电子邮件：mmtang@cqsbzx.com
研究方向
人工智能，3D打印，智慧化工，大数据，碳减排，遥感与环境资源，大气污染防治，健康暴露量评估。
教育背景与工作经历
2024-至今： 中国天天色天天（北京），化学工程与环境学院，环境科学与工程系，讲师
2023-2024： 康奈尔大学，土木与环境工程学院，博士后研究员
2021-2022： 加州大学戴维斯分校，农业与环境科学学院，博士后研究员
2016-2021： 加州大学戴维斯分校，大气科学，博士，导师：Deb Niemeier教授（美国工程院院士），
统计学，硕士
2014-2016： 密歇根大学安娜堡分校，环境工程，硕士，导师：Herek Clack教授和Brian Ellis教授
2012-2013： 莫那什大学，环境工程，学士，导师：Gavin Mudd教授
2009-2013： 同济大学，环境工程，学士
学术成果
Zhang, F., …, Tang M., et al. (2025) Coral Reef-like CdS/g-C3N5 Heterojunction with Enhanced CO2 Adsorption for Efficient Photocatalytic CO2 Reduction. Catalysts, 2025, 15, 94. http://doi.org/ 10.3390/catal15010094
Yu, J., Tang, M. et al. (2024) Computational fluid dynamics and machine learning assisted Al-LDH adsorbent reactor design for lithium recovery from salt lakes. Desalination, 2024, 600, 18396. http://doi.org/10.1016/j.desal.2024.118396
Tang, M., Li, X., (2024) Growing disparities in transportation noise exposure across major US cities over time. Transp Res D Transp Environ. 2024, 136, 104430. http://doi.org/ 10.1016/j.trd.2024.104430
Tang, M., Li, X., (2024) Hyper-local black carbon prediction by integrating land use variables with explainable machine learning model. Atmospheric Environment. Volume 336, 1 November 2024, http://doi.org/10.1016/j.atmosenv.2024.120733
Tang, M., Li, X., (2024) The Disparity of Greenness Accessibility across Major Metropolitan Areas in the United States from 2013 to 2022. Land. 2024, 13(8), 1182; http://doi.org/10.3390/land13081182
Smits, A.P., Scordo, F., Tang, M. et al. (2024) Wildfire smoke reduces lake ecosystem metabolic rates unequally across a trophic gradient. Communications Earth & Environment 5, 265 (2024). http://doi.org/10.1038/s43247-024-01404-9
Farruggia, M. J., …, Tang M., et al (2024) Wildfire smoke impacts lake ecosystems. Global Change Biology, 30, e17367. http://doi.org/10.1111/gcb.17367
Tang, M., Acharya TD, Niemeier D. (2023) Black Carbon Concentration Estimation with Mobile-Based Measurements in a Complex Urban Environment. ISPRS International Journal of Geo-Information. 2023; 12(7):290. http://doi.org/10.3390/ijgi12070290
Tang, M., et al. (2023). Tree-level almond yield estimation from high resolution aerial imagery with convolutional neural network. Front. Plant Sci. 14:1070699. Doi: 10.3389/fpls.2023.1070699
Tang, M., & Niemeier, D. (2021). How Air Pollution Influences Housing Price in Bay Area? International Journal of Environmental Research and Public Health. Int. J. Environ. Res. Public Health 2021, 18(22), 12195; http://doi.org/10.3390/ijerph182212195
Tang, M., & Niemeier, D. (2020). Using Big Data Techniques to Better Understand High-Resolution Cumulative Exposure Assessment of Traffic-Related Air Pollution. ACS EST Engg. Doi: 10.1021/acsestengg.0c00167
Tang, M., & Mudd, G. M. (2015). The pollution intensity of Australian power stations: a case study of the value of the National Pollutant Inventory (NPI). Environ Sci Pollut Res Int, 22(23), 18410-18424. Doi: 10.1007/s11356-015-5108-0
Tang, M., & Mudd, G. M. (2014). Canadian Power Stations and the National Pollutant Release Inventory (NPRI): A Success Story for Pollution Intensity? Water, Air, & Soil Pollution, 225(10), 2129. Doi: 10.1007/s11270-014-2129-0
Minmeng Tang, Dennis Sadowski, Peng Chen, Stavros George Vougioukas, Brandon Klever, Sat Darshan S. Khasla, Patrick Brown, and Yufang Jin (2022), Tree-level Almond Yield Prediction from High-Resolution Aerial Images with Deep Learning. Oral presentation at 2022 American Geophysical Union (AGU) Fall Meeting (国际顶会), Chicago, IL.
