- Type of research degree
- Application deadline
- Ongoing deadline
- Country eligibility
- International (open to all nationalities, including the UK)
- Competition funded
- Dr He Wang
- School of Computing
Every future city will have a digital `twin' that consumes data from the physical city and generates predictions for its design, construction, and management. The centre-piece of this digital twin is its residents. This research project is to build such residents, a `digital twin' of crowds, by proposing the next-generation mathematical models and artificial intelligence algorithms. This will be achieved by combining machine learning with neuroscience, architectural design and crowd management. Today, it is expected that more than 6.7 billion people will aggregate in urban spaces by 2050, leading to megacities of 10 million inhabitants (United Nations). The research project will lead to a crowd-driven framework that can predict crowd motions, help design new spaces and improve existing spaces, to eliminate potential dangers, minimise discomfort and maximise efficiency, enabling planners and policymakers to meet the great challenges of fast urbanisation in the 21st century.<br /> <br /> This project is to look into the fundamental crowd motions in different environments including indoor/outdoor scenarios. The goal of this project is to propose a series of new models and mathematical frameworks to capture the crowd motions for the purposes of analysis and simulation.<br /> <br /> The research falls into the category of data-driven crowd analysis where data is intensively used for analysis as compared to traditional empirical modelling where concise mathematical models are made trying to capture the complex structure in the data. However, because of the high complexity, more data (big data) is needed and meanwhile corresponding algorithms and models with enough capacity for data consumption are to be developed. <br /> <br /> The project is currently accepting PhD applications every year.
<p>Formal applications for research degree study should be made online through the <a href="http://www.leeds.ac.uk/rsa/prospective_students/apply/I_want_to_apply.html">University's website</a>. Please state clearly in the research information section that the research degree you wish to be considered for is 2D and 3D crowd analysis and simulation using deep learning and big data analysis as well as <a href="Dr He Wang">Dr He Wang</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>We welcome applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.</em></p>
Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.
The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at 6.0 in reading, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.
<p><strong>Self-Funding Students are welcome to apply.</strong></p> <p><strong>UK students</strong> – The <a href="https://phd.leeds.ac.uk/funding/138-leeds-doctoral-scholarships-2021-january-deadline">Leeds Doctoral Scholarship (January deadline)</a> and the <a href="https://phd.leeds.ac.uk/funding/53-school-of-computing-scholarship">School of Computing Scholarship </a>are available to UK applicants. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds.</p> <p><strong>Non-UK students</strong> – The <a href="https://phd.leeds.ac.uk/funding/53-school-of-computing-scholarship">School of Computing Scholarship </a> is available to support the additional academic fees of international applicants. The <a href="https://phd.leeds.ac.uk/funding/48-china-scholarship-council-university-of-leeds-scholarships-2021">China Scholarship Council - University of Leeds Scholarship</a> is available to nationals of China. The <a href="https://phd.leeds.ac.uk/funding/73-leeds-marshall-scholarship">Leeds Marshall Scholarship</a> is available to support US citizens. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds.</p>
<p>For further information regard your application, please contact Doctoral College Admissions by email: <a href="mailto:EMAIL@leeds.ac.uk">p</a><a href="mailto:firstname.lastname@example.org">email@example.com</a> or by telephone: +44 (0)113 343 5057.</p> <p>For further information regarding the project, please contact Dr He Wang by email: <a href="mailto:H.E.Wang@leeds.ac.uk">H.E.Wang@leeds.ac.uk</a></p>
<h3 class="heading heading--sm">Linked research areas</h3>