Dr. Yuankai Huang is currently an Assistant Professor at the Department of Civil, Construction,
& Environmental Engineering at the University of Memphis. His research explores the
intersection of diverse disciplines to address critical challenges related to water, food, energy,
sensors, and data. Specifically, He is passionate about pioneering real-time water/soil quality
monitoring through the design of robust, reliable sensors, advancing decentralized
water/agriculture systems that couple wastewater treatment with resource recovery and food
production, and harnessing the power of novel computational and data-driven methods to
revolutionize digital water-energy infrastructure and precision agriculture. Dr. Huang earned his
Ph.D. in Environmental Engineering from the University of Connecticut (2022) and completed a
postdoctoral fellowship in the School of Civil & Environmental Engineering at the Georgia
Institute of Technology (2024).

Personal Website: The Huang Lab – Water-Sensor-Resource-Food-Data

Education

• Ph.D. Environmental Engineering, University of Connecticut, Storrs, CT, USA, 2022
• M. Sc. Environmental Engineering,South China University of Technology, Guangzhou, China, 2015
• B. Sc. Environmental Science, South China University of Technology, Guangzhou, China, 2012

 
Professional Experience

• Assistant Professor, Department of Civil, Construction, and Environmental Engineering, The University of Memphis (8/2024-Present)
• Postdoctoral Fellow, Georgia Institute of Technology (7/2022-6/2024)
• Graduate Teaching Assistant, The University of Connecticut (1/2019-5/2021)
• Graduate Research Assistant, The University of Connecticut (8/2016-5/2022)
• Graduate Research Assistant, South China University of Technology, (9/2012-6/2015)

 

Research Interest:

• Reliable sensors development for real-time water/soil quality monitoring.
• Energy-sustainable water treatment processes.
• Digital Water-Energy-Agriculture-Food Nexus.

 

Selected Publications:

Huang, Y., Zhong, S., Gan, L., & Chen, Y.* (2024). Development of Machine Learning Models for Ion-Selective Electrode Cation Sensor Design. ACS ES&T Engineering, 4(7), 1702–1711. https://doi.org/10.1021/acsestengg.4c00087

Huang, Y., Afolabi, M. A., Gan, L., Liu, S., & Chen, Y.* (2024). MXene-Coated Ion-Selective Electrode Sensors for Highly Stable and Selective Lithium Dynamics Monitoring. Environmental Science & Technology, 58(2), 1359–1368. Front Cover https://doi.org/10.1021/acs.est.3c06235

Huang, Y., Zhang, J., Ren, Z., Xiang, W., Sifat, I., Zhang, W., Zhu, J., & Li, B.* (2023). Next Generation Decentralized Water Systems: A Water-Energy-Infrastructure-Human Nexus (WEIHN) Approach. Environmental Science: Water Research & Technology, 9(10), 2446–2471. https://doi.org/10.1039/D3EW00506B

Huang, Y., Qian, X., Wang, X., Wang, T., Lounder, S. J., Ravindran, T., Demitrack, Z., McCutcheon, J., Asatekin, A., & Li, B.* (2022). Electrospraying Zwitterionic Copolymers as an Effective Biofouling Control for Accurate and Continuous Monitoring of Wastewater Dynamics in a Real-Time and Long-Term Manner. Environmental Science & Technology, 56(12), 8176–8186. https://doi.org/10.1021/acs.est.2c01501

Huang, Y., Wang, X., Xiang, W., Wang, T., Otis, C., Sarge, L., Lei, Y., & Li, B.* (2022). Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review. Environmental Science & Technology, 56(9), 5334–5354. https://doi.org/10.1021/acs.est.1c07857

Wang, T., Cui, C., Huang, Y., Fan, Y., Xu, Z., Sarge, L., Bagtzoglou, C., Brückner, C., Gao, P., & Li, B.* (2022). Ion Selective Nano-mesh Electrode for Long-term Continuous Monitoring of Wastewater Quality Fabricated using Template-guided Membrane Immobilization. Environmental Science: Nano, 9(6), 2149–2160. https://doi.org/10.1039/D1EN00966D

Fan, Y., Qian, F., Huang, Y., Sifat, I., Zhang, C., Depasquale, A., Wang, L., & Li, B.* (2021). Miniature microbial fuel cells integrated with triggered power management systems to power wastewater sensors in an uninterrupted mode. Applied Energy, 302, 117556. https://doi.org/10.1016/j.apenergy.2021.117556

Fan, Y., Huang, Y., Linthicum, W., Liu, F., Beringhs, A. O., Dang, Y., Xu, Z., Chang, S.-Y., Ling, J., Huey, B. D., Suib, S. L., Ma, A. W. K., Gao, P.-X., Lu, X., Lei, Y., Shaw, M. T., & Li, B.* (2020). Toward Long-Term Accurate and Continuous Monitoring of Nitrate in Wastewater Using Poly(tetrafluoroethylene) (PTFE)–Solid-State Ion-Selective Electrodes (S-ISEs). ACS Sensors, 5(10), 3182–3193. https://doi.org/10.1021/acssensors.0c01422

Huang, Y., Wang, T., Xu, Z., Hughes, E., Qian, F., Lee, M., Fan, Y., Lei, Y., Brückner, C., & Li, B.* (2019). Real-Time in Situ Monitoring of Nitrogen Dynamics in Wastewater Treatment Processes using Wireless, Solid-State, and Ion-Selective Membrane Sensors. Environmental Science & Technology, 53(6), 3140–3148. https://doi.org/10.1021/acs.est.8b05928

Huang, Y., MahmoodPoor Dehkordy, F., Li, Y., Emadi, S., Bagtzoglou, A., & Li, B.* (2018). Enhancing Anaerobic Fermentation Performance through Eccentrically Stirred Mixing: Experimental and Modeling Methodology. Chemical Engineering Journal, 334, 1383–1391. https://doi.org/10.1016/j.cej.2017.11.088