Minmeng Tang, Yufang Jin, Zhehan Tang, Brandon Klever, Sat Darshan Khalsa, and Patrick Brown (2022), Almond yield prediction with aerial imagery and convolution neural network. Poster presentation at 2022 The Almond Conference, Sacramento, CA.
Yufang Jin, Minmeng Tang, Zhehan Tang, Brandon Klever, Sat Darshan Khalsa, and Patrick Brown (2021), Almond yield prediction across scales: integrating remote sensing and machine learning. Poster presentation at 2021 The Almond Conference, Sacramento, CA.
Minmeng Tang, Deb Niemeier (2021), High-Resolution Cumulative Exposure Assessment of Traffic-Related Air Pollution with Different Google Navigation Route Options. Poster presentation at 2021 Traffic Research Board (TRB) Annual Meeting (国际顶会), virtural conference.
Minmeng Tang, Deb Niemeier (2020), A land use model for high-resolution black carbon estimation in Oakland, CA: A comparison of different machine learning models’ performance in spatial prediction. Poster presentation at 2020 American Geophysical Union (AGU) Fall Meeting (国际顶会), virtural conference.
Minmeng Tang, Deb Niemeier (2020), High-Resolution Cumulative Exposure Assessment of Traffic-Related Air Pollution with Different Google Navigation Route Options. Oral presentation at 2020 American Association for Aerosol Research (AAAR) 38th Annual Conference (国际顶会), virtual conference.
Minmeng Tang, Wenqing Jiang, Sonya Collier, Qi Zhang (2017), Impacts of solvent polarity on extraction of ambient fine particles. Poster presentation on 2017 International Aerosol modelling Algorithms Conference (国际会议), Davis, CA.
Brian R. Ellis, Wenjia Fan, Minmeng Tang, Kim F. Hayes, Wei Xiong, Daniel E. Giammar, Philip Skemer (2015) Alternation Fracture Geometries During Flow of Acidic Fluids: Implications for Subsurface Energy Technologies. Oral presentation at 2015 American Chemical Society (ACS) Fall Meeting (国际顶会), Boston, MA.
基金主持/参与
（1）拔尖人才科研启动基金：人工智能与3D打印辅助化工反应器设计与优化 2025-01至2027-12。
（2）美国交通部基金：USDOT 69A3551747109, Utilizing geo-statistical algorithms to improve urban scale traffic-related air pollution measurement for public health exposure assessments, 2019-06 至 2020-05, 20万元, 主持。
（3）美国-以色列跨国农业研究与发展基金： BARD IS-5430-21, Tree-based multilevel spatial decision support systems to close the yield gap in almond orchards，2021-至今，200万元，主要参与。
（4）美国国家科学基金（NSF）：2102344，RAPID: Effects of wildfires on lake productivity and oxygen deficits in the western U.S.，2020-至今，140万元，主要参与。
（5）加州杏仁委员会基金：Yield Prediction for Resource Management and Yield Optimization in Almond， 2021-至今，主要参与。
科研项目
贝叶斯优化算法与人工智能模型结合实现金属合金的3D打印性能提升
- 通过实验数据驱动人工智能算法实现对于金属合金3D打印性能的预测。
- 耦合贝叶斯优化算法实现金属合金3D打印性能的优化与提升。
遗传算法与3D打印结合优化Li/Al-LDH系列反应器
- 提出AI模型、遗传算法与3D打印相结合的反应器制备策略。
- 利用流体仿真模拟计算与AI模型耦合实现对于流体行为的快速预测。
- 借助遗传算法优化Li/Al-LDH系列反应器的空间结构。
- 利用3D 打印技术实现了优化后Li/Al-LDH系列反应器的快速制备。
3D打印的钛基离子筛整体吸附剂用于从盐湖中选择性回收锂
- 采用3D打印结合原位生长策略制备了具有高吸附能力的固定床填料。
- 在动态提锂实验中实现高吸附性能的填料和高洗脱效率。
3D打印钛基离子筛整体吸附剂用于从盐湖中选择性回收锂
- 通过蒙脱石作为粘结剂集合3D打印技术制备了LIS含量为75%的整体式吸附剂。
- 通过动态吸附实验表明3D打印整体吸附剂在盐湖锂回收中具有良好的应用前景。
