About COVIDScholar

This website uses natural language processing (NLP) to power search on a set of research papers related to COVID-19. It was created by the team behind Matscholar, a research effort led by the HackingMaterials, Persson, and Ceder research groups at Lawrence Berkeley National Lab.

This work is currently funded by a Laboratory Directed Research and Development grant at the Lawrence Berkeley National Laboratory of the US Department of Energy. It was assisted by funding for the development of NLP tools in Materials Science from the Energy Biosciences Institute at UC Berkeley, the National Science Foundation., and the C3.ai Digital Transformation Institute.

Citing

If you use COVIDScholar in your research, please cite COVIDScholar: An automated COVID-19 research aggregation and analysis platform

Our team

Gerbrand Ceder

Gerbrand Ceder is The Daniel M. Tellep Distinguished Professor in Engineering in the Department of Materials Science and Engineering at UC Berkeley. His research interests lie in computational and experimental materials design for clean energy technology, Materials Genome approaches to materials design and synthesis, and machine learning and NLP approaches to knowledge extraction.

Kristin Persson

Kristin Persson is a Professor at the University of California, Berkeley and a Senior Faculty Scientist at Lawrence Berkeley National Laboratory. She is the Director and co-founder of the Materials Project (www.materialsproject.org).

John Dagdelen

John is a PhD Student in the Persson Group at UC Berkeley and Lawrence Berkeley National Lab. His research sits at the intersection of materials science, artificial intelligence, and high-performance computing. John is also part of the team behind Matscholar, a materials science knowledge portal that uses state of the art NLP to aid in materials discovery and design.

Amalie Trewartha

Amalie is a postdoc in Gerbrand Ceder's group at Lawrence Berkeley National Lab. She began her career as a nuclear physicist, before moving into materials science in 2019, with a focus on machine learning. Her research interests include the application of NLP techniques to scientific literature, and building thermodynamically-motivated ML models for materials property prediction.

Haoyan Huo

Haoyan is a Materials Science PhD candidate in the Ceder Group at UC Berkeley and Lawrence Berkeley National Lab. He obtained his bachelor's degree in Physics and Economics from Peking University in 2017. He is currently interested in applying NLP/IR to materials science literature, as well as automatic designing of materials synthesis using ML methods.

Kevin Cruse

Kevin joined the Ceder Group at UC Berkeley as a Ph.D. student in 2019. He uses text mining and machine learning techniques to extract synthesis recipes from materials science literature.

Yuxing Fei

Yuxing joined Ceder Group at UC Berkeley in 2020 as an undergraduate intern. He avidly dabbles in machine learning (especially natural language processing) to accelerate the design of next-generation materials.

Zheren Wang

Zheren joined Ceder Group at UC Berkeley and LBNL in 2018 as a Ph.D. student. He focuses on using machine learning and optimization algorithm to find material synthesis conditions.

Tanjin He

Tanjin joined the Ceder Group as a Ph.D. student in 2017. His research interest includes materials synthesis and machine learning. He utilizes NLP methods to extract materials information from scientific literature and learns how to predict synthesis from the big data.

Akshay Subramanian

Akshay joined the Ceder Group at LBNL in 2020 as an undergraduate intern. He is interested in the application of Machine Learning to molecular optimization and Materials Science.

Ben Justus

Ben is a rising Junior at UC Berkeley studying materials science and engineering and electrical engineering and computer science (B.S. MSE/EECS). He is also a computational materials science research assistant at Lawrence Berkeley National Laboratory in the Persson Group.

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