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For most postgraduate students, a written thesis is a requirement for completing their studies. But in China, a law passed in 2024 is allowing some people to graduate with a practical achievement, such as an innovative product, technique or project, instead of following the conventional PhD route.
Since the law came into effect in January last year, more than 60 doctoral candidates have graduated with practical achievements, according to China’s Ministry of Education. The pathway is currently available only to people studying engineering courses, and it is part of China’s broad campaign to increase the numbers of ‘elite engineers’ in the nation, with the hope of overcoming technological bottlenecks. Around 50 postgraduate colleges have been established by universities across the nation since 2021 to support the elite-engineer campaign.
At these institutions, each student completes their training at both university and a company. They also have two supervisors — one in charge of their academic studies and the other helping them to gain hands-on experience. The engineering colleges offer both product-based and thesis-based graduation options, and students can choose which route to take.
Although universities in other nations also offer ‘industrial PhDs’, in which students work closely with a company, many of these degrees still require a written thesis. The product-based graduation route is expected to help train workers who are capable of solving real-life problems, says Zong Yingying, the dean of the College of Elite Engineers at the Harbin Institute of Technology in China.
A university and its partner company will agree on who owns the intellectual property for each resulting product, Zong explains. “But even if the university doesn’t get the intellectual property, it still benefits a lot from such a collaboration because it will get research funding and industry experts from the company, and the right to use their production lines.”
Nature spoke to three PhD graduates about their experiences taking part in the programme.
WU XIANGYANG: Railway engineer
Earned a PhD on intelligent manufacturing in rail transit systems at Southwest Jiaotong University in Chengdu, China.
Growing up in a small town on China’s east coast, I was obsessed with heavy machinery. My father worked for a company that made fish feed and he took many business trips to source machines. He often brought me with him on those trips. The memories of parts being welded together, the noise and smell of a busy workshop and the sight of machines being put together by a production line stuck with me.
I received a double bachelor’s degree in welding and software engineering in 2008. After that, I started working at the company Qingdao CRRC Sifang Rolling Stock, a manufacturer of rail vehicles based in Qingdao, China, at which I investigated ways to improve manufacturing techniques. But over the years, I began to feel the need to return to my studies to enhance my professional knowledge. That was why I started a master’s course in vehicle engineering in 2014, and then a PhD programme in mechanical engineering in 2022.
My PhD course was provided jointly by Southwest Jiaotong University and Qingdao CRRC, which allowed me to pursue the PhD without resigning from my job. China’s railway manufacturing sector doesn’t lack advanced machines or skilled workers. What it lacks are processes that can coordinate the various machines in a system into the same production schedule so that it’s possible to build products safely and efficiently. That was what I set out to solve with my PhD project: a system of software and hardware that can plan, monitor and adjust production processes in rail-vehicle factories in real time.
I can’t share the exact details of my product owing to the confidentiality requirements of my course. But to develop it, I spent a lot of time on the factory floor to collect data from every step of the manufacturing process. Then, I built computer models on the basis of those data to find techniques that can solve specific problems. Finally, I returned to the factory to test and improve my product.
One of the biggest challenges for me was that I had to do the bulk of my research in a factory, which was busy and noisy, and last-minute changes and uncertainty were common. To gather the data that I wanted, I often had to spend a lot of time searching for the best angle and location to record information from. And testing my product on a running production line was daunting. I was concerned about whether it would work, and whether it would lead to pauses in production. Any problems would potentially affect the work of everyone in the factory.
I am glad that I chose this graduation route. Compared with working out equations on paper or experimenting in a lab, what matters more to me as an engineer is whether innovations will work well in the real world. I will never forget the moment that the production line moved for the first time under the command of my system. That was the proudest day of my doctorate.
CUI GUANGZHANG: AI developer
Earned a PhD on intelligent computing systems at Zhejiang University in Hangzhou, China.
One day in 2003, I saw a shopkeeper in my hometown in eastern China having a video chat with someone on his computer using Tencent QQ, a Chinese instant-messaging service. I marvelled at how two people who were so far away from each other could talk face to face. From that moment, I knew that I wanted to do something with computers.
Twenty-two years later, I earned a PhD at Zhejiang University for developing an intelligent computing system called Yansheng, which supports the research, development and deployment of artificial-intelligence programmes. In a nutshell, the system coordinates a network of various types of computing equipment, enabling them to work together to train, fine-tune and deploy AI tools efficiently.
When I started my PhD studies in 2020, I intended to complete my degree by writing a thesis because that was the only option at the time. But as a PhD candidate in engineering, I often felt frustrated by this requirement. My heart was in solving practical issues, and I planned to go back to working outside academia after graduation. In January last year, when my supervisor told me about the alternative graduation option being introduced, I was ecstatic. But the road towards my graduation, which took place in December last year, was anything but smooth. Even though my product had been in development for a long time, I faced a path that no other students had walked before. I had to pass a product appraisal — equivalent to a thesis defence — made up of several steps, including a preliminary review conducted by faculty members at my university and some formal reviews from external specialists.

Sentinel — Human

Confidence

The text appears to be primarily journalistic reporting that incorporates direct testimonials; the framing is complex and rich with specific anecdotal detail, suggesting human authorship.

Signals Detected
low severity: Sentence length variance is noticeable; the personal anecdotes feature highly variable rhythm.
low severity: Strong, focused narrative threads connecting the policy context to the personal experiences of the graduates.
low severity: The quotes from the graduates are distinct and contain specific experiential details (e.g., memories of the factory floor, specific timeline of their academic choices) that resist simple template matching.
severity: The content relies heavily on direct quotes and first-person perspective, which increases verification difficulty for synthetic generation, though the core factual premises appear grounded in established policy discussions.
Human Indicators
The embedded personal narratives (WU XIANGYANG and CUI GUANGZHANG) demonstrate a specific, lived experience of navigating academic/industry pathways, including reflections on challenges like factory floor uncertainty.
The tone shifts naturally between reporting policy facts and relaying deeply personal motivations.