Tim Hillel
This page reports only the academic work registered in the databases of the Transport and Mobility Laboratory, and is not necessarily a comprehensive list of the work by Tim Hillel.
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- Papers in international journals (7)
- Papers in conference proceedings (18)
- Technical reports (11)
- Seminar (9)
- Reviewing (14)
- Research projects (4)
- Regular teaching (5)
- Miscellaneous lectures (7)
- Project supervision (10)
International journals
Published
Total: 7
- Rezvany, N., Bierlaire, M., and Hillel, T. (2023). Simulating intra-household interactions for in- and out-of-home activity scheduling, Transportation Research Part C: Emerging Technologies 157(104362):. doi:10.1016/j.trc.2023.104362
- Pougala, J., Hillel, T., and Bierlaire, M. (2023). OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions, Transportation Research Part C: Emerging Technologies 155:. doi:10.1016/j.trc.2023.104291
- Manser, P., Haering, T., Hillel, T., Pougala, J., Krueger, R., and Bierlaire, M. (2022). Estimating flexibility preferences to resolve temporal scheduling conflicts in activity-based modelling, Transportation (accepted for publication on August 22, 2022) doi:10.1007/s11116-022-10330-8
- Pougala, J., Hillel, T., and Bierlaire, M. (2022). Capturing trade-offs between daily scheduling choices, Journal of Choice Modelling 43(100354):. doi:10.1016/j.jocm.2022.100354
- Ortelli, N., Hillel, T., Pereira, F. C., de Lapparent, M., and Bierlaire, M. (2021). Assisted Specification of Discrete Choice Models, Journal of Choice Modelling 39(100285):. doi:10.1016/j.jocm.2021.100285
- Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2021). Estimation of Discrete Choice Models with Hybrid Stochastic Adaptive Batch Size Algorithms, Journal of Choice Modelling 38(100226):. doi:10.1016/j.jocm.2020.100226
- Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y. (2021). A systematic review of machine learning classification methodologies for modelling passenger mode choice, Journal of Choice Modelling 38(100221):. doi:10.1016/j.jocm.2020.100221
Papers in conference proceedings
- Rezvany, N., Hillel, T., and Bierlaire, M. (2023). From domestic energy demand to household activity patterns. Proceedings of the 23rd Swiss Transport Research Conference (STRC) 10-12 May, 2023.
- Pougala, J., Hillel, T., and Bierlaire, M. (2023). From one-day to multiday activity scheduling: extending the OASIS framework. Proceedings of the 23rd Swiss Transport Research Conference (STRC) 10-12 May, 2023.
- Rezvany, N., Hillel, T., and Bierlaire, M. (2022). A utility optimization-based framework for joint in- and out-of-home scheduling. Proceedings of the 10th symposium of the European Association for Research in Transportation (hEART) (hEART) 1-3 June 2022, 2022.
- Pougala, J., Hillel, T., and Bierlaire, M. (2022). Parameter estimation for activity-based models. Proceedings of the 22nd Swiss Transport Research Conference (STRC) 18-20 May, 2022.
- Rezvany, N., Hillel, T., and Bierlaire, M. (2022). Integrated in- and out-of-home scheduling framework: A utility optimization-based approach. Proceedings of the 22nd Swiss Transport Research Conference (STRC ) 18-20 May, 2022.
- Salvadé, N., Hillel, T., Pougala, J., Haering, T., and Bierlaire, M. (2022). Representing location choice within activity-based models. Proceedings of the 22nd Swiss Transport Research Conference (STRC) 18-20 May, 2022.
- Haering, T., Manser, P., Hillel, T., Pougala, J., Krueger, R., and Bierlaire, M. (2021). Resolving time conflicts in activity-based scheduling: A case study of Lausanne. Proceedings of the 21st Swiss Transport Research Conference (STRC) 12-14 September, 2021.
