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Winter School 2025 (Beijing): Smart Sustainable Cities and Transportations

Date
8 – 14 December 2025

Venue
Tsinghua University
Haidian District, Beijing, 100084, P. R. China

Format
In-person

Learn from some of the world’s top universities this winter.

Embark on an exhilarating learning adventure this winter with the exclusive Winter School 2025 (Beijing) conducted two of the top universities in the world. Featuring an exciting line up of professors from TUM, TUM Asia and Tsinghua University.

Comprising a total of 13 sessions of training courses spanning from 08 – 14 December 2025, this Winter School features a cadre of experts from both universities to present research on Smart Sustainable Cities and Transportation.

Eligibility Criteria

Applications are open to candidates who already hold a bachelor’s degree or who are currently enrolled in a bachelor’s degree programme, in any of the following areas (but not limited): Civil Engineering, Transportation Engineering, Electrical Engineering, Geodetics, Mechanical Engineering, Geography, Computer Science, Communications Engineering, Economics, Mathematics, Physical Sciences, Architecture, Environmental Engineering, Tourisms.

All classes at the Winter School 2025 (Beijing) will be conducted in English. Participants should ensure that they are proficient in English (reading and writing) at university level.

Key Topics

Smart and green city growth
Use of geospatial data and geoinformatics to plan and manage smart city development and organize the transport system
Usage of big data analytics and artificial intelligence,
Usage if drones and robots in city and transport planning and management
Smart Railway systems and integration of public transport modes

Data-Driven Transportation Models

The emergence of novel data collection techniques has enabled a paradigm shift from primarily theory-based models to models that also exploit emerging data to develop more flexible, comprehensive functional forms. Machine learning methods are increasing in complexity and combined with the richer data can result in more powerful models. In this module we provide an overview of methodologies and related applications, such as resilience and emissions modelling, highlighting the state-of-the-art in the field of data-driven transportation models.

Lecturer: Prof. Dr. Constantinos Antoniou, TUM, Chair of Transportation Systems Engineering

Modelling Traveler Behaviour

The transportation network performance is the result of the interaction between demand and supply. In this module we will present models and applications of modelling traveller behaviour in order to be able to quantify the demand for transportation. We will look at different data collection techniques (traditional surveys, but also opportunistic data sources), and different modelling techniques. Applications from several real use cases and projects will be used to demonstrate the models and link them with policy and practice.

Lecturer: Prof. Dr. Constantinos Antoniou, TUM, Chair of Transportation Systems Engineering

Smart Capacity Management for Railway Systems

Rail Transportation Systems are the backbone of urban and continental transportation. In view of the rail renaissance and continuously growing demand experienced in recent years existing networks are operating under increasing stress. Transport planners and operators alike are therefore looking for ways to further increase the traffic load that can be supported by existing systems. In light of these developments the course will discuss different concepts and methodologies to define and assess the capacity of rail transportation systems. Starting from signalling and traffic control aspects, we will discuss approaches for robust capacity allocation, timetable stability evaluation, and network performance analysis and review new technologies in traffic management and train control with respect to their ability to further increase the efficiency and reliability of rail services.

Lecturer: Prof. Dr. Norman Weik, TUM, Professor for Design and Operation of Public Rail Transport Systems

Sustainable Urban planning concepts

City development and transport system are connected. This module will show how both are linked to each other and what kind of policies should be used to create a city with less congestion and a high living quality. Examples from cities worldwide will be shown. The principles and strategies of transport demand management will be presented. What are suitable policies to reduce the traffic volume on the roads and give priority for traffic which can’t be avoided and generates the highest benefits / revenue for the society? The last part of the presentation will focus on the implementation of these theoretical concepts into a real transport policy using Singapore as an example.

Lecturer: Dr. Andreas Rau, TUM Asia, Faculty Head and Principal Investigator (Rail, Transport & Logistics)

CityGML Model Analysis

Lecturer: Dr. Ihab Hijazi, TUM, Chair of Geoinformatics

Cycling Policies for a Sustainable City Development

This module aims to introduce the basic principles of public transport policies to create transport system where people can rely on a fast and passenger friendly public transport system. The theoretical policies will be supported by showing some case studies in Chinese cities, where these concepts are applied in a real city.

Lecturer: Prof. Dr. Yang Xinmiao, Tsinghua University

Transport Planning Theory and Its Development

This course is to introduce the basic principles of transport planning, planning methods, the working process of transport planning, and the application of transport planning theory in various transport planning and the latest research progress. The main contents include the characteristics of traffic demand and the main influencing factors, the content and main processes of urban traffic planning, the classical methods of urban traffic demand forecasting, and the outlook of traffic planning and management theory research.

Lecturer: Prof. Dr. Huapu Lu, Tsinghua University

AI for City Planning

Lecturer: Prof. Dr. Ying Long, Tsinghua University

AI for Transportation

Lecturer: Dr. Xianyuan Zhan, Tsinghua University

Admission Criteria

Admission to our Winter School is highly competitive. Selection is based on a comprehensive review of all documents received in the application by the examination board. Candidates will be notified by email as soon as the admission is granted.