Name: Zhuoran Hu
Class Year: 2021
Major: Mathematics, Growth and Structure of Cities
Internship Organization: Tsinghua Urban Planning Institute (THTF Co.)
Job Title: Intern
What’s happening at your internship?
My internship is related to smart cities, transportation, and big data. The team that I joined is currently working on an artificial intelligent system named Insight (or called Hui Yan Da in Chinese). This product is mainly used to improve or further solve some existing problems in China’s highway network system, such as lack of hardware equipment as well as intelligence. Currently, a large number of monitoring video images can only be observed and identified by human eyes, so some emergencies cannot be timely detected, which leads to under-reporting. At the same time, some traffic information is not interconnected and shared.
A large number of real-time traffic data collected by the system are sealed and idle. The current situation makes it difficult for the government and the police to manage traffic networks effectively. It is hard to make predictions as well as to identify and deal with emergent traffic accidents at first. The team is able to use machine learning techniques to form some models that can automatically analyze traffic problems. The goal of the product is to improve intelligent traffic management and service capabilities. Most of our clients are local government and some police offices or security departments. People in our group have pretty diverse backgrounds and have different responsibilities. There are people in charge of collecting, selecting, and categorizing different types of data (mostly images of roads or highways). There are also people who build models and test those models. My work is more similar to the first type because of my lack of knowledge in computer science, especially in algorithms. My other work includes preparing materials for conferences, taking notes, and organizing some team-building events. I also make phone calls, participate in group discussions, and brainstorm with other team members. We are trying to train and improve the model so that it can detect more kinds of traffic accidents even under a dark environment with a bad network connection.
Why did you apply for this internship?
I applied because I want to explore what kind of jobs that I can do with my background in both math and cities. I find organizations or occupations related to smart cities will be a good fit because it is interdisciplinary. I am interested in cities and how people circulate around the city. This internship touches many topics that I am interested in, including transportation and data.
What is something you have learned from your internship that you didn’t expect?
Before I came to this internship, I thought the concept of smart cities is more related to the field of urban planning or urban studies. But actually, the concept of smart cities is based more on computer science instead of urban studies. To succeed in this field, people not only need to have some knowledge about cities, but also need to become an expert in computer science as well as have a deep understanding of algorithms. I believe that if I am good at coding, I will be able to explore more in this internship.
Can you talk about the skills you are learning and why they are important to you?
I am learning the company’s own software that is used for data annotations. I am also learning the company’s own chat tool that people can use to send large documents and images to each other. I think this experience provides me inspirations and gives me a better understanding of software developments.
What has been the biggest challenge you have faced at your internship?
I think the biggest challenge is to wake up early. I need to wake up at 7 a.m. and leave my home at 7:30 a.m. in order to arrive at the company before 8:30 a.m. The fast pace of the company is also a challenge, because everyone needs to finish a lot of work in a limited time. I think my experience at Bryn Mawr prepared me for the work. I already learned how to work efficiently and multi-task.