電子郵件：[email protected]
研究方向
人工智能，3D打印，智慧化工，大數(shù)據(jù)，碳減排，遙感與環(huán)境資源，大氣污染防治，健康暴露量評(píng)估。
教育背景與工作經(jīng)歷
2024-至今： 中國(guó)石油大學(xué)（北京），化學(xué)工程與環(huán)境學(xué)院，環(huán)境科學(xué)與工程系，講師
2023-2024： 康奈爾大學(xué)，土木與環(huán)境工程學(xué)院，博士后研究員
2021-2022： 加州大學(xué)戴維斯分校，農(nóng)業(yè)與環(huán)境科學(xué)學(xué)院，博士后研究員
2016-2021： 加州大學(xué)戴維斯分校，大氣科學(xué)，博士，導(dǎo)師：Deb Niemeier教授（美國(guó)工程院院士），
統(tǒng)計(jì)學(xué)，碩士
2014-2016： 密歇根大學(xué)安娜堡分校，環(huán)境工程，碩士，導(dǎo)師：Herek Clack教授和Brian Ellis教授
2012-2013： 莫那什大學(xué)，環(huán)境工程，學(xué)士，導(dǎo)師：Gavin Mudd教授
2009-2013： 同濟(jì)大學(xué)，環(huán)境工程，學(xué)士
學(xué)術(shù)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. https://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. https://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. https://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, https://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; https://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). https://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. https://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. https://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; https://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 (國(guó)際頂會(huì)), 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 (國(guó)際頂會(huì)), 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 (國(guó)際頂會(huì)), 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 (國(guó)際頂會(huì)), 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 (國(guó)際會(huì)議), 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 (國(guó)際頂會(huì)), Boston, MA.
基金主持/參與
（1）拔尖人才科研啟動(dòng)基金：人工智能與3D打印輔助化工反應(yīng)器設(shè)計(jì)與優(yōu)化 2025-01至2027-12。
（2）美國(guó)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, 20萬(wàn)元, 主持。
（3）美國(guó)-以色列跨國(guó)農(nóng)業(yè)研究與發(fā)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，200萬(wàn)元，主要參與。
（4）美國(guó)國(guó)家科學(xué)基金（NSF）：2102344，RAPID: Effects of wildfires on lake productivity and oxygen deficits in the western U.S.，2020-至今，140萬(wàn)元，主要參與。
（5）加州杏仁委員會(huì)基金：Yield Prediction for Resource Management and Yield Optimization in Almond， 2021-至今，主要參與。
科研項(xiàng)目
貝葉斯優(yōu)化算法與人工智能模型結(jié)合實(shí)現(xiàn)金屬合金的3D打印性能提升
- 通過(guò)實(shí)驗(yàn)數(shù)據(jù)驅(qū)動(dòng)人工智能算法實(shí)現(xiàn)對(duì)于金屬合金3D打印性能的預(yù)測(cè)。
- 耦合貝葉斯優(yōu)化算法實(shí)現(xiàn)金屬合金3D打印性能的優(yōu)化與提升。
遺傳算法與3D打印結(jié)合優(yōu)化Li/Al-LDH系列反應(yīng)器
- 提出AI模型、遺傳算法與3D打印相結(jié)合的反應(yīng)器制備策略。
- 利用流體仿真模擬計(jì)算與AI模型耦合實(shí)現(xiàn)對(duì)于流體行為的快速預(yù)測(cè)。
- 借助遺傳算法優(yōu)化Li/Al-LDH系列反應(yīng)器的空間結(jié)構(gòu)。
- 利用3D 打印技術(shù)實(shí)現(xiàn)了優(yōu)化后Li/Al-LDH系列反應(yīng)器的快速制備。
3D打印的鈦基離子篩整體吸附劑用于從鹽湖中選擇性回收鋰
- 采用3D打印結(jié)合原位生長(zhǎng)策略制備了具有高吸附能力的固定床填料。
- 在動(dòng)態(tài)提鋰實(shí)驗(yàn)中實(shí)現(xiàn)高吸附性能的填料和高洗脫效率。
3D打印鈦基離子篩整體吸附劑用于從鹽湖中選擇性回收鋰
- 通過(guò)蒙脫石作為粘結(jié)劑集合3D打印技術(shù)制備了LIS含量為75%的整體式吸附劑。
- 通過(guò)動(dòng)態(tài)吸附實(shí)驗(yàn)表明3D打印整體吸附劑在鹽湖鋰回收中具有良好的應(yīng)用前景。
