Selected IALab papers

2023

[1] Xingshuai Huang, Di Wu, Benoit Boulet, “MetaProbformer for Charging Load Probabilistic Forecasting of Electric Vehicle Charging Stations”, accepted by IEEE Transactions on Intelligent Transportation Systems.

[2] Seal, S., Boulet, B., Dehkordi, V. R., Bouffard, F., & Joos, G. (2023). Centralized MPC for Home Energy Management with EV as Mobile Energy Storage Unit. accepted by IEEE Transactions on Sustainable Energy.

[3] Song, W., Wu, D., Shen, W., & Boulet, B. (2023). A Remaining Useful Life Prediction Method for Lithium-ion Battery Based on Temporal Transformer Network. Procedia Computer Science217, 1830-1838.

[4] Xijuan Sun, Di Wu, and Benoit Boulet. “Anomaly Detection with Ensemble of Encoder and Decoder.” arXiv preprint arXiv:2303.06431 (2023).

[5] Huiliang Zhang, Di Wu, and Benoit Boulet. “Adaptive Aggregation for Safety-Critical Control.” arXiv preprint arXiv:2302.03586 (2023).

2022

[1] Beaudoin, M.A. and Boulet, B. “Structured learning of safety guarantees for the control of uncertain dynamical systems.” IEEE Transactions on Intelligent Vehicles. 2022 Feb 4.

[2] Beaudoin, M.A. and Boulet, B. “Improving gearshift controllers for electric vehicles with reinforcement learning.” Mechanism and Machine Theory 169 (2022): 104654.

[3] H. Zhang, S. Seal, D. Wu, F. Bouffard and B. Boulet. ” Data-driven Model Predictive and Reinforcement Learning-Based Control for Building Energy Management: a Survey .” IEEE Access(2022).

[4] Song, Wenbin, Di Wu, Weiming Shen, and Benoit Boulet. “An Early Fault Detection Method of Rotating Machines Based on Multiple Feature Fusion with Stacking Architecture.” arXiv preprint arXiv:2205.00511 (2022).

[5] Y. Fu, D. Wu, and B. Boulet. “Reinforcement Learning based Dynamic Model Combination for Time Series Forecasting .” In AAAI. 2022.

[6] Zabetian-Hosseini, Asal, Geza Joos, and Benoit Boulet. “Centralized Control Design for Bidirectional DC Charging Stations to Enable V2G.” 2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D). IEEE, 2022.

[7] Y. Fu, D. Wu and B. Boulet. “On the Benefits of Transfer Learning and Reinforcement Learning for Short-term Load Forecasting.” In GreenCom. 2022.

[8] Y. Fu, D. Wu and B. Boulet. “A Closer Look at Offline RL Agents.” In NeurIPS, 2022.

[9] W. B. Song, D. Wu, W. M. Shen, B. Boulet, ” Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection”, https://arxiv.org/abs/2204.12637.

[10] W. B. Song, D. Wu, W.M. Shen, B. Boulet, “A Remaining Useful Life Prediction Method for Lithium-ion Battery Based on Temporal Transformer Network”, in ISM 2022.

[11] Di Wu, W. X. Lin, “Efficient Residential Electric Load Forecasting via Transfer Learning and Graph Neural Networks”, accepted by IEEE Transactions on Smart Grid.

[12] J. E. Zhang, D. Wu and B. Boulet, “Time Series Anomaly Detection via Reinforcement Learning-Based Model Selection”, in CCECE 2022.

[13] Xijuan Sun, Di Wu, Menghan Jia, Yuxuan Xiao, and Benoit Boulet “Forecasting of Solar Energy Generation via Dynamic Model Ensemble,” 2022 IEEE Electrical Power and Energy Conference (EPEC 2022)

[14] Xijuan Sun, Di Wu, Arnaud Zinflou, and Benoit Boulet “Power System Anomaly Detection via Ensemble of Encoder and Decoder Networks,” 2022 IEEE Electrical Power and Energy Conference (EPEC 2022)


2021

[1] Beaudoin, M.A. and Boulet, B., 2021. Fundamental limitations to no-jerk gearshifts of multi-speed transmission architectures in electric vehicles. Mechanism and Machine Theory, 160, p.104290. doi:10.1016/ j.mechmachtheory.2021.104290

[2] D. Wu, C. Cui, and B. Boulet, ” Zero-shot Knowledge Transfer for Residential Short-Term Load Forecasting. ” In 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 workshop on Artificial Intelligence for Energy and Sustainability

[3] D. Wu, C. Cui, and B. Boulet, ” Electric Load Forecasting with Boosting based Sample Instance Transfer.” accepted by International Conference on Machine Learning (ICML) 2021, Time Series Workshop

