Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Uchenna Ogenyi.

The work on this project will:

  • Integrate a variety of sensors into the robotic system to capture and interpret human cues from different modalities, including audio, visual, and tactile inputs.
  • Investigate how a robot can interpret and respond to a variety of human cues to improve overall interaction and task performance.
  • Implement adaptive learning techniques to allow the robot to learn and adapt its interaction patterns based on user preferences and evolving collaboration dynamics.
  • Apply principles of human-centered design to ensure that the multi-modal interaction is user-friendly, culturally sensitive, and aligns with human expectations for seamless collaboration.


The project aims to contribute to the development of advanced human-robot collaboration methods that leverage multi-modal interaction, resulting in more natural, intuitive, and efficient communication between humans and robots. The central objective is to create a robotic system capable of seamlessly capturing and interpreting various human cues, encompassing audio, visual, and tactile inputs.

The research methodology involves the integration of diverse sensors into the robotic framework to ensure a nuanced understanding of human cues across multiple modalities. By delving into how robots can effectively interpret and respond to a wide array of human cues, the project seeks to push the boundaries of interaction possibilities. This exploration is poised to not only improve collaboration dynamics but also optimize task execution in different scenarios.

One of the key facets of the project is the incorporation of adaptive learning techniques. This strategic approach enables the robot to dynamically learn and adapt its interaction patterns. By leveraging user preferences and accommodating evolving collaboration dynamics, the adaptive learning component ensures a responsive and personalized interaction experience.

Furthermore, the project places a strong emphasis on human-centered design principles. This design philosophy is crucial to ensuring that the multi-modal interaction system is not only technologically advanced but also user-friendly, culturally sensitive, and aligned with human expectations. The goal is to create a collaborative environment that seamlessly integrates robotics into various domains, including healthcare, education, and industry.

In essence, the project is a comprehensive exploration of cutting-edge technologies and methodologies aimed at transforming human-robot collaboration. Through the integration of sensors, adaptive learning, and human-centered design, the research anticipates contributing to more natural, intuitive, and efficient collaborative experiences across diverse applications.


Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Applicants should possess a solid understanding of the core principles in robotics, computer vision, and machine learning techniques. Proficiency in Python/C++ programming, strong analytical skills, and a foundation in computer science or related field are essential requirements. The ideal candidate must demonstrate the ability to think critically and independently, including the formulation of research problems. Additionally, effective oral and written communication skills, along with proficient time management, are highly valued.


How to apply

We’d encourage you to contact Dr Uchenna Ogenyi ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: COMP6231025