I am keen to supervise self-motivated PhD students who have similar research interests to mine; i.e., Machine Learning, Pattern Recognition, Machine Perception and their applications to Intelligent System Development. You can find my current PhD Research Project Suggestions, where the background knowledge and skills required for PhD studies are also specified as pre-requisite. You will need to develop your own research proposal based on either my PhD project suggestions or your self-proposed project if accepted by me.

If you are interested in working with me for your PhD studies at The University of Manchester, you are strongly encouraged to contact me informally for the first instance. Prior to contacting me, however, all applicants (especially international applicants) should first check the funding information below to see if you meet the funding requirements and have been following a proper inquiry procedure described below.

When you contact me, you'll need to send me your CV, your personal statement and other background materials of yours (e.g., your transcripts at different levels, your UG final year project report, your MSc thesis and selected publications if you have). Once we have an agreed research topic along with the proposal drafted by yourself, you can kick off your formal application via our Online Application website. For the formal application, you can find the detailed information from The Departmental Research Student and The University Research Student pages. During the application process, please direct all non-acadmic quaries, e.g., English language qualification for overseas students, to our Recruitment and Admission team (Email: FSE.doctoralacademy.admissions@manchester.ac.uk).  

Funding Information for Prospective Applicants

The following funding information is only for your convenience. If you have any questions regarding funding and/or want the latest funding information, please directly consult with our CS Department Admission Office.

• UK Applicants

  At the University of Manchester, there are various financial support opportunities for a prospective UK PhD student. In Department of Computer Science, qualified UK applicants (who at least have been awarded the first-class honour in UG or the distinction in MSc, ideally both) may be awarded a full studentship including tuituion fee and maintenance for our normal three-year PhD programme. The departmental funding is allocated on a competitive basis; qualified candidates are shortlisted and interviewed to be awarded such a scholarship. In addition, the University offers alternative scholarship, e.g, President's Doctoral Scholar Award and FSE Faculty Studentship. You can access to the The University Postgraduate Funding page to find the latest funding information as well as checking your eligibility. If you have any questions to funding, please don't hesitate to direct your inquires to our Recruitment and Admission team (Email: FSE.doctoralacademy.admissions@manchester.ac.uk).

• EU Applicants

  Due to Brexit, the previous policy (i.e., EU applicants were treated the same as UK students) has been changed. In general, EU applicants are considered as International applicants (see below) unless you have been granted the EU settled status hence still treated the same as UK students. If you are not sure about whether you are eligible for studentship offered to UK applicants, you can directly contact our PGR office for clarification.

• International Applicants

  To apply for any funding described below, a candidate must gain the English qualification before their application.
  
  For an excellent international student, who at least holds a 1st class honour or distinction degree in MSc or equivalent (ideally both), our CS department could offer you a scholarship that waives the full tuition fee each year over three years. It is also possible for Ellite students to be awarded additional funding to cover the living expenses. For your information, "ELITE" means that one has been rated to top 3% in their UG/PGT classes in terms of academic performance,  published papers in prestigious journals of a high impact factor/topmost conferences (In practice, the above two requirements are essential for success), won non-trivial academic award(s) and so on. The departmental funding is allocated on a competitive basis; qualified candidates are shortlisted and interviewed to be awarded such a highly competitive scholarship. 
  
  The following information is especially for an outstanding international applicant who wants tuition fee waiver and maintainance. Our university and FSE faculty offer extremely competitive President's Doctoral Scholar Award and FSE Faculty Dean's Award for top-level elite students including qualified interational applicants. The selection process undergoes at two levels: department and faculty/university; that is, each department can only nominate up to two candidates no matter how many applications are received. Then a panel at faculty/university level makes the final decision after interviewing and assessing all the candidates selected by different departments. The internal deadline in CS is normally 1st November/Febuary for the first/second round and enrollment time must be next September. If an international student needs a FULL studentship, you should first check with The Department Postgraduate Funding, FSE PhD Funding and The University Postgraduate Funding pages for eligibility.
  