[4] D. Wu, F. Zhou, B. Wang, C. Wong, C. Shui, Y. Zhou, Q. Lao, and F. Wan, “On the Benefits of Two Dimensional Metric Learning.” IEEE Transactions on Knowledge and Data Engineering

[5] J. E. Zhang, D. Wu and B. Boulet, “Time Series Anomaly Detection for Smart Grids: A Survey,” 2021 IEEE Electrical Power and Energy Conference (EPEC), Toronto, ON, 2021, pp. 1-5

[6] Q. Dang, D. Wu and B. Boulet, “Virtual Battery Resource for Community Microgrid Energy Storage Planning Le parc de véhicules électriques comme ressource de batterie virtuelle pour la planification du stockage d’énergie des micro-réseaux communautaires,” in IEEE Canadian Journal of Electrical and Computer Engineering, doi: 10.1109/ICJECE.2021.3093520.

[7] Q. Dang, D. Wu and B. Boulet, “EV Fleet Batteries as Distributed Energy Resources Considering Dynamic Electricity Pricing.” 2021 IEEE 12th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). IEEE, 2021.

[8] Q. Dang, D. Wu and B. Boulet, “Electric Vehicle Battery as Energy Storage Unit Consider Renewable Power Uncertainty,” 2021 IEEE Energy Conversion Congress and Exposition (ECCE), Vancouver, Canada, 10-14 Oct 2021, pp. 1-6.

[9] Toukhtarian, Raffi, Mostafa Darabi, Savvas Hatzikiriakos, Haile Atsbha, and Benoit Boulet. “Parameter identification of transport PDE/nonlinear ODE cascade model for polymer extrusion with varying die gap.” The Canadian Journal of Chemical Engineering 99, no. 5 (2021): 1158-1176.

[10] W. Lin and D. Wu, “Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks.” In 30th International Joint Conference on Artificial Intelligence, IJCAI 2021, pp. 1-7

[11] W. Lin and D. Wu, “Residential Customer Characteristics Identification via Deep Ensemble Learning.” In 30th International Joint Conference on Artificial Intelligence, IJCAI 2021 workshop on Artificial Intelligence for Energy and Sustainability

[12] W. Lin, D. Wu and B. Boulet, “Spatial-Temporal Residential Short-term Load Forecasting via Graph Neural Networks,” in IEEE Transactions on Smart Grid, doi: 10.1109/TSG.2021.3093515.

[13] X. Huang, D. Wu and B. Boulet, “ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control.” accepted by International Conference on Machine Learning (ICML) 2021, Reinforcement Learning for Real Life Workshop

[14] Y. Fu, D. Wu, and B. Boulet. “Benchmarking Sample Selection Strategies for Batch Reinforcement Learning.” In Offline Reinforcement Learning Workshop at NeurIPS. 2021.

[15] Zabetian-Hosseini, A., Joos, G. and Boulet, B., 2021, October. Distributed Control Design for V2G in DC Fast Charging Stations. In 2021 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 655-661). IEEE.


2020

[1] A. E. Fathi, R. E. Kearney, E. Palisaitis, B. Boulet and A. Haidar, “A Model-Based Insulin Dose Optimization Algorithm for People With Type 1 Diabetes on Multiple Daily Injections Therapy,” in IEEE Transactions on Biomedical Engineering, vol. 68, no. 4, pp. 1208-1219, April 2021, doi: 10.1109/TBME.2020.3023555.

[2] Darabi, M., Toukhtarian, R., Alizadeh, H. V., & Boulet, B. (2020). Closed-loop thickness control and sensor placement in extrusion blow molding. International Journal of Automation and Control.

[3] H. Zhang, D. Wu and B. Boulet, “A Review on Recent Advances of Reinforcement Learning for Smart Home Energy Management,” 2020 IEEE Electrical Power and Energy Conference (EPEC), Edmonton, AB, 2020, pp. 1-5

[4] Q. Dang, D. Wu and B. Boulet, “Community Microgrid Energy Storage Sizing Considering EV Fleet Batteries as Supplemental Resource,” 2020 IEEE Electrical Power and Energy Conference (EPEC), Edmonton, AB, 2020, pp. 1-5

[5] Q. Dang, D. Wu and B. Boulet, (2020, June). EV Charging Management with ANN-Based Electricity Price Forecasting. In 2020 IEEE Transportation Electrification Conference & Expo (ITEC) (pp. 626-630). IEEE.

[6] Seal, S., Boulet, B. and Dehkordi, V.R., 2020. Centralized model predictive control strategy for thermal comfort and residential energy management. Energy, 212, p.118456.

