ABOUT LIN's RESEARCH
Materials and Manufacturing Intelligence
Dr. Lin’s research group is conducting highly interdisciplinary research which dedicates computational and experimental research in advanced manufacturing and materials to promote biomedical, energy, and robotics fields. The research lies in three main clusters: 1) smart manufacturing powered by artificial intelligence; 2) programmable materials and devices; 3) robotics. His work has been published in top-tier journal papers and reported by many media outlets.
12/2019 Machine learning assisted material synthesis
Sheldon published a paper about machine learning for metal organic nanocapsule synthesis in JACS with a title of "Machine learning assisted synthesis metal organic synthesis". The work shows the power of machine learning algorithms for predicting synthesis outcomes given input successful and failed experimental data as well as for extracting chemical intuition from the hidden information in the high dimensional space!
04/2019 Organize MRS 2020 Spring conference
Together with scientists from Livermore National Lab, Tufts University, and University of Manchester, Dr. J. Lin will organize a symposium titled "Artificial Intelligence for Material Design, Processing, and Characterizations" in 2020 MRS Spring conference. The symposium is now online and will be open for abstract submission on Sept. 26th. Welcome to submit your abstracts!
02/2019 Material science meets deep learning
Yuan and Jerry published our FIRST machine learning related paper entitled “Bandgap prediction by deep learning in configurationally hybridized graphene and boron nitride.” in npj Computional Materials. It is really a long and tough process. Excellent job, guys! This work was heavily reported by multiple media such as ScienceDaily, Phys.org, Facebook, Futurity, Technology Networks, InnovationToronto, RobotConsumer, Akil Media. It was also mentioned in the website of our sponsor DOE NETL.