Research

TRANSP-OR: Rico Krueger

Rico Krueger

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 Rico Krueger.

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Rico Krueger

International journals

Published

Total: 3

        Technical reports

        • Krueger, R., Bansal, P., Bierlaire, M., and Gasos, T. (2020). Robust discrete choice models with t-distributed kernel errors. Technical report arXiv preprint arXiv:2009.06383. Transport and Mobility Laboratory, ENAC, EPFL.
        • Bansal, P., Krueger, R., and Graham, D. J (2020). Fast bayesian estimation of spatial count data models. Technical report arXiv preprint arXiv:2007.03681. Transport and Mobility Laboratory, ENAC, EPFL.
        • Bansal, P., Krueger, R., Bierlaire, M., Daziano, R., and Rashidi, T. (2019). Bayesian estimation of mixed multinomial logit models: Advances and simulation-based evaluations.. Technical report arXiv:1904.03647. Transport and Mobility Laboratory, ENAC, EPFL.

        Seminars

        Reviewing

      • Transportation Research Part C: Emerging Technologies (4)
      • Transportation Research Part A: Policy and Practice (3)
      • Accident Analysis and Prevention (2)
      • International Journal of Sustainable Transportation (2)
      • Research in Transportation Economics (2)
      • Transportation Letters: the International Journal of Transportation Research (2)
      • International Journal of Transportation Science and Technology (1)
      • Journal of Choice Modelling (1)
      • Networks and Spatial Economics (1)
      • Transportmetrica (1)
      • Total: 19 reviews for 10 journals (since 2004). Per year: 2020: 18, 2019: 1.

        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.

        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
        Optimization and Simulation
        Year: Spring 2020
        Section(s): Doctoral program in Civil and Environmental Engineering
        Lecturers: Michel Bierlaire, Rico Krueger, Melvin Wong
        Webpage: http://transp-or.epfl.ch/courses/OptSim2020/

        Miscellaneous lectures

        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

        Project supervision

        Masters theses

        Julien Harbulot
        Transportation mode classification with smartphone accelerometer data: An end-to-end deep learning approach
        Supervision:Rico Krueger, Michel Bierlaire
        Expert: Florent Martin
        17/02/2020-08/09/2020

        Semester projects

        • Bayesian analysis of multinomial discrete choice model with t-distributed kernel errors, Thomas Gasos, June 09, 2020