- Pougala, J., Hillel, T., and Bierlaire, M. (2021). Choice set generation for activity-based models. Proceedings of the 21st Swiss Transport Research Conference (STRC) 12-14 September, 2021.
- Rezvany, N., Hillel, T., and Bierlaire, M. (2021). Integrated models of transport and energy demand: A literature review and framework. Proceedings of the 21st Swiss Transport Research Conference (STRC ) 12-14 September, 2021.
- Hillel, T., Pougala, J., Manser, P., Luethi, R., Scherr, W., and Bierlaire, M. (2020). Modelling mobility tool availability at a household and individual level: A case study of Switzerland. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
- Ortelli, N., Hillel, T., Pereira, F. C., de Lapparent, M., and Bierlaire, M. (2020). Variable Neighborhood Search for Assisted Utility Specification in Discrete Choice Models. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
- Pougala, J., Hillel, T., and Bierlaire, M. (2020). An optimization framework for daily activity schedules. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
- Xie, S., Hillel, T., and Jin, Y. (2020). An Early Stopping Bayesian Data Assimilation Approach for improved Mixed Multinomial Logit transferability. Proceedings of the 9th Symposium of the European Association for Research in Transportation (HEART) 3-4 February 2021, 2020.
- Pougala, J., Hillel, T., and Bierlaire, M. (2020). Scheduling of daily activities: an optimization approach. Proceedings of the 20th Swiss Transport Research Conference (STRC) 13-14 May, 2020.
- Hillel, T., Jin, Y., Elshafie, M. Z E B, and Bierlaire, M. (2019). Weak teachers: Assisted specification of discrete choice models using ensemble learning. Proceedings of the 8th Symposium of the European Association for Research in Transportation (HEART) 4-6 September, 2019.
- Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Stochastic optimization with adaptive batch size: Discrete choice models as a case study. Proceedings of the 8th Symposium of the European Association for Research in Transportation (HEART) 4-6 September, 2019.
- Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Stochastic optimization with adaptive batch size: Discrete choice models as a case study. Proceedings of the 19th Swiss Transport Research Conference (STRC) 15-17 May, 2019.
- Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y. (2018). Validation of probabilistic classifiers. Proceedings of the 18th Swiss Transport Research Conference (STRC) 16-18 May, 2018.
Technical reports
- Rezvany, N., Bierlaire, M., and Hillel, T. (2023). Simulating intra-household interactions for in- and out-of-home activity scheduling. Technical report . Transport and Mobility Laboratory, ENAC, EPFL.
- Pougala, J., Hillel, T., and Bierlaire, M. (2022). OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions. Technical report TRANSP-OR 221124. Transport and Mobility Laboratory, ENAC, EPFL.
- Manser, P., Haering, T., Hillel, T., Pougala, J., Krueger, R., and Bierlaire, M. (2021). Resolving temporal scheduling conflicts in activity-based modelling. Technical report TRANSP-OR 211209. Transport and Mobility Laboratory, ENAC, EPFL.
- Bierlaire, M., Frejinger, E., and Hillel, T. (2021). Dynamic choice models. Technical report TRANSP-OR 210305. Transport and Mobility Laboratory, ENAC, EPFL.
- Pougala, J., Hillel, T., and Bierlaire, M. (2021). Capturing trade-offs between daily scheduling choices. Technical report TRANSP-OR 210101. Transport and Mobility Laboratory, ENAC, EPFL.
- Xie, S., Hillel, T., and Jin, Y. (2021). An Early Stopping Bayesian Data Assimilation Approach for Mixed-Logit Estimation. Technical report arXiv:2101.11159. Transport and Mobility Laboratory, ENAC, EPFL.
- Rezvany, N., Hillel, T., and Bierlaire, M. (2021). Integrated models of transport and energy demand: A literature review and framework. Technical report . Transport and Mobility Laboratory, ENAC, EPFL.