[7] T. Cui, D. Wu and B. Boulet, “Residential Short-term Load Forecasting via Boosting based Instance Transfer,” in IEEE Transactions on Smart Grid (Under review)

[8] Toukhtarian, R., Darabi, M., Hatzikiriakos, S., Atsbha, H. and Boulet, B., 2020. Parameter identification of transport PDE/nonlinear ODE cascade model for polymer extrusion with varying die gap. The Canadian Journal of Chemical Engineering.

[9] X. Huang, D. Wu and B. Boulet, “Ensemble Learning for Charging Load Forecasting of Electric Vehicle Charging Stations,” 2020 IEEE Electrical Power and Energy Conference (EPEC), Edmonton, AB, 2020, pp. 1-5

[10] Y. Fu, D. Wu, and B. Boulet. “Batch Reinforcement Learning in the Real World: A Survey.” In Offline Reinforcement Learning Workshop at NeurIPS. 2020.


2019

[1] Azarnoush, Hamed, et al. “Intravascular optical coherence tomography to validate finite-element simulation of angioplasty balloon inflation.” Physics in medicine and biology (2019).

[2] D Wu, TC Cui, D Precup, B Boulet. Data-Driven Chance Constraint Programming based Electric Vehicle Penetration Analysis. International Conference on Machine Learning (ICML) 2019 workshop on AI for Climate Change

[3] Wu, Di, Boyu Wang, Doina Precup, and Benoit Boulet. “Multiple kernel learning-based transfer regression for electric load forecasting.” IEEE Transactions on Smart Grid 11, no. 2 (2019): 1183-1192.

[4] El Fathi, Anas, et al. “An unannounced meal detection module for artificial pancreas control systems.” 2019 American Control Conference (ACC). IEEE, 2019.

[5] Q Dang, D Wu and B Boulet, “A Q-Learning Based Charging Scheduling Scheme for Electric Vehicles,” 2019 IEEE Transportation Electrification Conference and Expo (ITEC), Novi, MI, 2019, pp. 1-5.

[6] Q Dang, D Wu and B Boulet, “An Advanced Framework for Electric Vehicles Interaction with Distribution Grids Based on Q-Learning,”2019 IEEE Energy Conversion Congress and Exposition (ECCE), Baltimore, MD, 2019, pp. 1-5.


2018

[1] Toukhtarian, Raffi, et al. “Modeling polymer extrusion with varying die gap using Arbitrary Lagrangian Eulerian (ALE) method.” Physics of Fluids 30.9 (2018): 093103.

[2] Lotfalian, Reza, et al. “Acquisition Cost-Torque Capacity-Reliability Modeling for Spur Gears.” Journal of Mechanical Design 140.6 (2018): 064501.

[3] El Fathi, Anas, et al. “The artificial pancreas and meal control: An overview of postprandial glucose regulation in type 1 diabetes.” IEEE Control Systems Magazine 38.1 (2018): 67-85.

[4] Alizadeh, Hossein Vahid, Mohamed K. Helwa, and Benoit Boulet. “Modeling, analysis and constrained control of wet cone clutch systems: A synchromesh case study.” Mechatronics 49 (2018): 92-104.

[5] Maghoul, Pooya, et al. “Computer Simulation Model to Train Medical Personnel on Glucose Clamp Procedures.” Canadian journal of diabetes 41.5 (2017): 485-490.

[6] El Fathi, Anas, et al. “The artificial pancreas and meal control: An overview of postprandial glucose regulation in type 1 diabetes.” IEEE Control Systems Magazine 38.1 (2018): 67-85.

[7] D Wu, Rabusseau, G, François-lavet, V., D Precup, & B Boulet. Optimizing Home Energy Management and Electric Vehicle Charging with Reinforcement Learning. International Conference on Machine Learning (ICML) 2018 workshop on Adaptive Learning Agents.


2017

[1] Maghoul, Pooya, et al. “Computer Simulation Model to Train Medical Personnel on Glucose Clamp Procedures.” Canadian journal of diabetes 41.5 (2017): 485-490.

[2] D Wu, B Wang, D Precup, B Boulet. “Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting.” Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, Cham, 2017.

[3] Mousavi, Mir Saman Rahimi, Hossein Vahid Alizadeh, and Benoit Boulet. “Estimation of synchromesh frictional torque and output torque in a clutchless automated manual transmission of a parallel hybrid electric vehicle.” IEEE Transactions on Vehicular Technology 66.7 (2017): 5531-5539.

[4] D Wu, H Zeng, C Lu, B Boulet. “Two-stage energy management for office buildings with workplace EV charging and renewable energy.” IEEE Transactions on Transportation Electrification 3.1 (2017): 225-237.