  For Chinese applicants who graduate from one of top-36 universities in China or one of top-50 university in the World (according to Times World University Rankings in the current year), they can also apply for the joint scholoarship between University of Mancheste (UoM) and Chinese Scholarship Council (CSC). The UoM-CSC Scholarship provides a full studentship and the essential requirements include an MSc degree in distinction equivalent and at least one paper published in prestigious conferences and journals of a high impact factor (more details can be found from the FSE PhD Funding website). The selection process also undergoes at two levels: school and faculty/university.  The deadline in CS is normally 1st of January and the enrollment time must be next September.

PhD Students Supervised in Manchester

I am currently the primary supervisor for the following PhD students:

• Ruoyu Sun (2019-present) 
  Combining Reinforcement Learning and Rule-based Methods for Local Motion Planning in Autonomous Driving
  
  
• Lisheng Wu (2020-present) 
  Boosting Exploration and Learning Efficiency for Goal-conditioned Reinforcement Learning 
  
  
• William Murphy (2020-present) 
  Attention-based Deep Learning for Time Series Forecasting
  
  
• Tom Baker (2021-present) 
  Performance Style Conversion using Deep Generative Modelling
  
  
• Shaojie Zhang (2023-present) 
  Deep Constrained Clustering and Its Applications
  
  
• Zhizhong Zhao (2023-present) 
  XRL: Towards Explainable Reinforcement Learning in Autonomous Driving
  
  
• Xianyu Meng (2024-present) 
  Speech Information Component Analysis for Learning Disentangled Speech Representations
  
  

In Manchester, the students listed below, who were under my supervision as their sole or primary supervisor, have been awarded PhD degrees.

• Maksymilian Aleksander Wojtas (2019-2023) 
  Neural Networks for Iterative Feature Importance Analysis of Deep Learning Models
  
  
• Jiyong Lee (2019-2023) 
  Anchor-free Pipeline Temporal Action Localisation
  
  
• Jonathan Crawfold (2017-2021) 
  Exploring Generalisable Multi-task Reinforcement Learning Agents Using Task Similarity Metrics  
  
  
• Hao Zhou (2016-2021) 
  Domain Shift Adaptation via Adversarial Learning for Speech Emotion Recognition 
  
  
• William Woof (2016-2020) 
  Deep Learning on Semi-structural Data and Its Application to Video-Game AI
  
  
• Danny Wood (2015-2020) 
  Effects of Network Weight Structure in Echo State Networks
  
  
• Mike Phuycharoen (2015-2019) 
  Deep Learning Uncovers Genomic Features of Cell-type and State 
  
  
• Peizhi Shi (2013-2018)
  Learning Constructive Primitives for Procedural Content Generation  
  
  
• Harits As Rosyid (2013-2017)
   Adaptive Serious Educational Game with Machine Learning 
  
  
• Qian Wang (2013-2017)
  Zero-Shot Visual Recognition via Latent Embedding Learning
  
  
• Fabio Zennaro (2013-2017)
  Feature Distribution Learning for Covariant Shift Adaptation Using Sparse Filtering
  
  
• Ubai Sandouk (2012-2016)
  Concept Representation Learning for Multimedia Information Retrieval 
  
  
• Jonathan Parkinson (2012-2016)
  Representation Learning with a Temporally Coherent Mixed Representation
  
  
• Tamas Madl (2011-2015)
  Bayesian Mechanisms in Spatial Cognition: Towards Real-World Capable Computational Cognitive Model of Spatial Memory
  
  
• David Buckley (2011-2015)
  Skill Capture in First-Person Shooters
  
  
• Jonathan Roberts (2009-2013)
  Learning-based Procedural Content Generation
  
  
• Ahmad Salman (2007-2011)
  Learning Speaker-Specific Characteristics with Deep Neural Architectures
  
  
• Yun Yang (2006-2010)
  Clustering Ensemble and Applications to Temporal Data Clustering
  
  
• Arslan Shaukat (2005-2009)
  Emotional State Anaysis and Recognition from Speech Signals
  
  
• Shihai Wang (2005-2009)
  Boosting Learning Applied to Facial Expression Recognition