- Ortelli, N., Hillel, T., Pereira, F. C., de Lapparent, M., and Bierlaire, M. (2020). Assisted Specification of Discrete Choice Models. Technical report TRANSP-OR 200708. Transport and Mobility Laboratory, ENAC, EPFL.
- Hillel, T. (2020). New perspectives on the performance of machine learning classifiers for mode-choice prediction. Technical report TRANSP-OR 200704. Transport and Mobility Laboratory, ENAC, EPFL.
- Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (2019). Estimation of Discrete Choice Models with Hybrid Stochastic Adaptive Batch Size Algorithms. Technical report TRANSP-OR 191213. Transport and Mobility Laboratory, ENAC, EPFL.
- Hillel, T., Bierlaire, M., and Jin, Y. (2019). A systematic review of machine learning methodologies for modelling passenger mode choice. Technical report TRANSP-OR 191025. Transport and Mobility Laboratory, ENAC, EPFL.
Seminars
- Hillel, T., Pougala, J., Bierlaire, M., Manser, P., Haering, T., and Luethi, R., Modelling mobility tool availability at a household and individual level: A case study of Switzerland. hEART 2020, 9th Symposium of the European Association for Research in Transportation, February 03, 2021, Lyon, France
- Hillel, T., Pougala, J., Bierlaire, M., Scherr, W., and Manser, P., Validating disaggregate models at an aggregate scale: A case study of mobility tool ownership in Switzerland. Applied Urban Modelling 2020: Modelling the New Urban World, January 28, 2021, Cambridge, UK
- Hillel, T., Bierlaire, M., and Jin, Y., Weak teachers: A machine learning approach for assisted specification of Discrete Choice Models. Applied Urban Modelling Workshop, University of Cambridge, September 18, 2019, Cambridge, UK
- Hillel, T., Pougala, J., Bierlaire, M., Manser, P., and Scherr, W., Activity-based Travel Demand Forecasting: Extensions to the SBB Nationwide Model. nextRail19, International Rail and Mobility Conference, Swiss Federal Institute of Technology - ETH Zurich, September 13, 2019, Zurich, Switzerland
- Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., Weak teachers: Assisted specification of discrete choice models using ensemble learning. hEART 2019, 8th Symposium of the European Association for Research in Transportation, Budapest University of Technology and Economics, September 04, 2019, Budapest, Hungary
- Hillel, T., Weak teachers: assisted specification of discrete choice models using ensemble learning algorithms. Workshop on Discrete Choice Models 2019, EPFL, April 26, 2019, Lausanne, Switzerland
- Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., A new framework for assessing classification algorithms for mode choice prediction. hEART 2018, 7th Symposium of the European Association for Research in Transportation, National Technical University of Athens, September 05, 2018, Athens, Greece
- Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Jin, Y., Validation of probabilistic classifiers. 18th Swiss Transport Research Conference (STRC), May 18, 2018, Monte Verità, Ascona, Switzerland
- Hillel, T., Elshafie, M. Z E B, and Jin, Y., A comparison of classification methods for modelling urban mode choice. Workshop on Discrete Choice Models 2017, EPFL, June 22, 2017, Lausanne, Switzerland
Reviewing
Total: 14 reviews for 7 journals (since 2004). Per year: 2021: 2, 2020: 10, 2019: 2.
