Research

TRANSP-OR: Tim Hillel

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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Tim Hillel

International journals

Accepted

Total: 2

  • Lederrey, G., Lurkin, V., Hillel, T., and Bierlaire, M. (to appear). Estimation of Discrete Choice Models with Hybrid Stochastic Adaptive Batch Size Algorithms, Journal of Choice Modelling (accepted for publication on May 20, 2020)
  • Hillel, T., Bierlaire, M., Elshafie, M. Z E B, and Ying, J. (to appear). A systematic review of machine learning classification methodologies for modelling passenger mode choice, Journal of Choice Modelling (accepted for publication on May 10, 2020)

      Papers in conference proceedings

      • 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., Ying, J., 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 Ying, J. (2018). Validation of probabilistic classifiers. Proceedings of the 18th Swiss Transport Research Conference (STRC) 16-18 May, 2018.

      Technical reports

      Seminars

      • Hillel, T., Bierlaire, M., and Ying, J., 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 Ying, J., 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 Ying, J., 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 Ying, J., 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 Ying, J., A comparison of classification methods for modelling urban mode choice. Workshop on Discrete Choice Models 2017, EPFL, June 22, 2017, Lausanne, Switzerland

      Reviewing

    • Transportation Research Part C: Emerging Technologies (3)
    • Applied Soft Computing (1)
    • International Journal of Theoretical and Applied Papers on Economic Modelling (1)
    • Journal of Choice Modelling (1)
    • Journal of Transportation Engineering, Part A (1)
    • Transport Reviews (1)
    • Transportation Research Part B: Methodological (1)
    • Total: 9 reviews for 7 journals (since 2004). Per year: 2020: 7, 2019: 2.

      Research projects

      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), Tim Hillel (PM), Melvin Wong, Rico Krueger, Nour Dougui
      Period: October 01, 2019-April 01, 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

      Mathematical modeling of behavior
      Year: Fall 2020
      Section(s): Mathematics, Master in Financial Engineering
      Lecturers: Michel Bierlaire, Meritxell Pacheco, Tim Hillel
      Teaching assistant: Melvin Wong, Rico Krueger, Janody Pougala, Nicola Ortelli
      Webpage: https://moodle.epfl.ch/course/view.php?id=1001
      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

      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

      Isabelle Pumford
      Section:
      Simulating realistic traffic flows to predict bridge loadings
      Supervision:Tim Hillel, Michel Bierlaire
      Expert: TBC
      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 transport modes for activity based applications, Benoit Pahud (GC), January 29, 2021
      • Generating choice sets of destinations for activity based applications, Nicolas Salvadé (GC), January 29, 2021
      • Investigating daily activity patterns, Sergey Gasparovich (GC), January 31, 2020
      • Tour-based mode choice modelling, Adrien Nicolet (SGC), January 31, 2020
      • Demand forecasting for a novel transportation mode, Denis Steffen (MATH), June 30, 2019
      • Automatic utility specification using machine learning techniques, Nicola Ortelli, June 08, 2018