My research focuses on the intersection of applied machine learning and strategic innovation management, with a commitment to addressing complex business challenges and fostering competitive advantage. In the domain of applied machine learning, I specialize in forecasting, non-intrusive load monitoring, and time-series analysis, with applications in predictive maintenance and power grid optimization. Within strategic innovation management, my interests lie in developing innovative business models, crafting strategic roadmaps, and advancing effective innovation management practices to drive organizational success in dynamic markets.
Journal articles
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Anthony Faustine, and Pereira, Lucas, “FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting With Uncertainty Estimates,” IEEE Transactions on Smart Grid 2024, doi:
10.1109/TSG.2022.3148699Quantile regression / Low voltage substation -
Anthony Faustine,Nunes, Nuno Jardim , and Pereira, Lucas, “Efficiency Through Simplicity: MLP-Based Approach for Net-Load Forecasting With Uncertainty Estimates in Low-Voltage Distribution Networks,” IEEE Transactions on Power Systems 2024, doi:
10.1109/TPWRS.2024.3400123Quantile regression / Low voltage substation -
Hafsa Bousbiat,Anthony Faustine, Christoph Klemenjak, and Lucas Pereira “Unlocking the Full Potential of Neural NILM: On Automation, Hyperparameters, and Modular Pipelines,” IEEE Transactions on Industrial Informatics vol. 19, no. 5, pp. 7002-7010 May 2023, doi:
10.1109/TII.2022.3206322.sustainable energy / buildings -
Anthony Faustine and Pereira, Lucas, “Improved Appliance Classification in Non-Intrusive Load Monitoring Using Weighted Recurrence Graph and Convolutional Neural Networks,” Energies 2020, 13, 3374, doi:
10.3390/en13133374sustainable energy / buildings / nilm state prediction -
Benjamin Völker, Andreas Reinhardt, Anthony Faustine and Pereira, Lucas, “Watt’s up at Home? Smart Meter Data Analytics from a Consumer-Centric Perspective,” Energies 2021, 14(3), 719, doi:
10.1109/10.3390/en14030719sustainable energy / buildings / nilm state prediction -
Anthony Faustine, Lucas Pereira and Christoph Klemenjak “Adaptive Weighted Recurrence Graphs for Appliance Recognition in Non-Intrusive Load Monitoring,” IEEE Transactions on Smart Grid vol. 12, no. 1, pp. 398-406, Jan. 2021, doi:
10.1109/TSG.2020.3010621.sustainable energy / buildings / nilm state prediction -
Anthony Faustine, and Pereira, Lucas, “Multi-Label Learning for Appliance Recognition in NILM Using Fryze-Current Decomposition and Convolutional Neural Network,” Energies 2020, 13, 4154., doi:
10.1109/TSG.2022.3148699sustainable energy / buildings / nilm state prediction
Conference papers
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Anthony Faustine and Pereira, Lucas, “Enhancing LV system resilience through probabilistic forecasting of interdependent variables: voltage, reactive and active power,” CIRED Chicago Workshop 2024: Resilience of Electric Distribution Systems, Chicago, USA, 2025, pp. 27-31, doi:
10.1049/icp.2024.2555 -
Anthony Faustine and Pereira, Lucas, “Scalable and Efficient MLP-based Fully Parameterised Quantile for Probabilistic Power Forecasting,” 44th International Symposium on Forecasting, Dijon, France 2024
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Anthony Faustine and Pereira, Lucas, “Applying Symmetrical Component Transform for Industrial Appliance Classification in Non-Intrusive Load Monitoring,” ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece 2023, pp. 1-5, doi:
10.1109/ICASSP49357.2023.10096324 -
Anthony Faustine and Pereira, Lucas, “Conformal Multilayer Perceptron-Based Probabilistic Net-Load Forecasting for Low-Voltage Distribution Systems with Photovoltaic Generation,” 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Oslo, Norway 2024, pp. 59-64, doi:
10.1109/SmartGridComm60555.2024.10738106