Meiqi Yang

Office 020,

86 Olden Street,

Princeton, NJ 08540

I am a final year Ph.D. candidate in the Department of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment at Princeton University. I am currently supervised by Dr. Jason Ren at the Princeton WET Lab. I also work closely with Dr. Howard A. Stone from the Department of Mechanical and Aerospace Engineering. Before joining Princeton, I obtained my M.S. degree from Yale University and worked as a full-time research assistant with Drs. Menachem Elimelech and Shu Hu.

My current research focuses on designing advanced materials and developing models to enhance the efficiency and reduce the cost of resource recovery from wastewater through data-driven modeling and advanced machine learning techniques. I aim to leverage these innovative approaches to address critical environmental challenges and contribute to sustainable resource management.

news

May 14, 2024	Our paper “Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery” had been selected as front cover of Environmental Science & Technology.
Mar 20, 2024	Our study “Machine Learning in Environmental Research: Common Pitfalls and Best Practices” had been selected as supplementary art of Environmental Science & Technology.
Mar 20, 2024	I am hornored to recieved the Graduate Conferences Fellowship from Andlinger Center for Energy and the Environment 2024.
Sep 01, 2023	Our paper “Spatially Separated Crystallization for Selective Lithium Extraction from Saline Water” had been selected as Front Cover of Nature Water, and reported by Princeton News Release
Jun 28, 2023	Our study “Highly Selective Electrochemical Nitrate to Ammonia Conversion by Dispersed Ru in a Multielement Alloy Catalyst” had been selected as supplementary art of Nano Letters.
Jun 20, 2023	I am hornored to recieved the Graduate Conferences Fellowship from Andlinger Center for Energy and the Environment 2023.

selected publications

ES&T

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management

Meiqi Yang, Jun-Jie Zhu, Allyson McGaughey , and 3 more authors

Environmental Science & Technology, 2023

Bib HTML

@article{yang2023predicting,
  title = {Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management},
  author = {Yang, Meiqi and Zhu, Jun-Jie and McGaughey, Allyson and Zheng, Sunxiang and D. Priestley, Rodney and Ren, Zhiyong Jason},
  journal = {Environmental Science \& Technology},
  year = {2023}
}

ES&T

Machine learning in environmental research: common pitfalls and best practices

Jun-Jie Zhu, Meiqi Yang, and Zhiyong Jason Ren

Environmental Science & Technology, 2023

Bib HTML

@article{zhu2023machine,
  title = {Machine learning in environmental research: common pitfalls and best practices},
  author = {Zhu, Jun-Jie and Yang, Meiqi and Ren, Zhiyong Jason},
  journal = {Environmental Science \& Technology},
  volume = {57},
  number = {46},
  pages = {17671--17689},
  year = {2023},
  publisher = {American Chemical Society}
}

Nature Water

Spatially separated crystallization for selective lithium extraction from saline water

Meiqi Yang, Xi Chen, Sunxiang Zheng , and 7 more authors

Nature Water, 2023

Bib HTML

@article{chen2023spatially,
  title = {Spatially separated crystallization for selective lithium extraction from saline water},
  author = {Yang, Meiqi and Chen, Xi and Zheng, Sunxiang and Temprano-Coleto, Fernando and Dong, Qi and Cheng, Guangming and Yao, Nan and Stone, Howard A and Hu, Liangbing and Ren, Zhiyong Jason},
  journal = {Nature Water},
  volume = {1},
  number = {9},
  pages = {808--817},
  year = {2023},
  publisher = {Nature Publishing Group UK London}
}

ES&T

Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery

Meiqi Yang, Jun-Jie Zhu, Allyson L McGaughey , and 4 more authors

Environmental Science & Technology, 2024

Bib HTML

@article{yang2024machine,
  title = {Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery},
  author = {Yang, Meiqi and Zhu, Jun-Jie and McGaughey, Allyson L and Priestley, Rodney D and Hoek, Eric MV and Jassby, David and Ren, Zhiyong Jason},
  journal = {Environmental Science \& Technology},
  year = {2024},
  publisher = {American Chemical Society}
}