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The value of human data annotation for machine learning based anomaly detection in environmental systems
Russo, S., Besmer, M. D., Blumensaat, F., Bouffard, D., Disch, A., Hammes, F., … Villez, K. (2021). The value of human data annotation for machine learning based anomaly detection in environmental systems. Water Research, 206, 117695 (10 pp.). https://doi.org/10.1016/j.watres.2021.117695
Electrochemical nitrite sensing for urine nitrification
Britschgi, L., Villez, K., Schrems, P., & Udert, K. M. (2020). Electrochemical nitrite sensing for urine nitrification. Water Research X, 9, 100055 (30 pp.). https://doi.org/10.1016/j.wroa.2020.100055
Can machines learn what we know? And should they?
Brupbacher, A., Menniti, A., & Villez, K. (2020). Can machines learn what we know? And should they? In 93rd Water environment federation technical exhibition and conference 2020 (WEFTEC 2020) (pp. 310-320). Water Environment Federation.
Active learning for anomaly detection in environmental data
Russo, S., Lürig, M., Hao, W., Matthews, B., & Villez, K. (2020). Active learning for anomaly detection in environmental data. Environmental Modelling and Software, 134, 104869 (11 pp.). https://doi.org/10.1016/j.envsoft.2020.104869
Benchmarking soft sensors for remote monitoring of on-site wastewater treatment plants
Schneider, M. Y., Furrer, V., Sprenger, E., Carbajal, J. P., Villez, K., & Maurer, M. (2020). Benchmarking soft sensors for remote monitoring of on-site wastewater treatment plants. Environmental Science and Technology, 54(17), 10840-10849. https://doi.org/10.1021/acs.est.9b07760
Monitoring and quantifying the treatment performance of on-site wastewater treatment plants
Schneider, M. Y. (2020). Monitoring and quantifying the treatment performance of on-site wastewater treatment plants [Doctoral dissertation, ETH Zurich]. https://doi.org/10.3929/ethz-b-000445338
A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems - with application to wastewater treatment plants
Villez, K., Vanrolleghem, P. A., & Corominas, L. (2020). A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems - with application to wastewater treatment plants. Computers and Chemical Engineering, 139, 106880 (14 pp.). https://doi.org/10.1016/j.compchemeng.2020.106880
Accounting for erroneous model structures in biokinetic process models
Villez, K., Del Giudice, D., Neumann, M. B., & Rieckermann, J. (2020). Accounting for erroneous model structures in biokinetic process models. Reliability Engineering and System Safety, 203, 107075 (8 pp.). https://doi.org/10.1016/j.ress.2020.107075
How urban storm- and wastewater management prepares for emerging opportunities and threats: digital transformation, ubiquitous sensing, new data sources, and beyond – a horizon scan
Blumensaat, F., Leitão, J. P., Ort, C., Rieckermann, J., Scheidegger, A., Vanrolleghem, P. A., & Villez, K. (2019). How urban storm- and wastewater management prepares for emerging opportunities and threats: digital transformation, ubiquitous sensing, new data sources, and beyond – a horizon scan. Environmental Science and Technology, 53(15), 8488-8498. https://doi.org/10.1021/acs.est.8b06481
N<sub>2</sub>O emission in full-scale wastewater treatment: proposing a refined monitoring strategy
Gruber, W., Villez, K., Kipf, M., Wunderlin, P., Siegrist, H., Vogt, L., & Joss, A. (2019). N2O emission in full-scale wastewater treatment: proposing a refined monitoring strategy. Science of the Total Environment, 699, 134157 (9 pp.). https://doi.org/10.1016/j.scitotenv.2019.134157
Biomass segregation between biofilm and flocs improves the control of nitrite-oxidizing bacteria in mainstream partial nitritation and anammox processes
Laureni, M., Weissbrodt, D. G., Villez, K., Robin, O., de Jonge, N., Rosenthal, A., … Joss, A. (2019). Biomass segregation between biofilm and flocs improves the control of nitrite-oxidizing bacteria in mainstream partial nitritation and anammox processes. Water Research, 154, 104-116. https://doi.org/10.1016/j.watres.2018.12.051
Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities
Mansfeldt, C., Achermann, S., Men, Y., Walser, J. C., Villez, K., Joss, A., … Fenner, K. (2019). Microbial residence time is a controlling parameter of the taxonomic composition and functional profile of microbial communities. ISME Journal, 13(6), 1589-1601. https://doi.org/10.1038/s41396-019-0371-6
Characterizing long-term wear and tear of ion-selective pH sensors
Ohmura, K., Thürlimann, C. M., Kipf, M., Carbajal, J. P., & Villez, K. (2019). Characterizing long-term wear and tear of ion-selective pH sensors. Water Science and Technology, 80(3), 541-550. https://doi.org/10.2166/wst.2019.301
The future of WRRF modelling – outlook and challenges
Regmi, P., Stewart, H., Amerlinck, Y., Arnell, M., García, P. J., Johnson, B., … Rosso, D. (2019). The future of WRRF modelling – outlook and challenges. Water Science and Technology, 79(1), 3-14. https://doi.org/10.2166/wst.2018.498
Automated model selection in principal component analysis: a new approach based on the cross-validated ignorance score
Russo, S., Li, G., & Villez, K. (2019). Automated model selection in principal component analysis: a new approach based on the cross-validated ignorance score. Industrial and Engineering Chemistry Research, 58(30), 13448-13468. https://doi.org/10.1021/acs.iecr.9b00642
Beyond signal quality: the value of unmaintained pH, dissolved oxygen, and oxidation-reduction potential sensors for remote performance monitoring of on-site sequencing batch reactors
Schneider, M. Y., Carbajal, J. P., Furrer, V., Sterkele, B., Maurer, M., & Villez, K. (2019). Beyond signal quality: the value of unmaintained pH, dissolved oxygen, and oxidation-reduction potential sensors for remote performance monitoring of on-site sequencing batch reactors. Water Research, 161, 639-651. https://doi.org/10.1016/j.watres.2019.06.007
Soft-sensing, automation, and diagnosis for nitrification
Thürlimann, C. M. (2019). Soft-sensing, automation, and diagnosis for nitrification [Doctoral dissertation, ETH Zurich]. https://doi.org/10.3929/ethz-b-000347049
Stabilizing control of a urine nitrification process in the presence of sensor drift
Thürlimann, C. M., Udert, K. M., Morgenroth, E., & Villez, K. (2019). Stabilizing control of a urine nitrification process in the presence of sensor drift. Water Research, 165, 114958 (10 pp.). https://doi.org/10.1016/j.watres.2019.114958
Incremental parameter estimation under rank-deficient measurement conditions
Villez, K., Billeter, J., & Bonvin, D. (2019). Incremental parameter estimation under rank-deficient measurement conditions. Processes, 7(2), 75 (33 pp.). https://doi.org/10.3390/pr7020075
Transforming data into knowledge for improved wastewater treatment operation: a critical review of techniques
Corominas, L., Garrido-Baserba, M., Villez, K., Olsson, G., Cortés, U., & Poch, M. (2018). Transforming data into knowledge for improved wastewater treatment operation: a critical review of techniques. Environmental Modelling and Software, 106, 89-103. https://doi.org/10.1016/j.envsoft.2017.11.023