In the summer of 2023, we plan to recruit up to four interns to work on an open-source solution for applying DTs in smart cities. The ideal candidates are undergraduate students familiar with C/C++ and Python programming, computer networks, and cloud/edge computing. Students will work with motivated and dedicated graduate students to build the open-source platform.

Our research lab ( is well-equipped with computing and networking devices. National Tsing Hua University (NTHU) has been constantly ranked among the best universities by multiple international university rankings. The internship is ideal for international students considering doing an advanced Computer Science degree in Taiwan. The core idea of Digital Twin (DT) is to create a mirrored digital world of a physical world equipped with senor- and actuator-rich Internet-of- Things (IoT) devices. With live feeds from sensors in smart cities or historical/synthetic big data, DT leverages diverse physical models for real-time analysis and Machine Learning (ML) driven simulations for what-if analysis. The analysis results are sent back to IoT devices for autonomous actuation or human-in-the-loop decision-making. Many novel applications can be enabled by applying DTs to smart cities, e.g., when upgrading a wind turbine generator in a smart city, a new transmission system design may only exist in CAD (Computer Aided Design) software, but be evaluated with sensor data from the existing/working wind turbine to quantify its potential on power generation under the current or even imagined contexts. This is not possible in today’s smart cities.

Unfortunately, existing DT products and studies focus on manufacturing and healthcare domains, and research on DT-enabled smart cities is still in its infancy. To build up the experience of applying DTs to smart cities, we plan to develop the first open-source urban DT infrastructure and a disaster management application as a case study.

  • Field: Engineering
  • School: National Tsing Hua University
  • Organizer: Department of Computer Science
  • Period of Apply: Before July 1, 2023
  • Term: Three months between June and December, 2023
  • Website of Program:
  • Contact Person:Prof. Cheng-Hsin Hsu