-language models, and low-resource/multilingual NLP, garnering more than 23,000 peer citations. Additionally, he holds over 100 patents on cutting-edge techniques in artificial intelligence and machine learning.
Lidong serves as an Action Editor for Transactions of the Association for Computational Linguistics (TACL) and ACL Rolling Review (ARR), an Area Chair for AI conferences, and an Associate Editor for AI journals.
Liu Chong
UCLA
Liu Chong works in electrochemistry and materials-related research, including directions connected to accelerated discovery and automation.
Luis Camuñas-Mesa
IMSE-CNM • CSIC • University of Seville
Luis Camuñas-Mesa works on neuromorphic systems, unconventional computing, and event-driven hardware architectures.
Marco Bernardi
Caltech
Marco Bernardi develops computational and AI-driven methods for electronic transport, excitons, and quantum phenomena in advanced materials.
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.
Milad Abolhasani
North Carolina State University • University of Toronto
Milad Abolhasani develops autonomous chemical discovery platforms combining AI, robotics, and flow chemistry.
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.
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.
Peichen Zhong
Department of Materials Science and Engineering, National University of Singapore
Dr. Peichen Zhong is an Assistant Professor at the Department of Materials Science and Engineering, National University of Singapore. He obtained a BS in Physics from the University of Science and Technology of China (USTC) in 2018, followed by a PhD in Materials Science from UC Berkeley in 2023. He then completed the postdoctoral work at Lawrence Berkeley National Laboratory (LBNL) and Bakar Institute of Digital Materials for the Planet (BIDMaP). He was awarded the 2023 Rising Stars in Materials Science and Engineering by CMU/MIT/Stanford, the BIDMaP Emerging Scholar Fellowship from the College of Data Science, Computing and Society (CDSS) at UC Berkeley, and the AI2050 Early Career Fellowship by Schmidt Sciences.
Pengfei Ou
Department of Chemistry, National University of Singapore
Dr. Pengfei Ou is an Assistant Professor in the Department of Chemistry at the National University of Singapore, appointed with the NUS Presidential Young Professorship. He completed his Ph.D. in Materials Engineering at McGill University in 2020. He subsequently carried out postdoctoral research at the University of Toronto and Northwestern University from 2020 to 2024, before joining NUS Chemistry in August 2024. His research focuses on developing a computational framework that integrates DFT calculations, AIMD simulations, electrochemical interface modeling, active learning data generation, and machine-learned interatomic potentials for large-scale simulations, enabling predictive modeling of catalytic reactions and degradation at electrified interfaces.
Qianxiao Li
Department of Mathematics, National University of Singapore
Ray Meng Gao
Meta
Ray Meng Gao works on AI methods and their applications across scientific problems, including chemistry, materials science, and physics.
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.
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.
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.
Tapio Schneider
Caltech • Google Research
Tapio Schneider leads the Climate Modeling Alliance (CliMA), building next-generation Earth system models integrating physics and machine learning.
Tejs Vegge
DTU Energy
Tejs Vegge is a Professor at DTU Energy and works on autonomous materials discovery, computational materials design, and energy conversion and storage.
Ting Zhang
Suzhou Institute of Nanotech & Nanobionics
Ting Zhang is a full professor and director of the i-Lab department at the Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences. His work includes nanoelectronics, nanosensors, and nanofabrication.
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.
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.
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.
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.
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.
Yizhou Zhu
Westlake University
I am currently an assistant professor in the Department of Materials Science and Engineering from Westlake University. My current research interests includes: 1) Automated XRD analysis; 2) Rational solid state synthesis; 3) Machine learning force fields for solid electrolyte materials
Yousung Jung
Seoul National University
Yousung Jung is a Professor of Chemical and Biological Engineering at Seoul National University and an adjunct faculty member in the Graduate School of AI. His research includes quantum chemistry and machine learning for molecular and materials discovery.
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.