Research projects
- Intelligent digital twins for assessing and predicting bridge road traffic demands
- Sponsor: School of Architecture, Civil and Environmental Engineering (ENAC), École polytechnique fédérale de Lausanne
- Team: Tim Hillel (PI&PM)
- Period: October 01, 2020-April 01, 2022
- Road bridges are a vital part of transportation networks, forming crucial links in natural bottleneck locations and enabling the continual flow of people and goods into, out of, and across cities. However, the analysis used for design and maintenance planning of this community-critical infrastructure is typically carried out using static models and assuming generalized traffic patterns. This analysis represents only peak loading scenarios and does not reflect the spatial and temporal variations in real-world traffic loads. The resulting uncertainty in load prediction can lead to in overengineering in bridge design as well as sub-optimal maintenance planning. Furthermore, as current analysis techniques model only maximal loads, they cannot be used to predict the maintenance condition of bridges due to fatigue from repeated loading and unloading of the bridge over time. This research aims to address these limitations by developing intelligent digital twins which can simulate the response of a bridge to realistic traffic loading scenarios. These digital twin models combine two primary elements: (i) a traffic simulation model which exploits detailed traffic count and weigh-in-motion data to generate time-dependent traffic loadings, and (ii) a detailed structural model which predicts the compliance and maintenance condition of a bridge for different maximal and cyclic loading patterns. The intelligent digital twin is intended to be generalizable to any bridge or network of bridges for which relevant data exists. This will enable these models to be used within an integrated approach to study infrastructure vulnerability and multi-hazard risk management.
- Optimization of individual mobility plans to simulate future travel in Switzerland
- Sponsor: Innosuisse (Swiss Innovation Agency)
- Team: Michel Bierlaire (PI), Tim Hillel (PM), Janody Pougala, Rico Krueger
- Period: September 01, 2020-March 01, 2022
- This project, joint with Swiss Federal Railways (SBB) will develop a new activity-based modelling approach based on optimization of individual daily mobility plans. This approach will be implemented within SBB's existing nationwide model for Switzerland for investment and service planning decisions for future transportation.
- OrgVisionPro: Automated organizational design and optimization
- Sponsor: Innosuisse (Swiss Innovation Agency)
- Team: Michel Bierlaire (PI), Rico Krueger (PM), Tim Hillel (PM), Melvin Wong, Nour Dougui
- Period: October 01, 2019-June 30, 2021
- This project, joint with CLEAP S.A., is will develop advanced analytics algorithms to propose organization design (OD) scenarios based on the existing situation, constraints, and future needs of a business. These scenarios will support organizations in shaping their future by optimizing their structure and operating models.
- Activity based travel demand forecasting
- Sponsor: Swiss Federal Railways (SBB)
- Team: Michel Bierlaire (PI), Tim Hillel (PM), Janody Pougala
- Period: March 01, 2019-March 01, 2020
- This research project aims to update and improve the microscopic activity-based demand model developed and maintained by SBB. Specifically the research intends to address the following questions: 1. Ownership of mobility instruments: Which metrics and specifications can be added to the current model, in order to improve its ability to forecast mid-and long-term ownership of mobility instruments? More specifically, how can the notion of accessibility be integrated to the current model to capture more complex mode interactions? 2. Mode choice model: Can a tour-based approach be used to model mode choice? In addition, how can the processes to estimate destination and mode choice (currently nested) be combined to generate results that are consistent with observed mobility behaviors at different time horizons (short, mid, and long-term)? 3. Tour and activity generation: How can the generation of tours and activity patterns be combined to allow modelling of joint decisions?
