Jie Chen

A new multimodal tool combines a large language model with powerful graph-based AI models to efficiently find new, synthesizable molecules with desired properties, based on a user's queries in plain language.

Researchers have developed a computationally efficient method that could be used to identify anomalies in the U.S. power grid in real time. The novel technique augments a special type of machine-learning model with a powerful graph structure, and does not require any labeled data to train.

A new MIT framework uses machine learning to simultaneously predict molecular properties and generate new molecules using only a small amount of data for training.

Researchers at the MIT-IBM Watson AI lab have developed a computationally efficient method that could be used to identify anomalies in the U.S. power grid in real time. The novel technique augments a special type of machine-learning model with a powerful graph structure, and does not require any labeled data to train.

Recently, the research team led by Dr. Shunping He from the Institute of Deep Sea Science and Engineering, Chinese Academy of Sciences, published their research findings in the online version of Science China Life Sciences.

Chemical engineers and materials scientists are constantly looking for the next revolutionary material, chemical, and drug. The rise of machine-learning approaches is expediting the discovery process, which could otherwise take years. "Ideally, the goal is to train a machine-learning model on a few existing chemical samples and then allow it to produce as many manufacturable molecules of the same class as possible,…

The tale of Taiwanese businessman Lee Meng-chu, detained in China four years ago, underscores the dangers of working in a China with shifting « red lines. »

A new study suggests that Clostridioides difficile is responsible for certain colorectal cancers. According to data gathered by scientists at the Bloomberg Kimmel Institute for Cancer Immunotherapy and the Johns Hopkins Kimmel Cancer Center, the bacterial species Clostridioides difficile, or C. dif

MIT and IBM researchers develop an efficient machine learning method that uses chemical knowledge to create a learnable grammar with production rules to build new, synthesizable monomers and polymers.

Residential exposure to fine particulate matter, nitrogen dioxide, and black carbon are positively linked to lung cancer incidence and mortality.

A new president means another round of reaction from Beijing.

Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to predict molecular properties and narrow down the molecules they need to synthesize and test in the lab.

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