| A systematic review of machine learning classification methodologies for modelling passenger mode choice T Hillel, M Bierlaire, M Elshafie, Y Jin Journal of Choice Modelling 38, 100221, 2021 | 198* | 2021 |
| Recreating passenger mode choice-sets for transport simulation: A case study of London, UK T Hillel, MZ Elshafie, Y Jin Proceedings of the Institution of Civil Engineers - Smart Infrastructure and …, 2018 | 93 | 2018 |
| A prediction and behavioural analysis of machine learning methods for modelling travel mode choice JÁ Martín-Baos, JA López-Gómez, L Rodriguez-Benitez, T Hillel, ... Transportation Research Part C: Emerging Technologies 156, 104318, 2023 | 49 | 2023 |
| Capturing trade-offs between daily scheduling choices J Pougala, T Hillel, M Bierlaire Journal of Choice Modelling 43, 100354, 2022 | 45 | 2022 |
| Assisted specification of discrete choice models N Ortelli, T Hillel, FC Pereira, M de Lapparent, M Bierlaire Journal of choice modelling 39, 100285, 2021 | 44 | 2021 |
| DATGAN: Integrating expert knowledge into deep learning for synthetic tabular data G Lederrey, T Hillel, M Bierlaire arXiv preprint arXiv:2203.03489, 2022 | 33 | 2022 |
| OASIS: optimisation-based activity scheduling with integrated simultaneous choice dimensions J Pougala, T Hillel, M Bierlaire Transportation Research Part C: Emerging Technologies 155, 104291, 2023 | 32 | 2023 |
| Weak teachers: Assisted specification of discrete choice models using ensemble learning T Hillel, M Bierlaire, M Elshafie, Y Jin hEART 2019, 8th Symposium of the European Association for Research in …, 2019 | 29 | 2019 |
| Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms G Lederrey, V Lurkin, T Hillel, M Bierlaire Journal of Choice Modelling 38, 100226, 2021 | 27 | 2021 |
| Understanding travel mode choice: A new approach for city scale simulation T Hillel University of Cambridge, 2019 | 24 | 2019 |
| Empowering revealed preference survey with a supplementary stated preference survey: demonstration of willingness-to-pay estimation within a mode choice case M Tabasi, A Raei, T Hillel, R Krueger, TH Rashidi Travel Behaviour and Society 33, 100632, 2023 | 20 | 2023 |
| Simulating intra-household interactions for in- and out-of-home activity scheduling N Rezvany, M Bierlaire, T Hillel Transportation Research Part C: Emerging Technologies 157, 2023 | 16 | 2023 |
| New perspectives on the performance of machine learning classifiers for mode choice prediction T Hillel Tech. Rep., 2020 | 14* | 2020 |
| Choice set generation for activity-based models J Pougala, T Hillel, M Bierlaire 21st Swiss Transport Research Conference (STRC 2021), Ascona, Switzerland, 2021 | 12 | 2021 |
| RUMBoost: Gradient boosted random utility models N Salvadé, T Hillel Transportation Research Part C: Emerging Technologies 170, 104897, 2025 | 11 | 2025 |
| Estimating flexibility preferences to resolve temporal scheduling conflicts in activity-based modelling P Manser, T Haering, T Hillel, J Pougala, R Krueger, M Bierlaire Transportation 51 (2), 501-528, 2024 | 11* | 2024 |
| Integrated models of transport and energy demand: A literature review and framework N Rezvany, T Hillel, M Bierlaire Swiss Transport Research Conference, 2021 | 6 | 2021 |
| Joint modelling of electric vehicle charging and daily activity scheduling S Wang, J Pougala, T Hillel Transportation Research Part D: Transport and Environment 147, 104911, 2025 | 5 | 2025 |
| Modelling mobility tool availability at a household and individual level: A case study of Switzerland T Hillel, J Pougala, P Manser, R Luethi, W Scherr, M Bierlaire European Association for Research in Transportation, 2021 | 5 | 2021 |
| Scheduling of daily activities: an optimization approach J Pougala, T Hillel, M Bierlaire Swiss Transportation Research Conference. Ascona, Switzerland, 2020 | 5 | 2020 |
Michel BierlaireEcole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