Regular teaching
- Decision-aid methodologies in transportation
- Year: Spring 2022
- Section(s): Civil Engineering
- Lecturers: Tim Hillel, Nour Dougui
- Teaching assistant: Selin Atac, Janody Pougala, Marija Kukic, Negar Rezvany
- Decision-aid methodologies in transportation
- Year: Spring 2021
- Section(s): Civil Engineering
- Lecturers: Tim Hillel, Nour Dougui
- Teaching assistant: Selin Atac, Janody Pougala, Marija Kukic, Negar Rezvany
- Webpage: https://transp-or.epfl.ch/courses/decisionAid2020/index.php
- Decision-aid methodologies in transportation
- Year: Spring 2020
- Section(s): Civil Engineering
- Lecturers: Tim Hillel, Nour Dougui
- Teaching assistant: Stefano Bortolomiol, Gael Lederrey, Selin Atac, Janody Pougala
- Webpage: https://transp-or.epfl.ch/courses/decisionAid2020/index.php
- Mathematical modeling of behavior
- Year: Fall 2019
- Section(s): Mathematics, Master in Financial Engineering
- Lecturer: Michel Bierlaire
- Teaching assistant: Tim Hillel, Meritxell Pacheco, Janody Pougala, Nicola Ortelli
- Webpage: https://moodle.epfl.ch/course/view.php?id=1001
- Decision-aid methodologies in transportation
- Year: Spring 2019
- Section(s): Civil Engineering
- Lecturers: Nikola Obrenovic, Tim Hillel
- Teaching assistant: Stefano Bortolomiol, Gael Lederrey, Selin Atac
- Webpage: http://transp-or.epfl.ch/courses/decisionAid2019/index.php
Miscellaneous lectures
- Bayesian Estimation; Individual Prediction
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, February 11, 2021
- School: EPFL
- Lecturer: Rico Krueger
- Assistant: Tim Hillel
- Introduction; Logit Estimation and Testing
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, February 08, 2021
- School: EPFL
- Lecturer: Tim Hillel
- Assistant: Cloe Cortes Balcells
- Hybrid Choice Models
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 28, 2019
- School: EPFL
- Lecturer: Yuki Oyama
- Assistant: Tim Hillel
- Bayesian Estimation; Individual Prediction
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 27, 2019
- School: EPFL
- Lecturer: Rico Krueger
- Assistants: Tim Hillel, Selin Atac, Meritxell Pacheco
- Logit Mixtures; Combining RP and SP data
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 26, 2019
- School: EPFL
- Lecturer: Meritxell Pacheco
- Assistants: Tim Hillel, Rico Krueger
- Nested Logit; Aggregate Forecasting
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 25, 2019
- School: EPFL
- Lecturer: Selin Atac
- Assistants: Meritxell Pacheco, Yuki Oyama, Tim Hillel
- Introduction; Logit Estimation; Specification Testing
- Program: Discrete Choice Analysis: Predicting Individual Behavior and Market Demand, March 24, 2019
- School: EPFL
- Lecturer: Tim Hillel
- Assistants: Meritxell Pacheco, Yuki Oyama, Selin Atac
Project supervision
Masters theses
- Nicolas Salvadé
- Section: Civil Engineering
- Representing destination choice sets within activity-based models
- Supervision:Janody Pougala, Tom Haering, Tim Hillel
- Expert: Patrick Manser
- 21/09/2021-17/01/2022
- Isabelle Pumford
- Section: Computer science
- Simulating realistic traffic flows to predict bridge loadings
- Supervision:Tim Hillel, Michel Bierlaire
- Expert: Dimitrios Papastergiou, ASTRA
- 14/09/2020-15/01/2021
- Sergej Gasparovich
- Section: Civil Engineering
- Generating daily activity schedules using machine learning
- Supervision:Janody Pougala, Tim Hillel, Michel Bierlaire
- Expert: Antonin Danalet
- 17/02/2020-19/06/2020
- Jessica Hopkins
- Section: Mathematics
- Evaluation of Bootstrap methods
- Supervision:Tim Hillel, Gael Lederrey, Michel Bierlaire
- Expert: Damon Wischik
- 18/02/2019-21/06/2019
Semester projects
- Generating choice sets of destinations for activity based applications, Nicolas Salvadé (SGC), January 29, 2021
- Generating choice sets of transport modes for activity based applications, Benoit Pahud (SGC), January 29, 2021
- Tour-based mode choice modelling, Adrien Nicolet (SGC), January 31, 2020
- Investigating daily activity patterns, Sergey Gasparovich (SGC), January 31, 2020
- Demand forecasting for a novel transportation mode, Denis Steffen (SMA), June 30, 2019
- Automatic utility specification using machine learning techniques, Nicola Ortelli, June 08, 2018