UNIQplus participants gain hands-on research experience in engineering at Oxford

The UNIQplus programme offers talented undergraduates and recent graduates from under-represented groups the opportunity to experience postgraduate research at Oxford firsthand. During the programme, interns join active research groups, contribute to ongoing projects and gain insight into what it is like to pursue a research career.

This year, participants on placements in the Department of Engineering Science worked on projects spanning artificial intelligence, robotics, advanced manufacturing and materials engineering. Alongside their research, they attended seminars, workshops and social events, giving them a glimpse of life as part of a research community.

The placements concluded with a presentation day where participants shared their research with peers and supervisors.

Ali Shihab

Ali Shihab worked with Associate Professor Jakob Foerster in the Foerster Lab for AI Research (FLAIR) on a project exploring reward attribution in general-sum games. He says “From learning about the pioneering research coming out of FLAIR to rapidly up-skilling in JAX and contributing to the lab’s JaxMARL framework, the internship was pivotal to my development as a researcher.”

Ali’s placement focused on learning reward attribution methods in multi-agent reinforcement learning. While he had previous experience in reinforcement and meta learning, the project introduced him to multi-agent RL and evolutionary reward-shaping approaches. During the placement he learned new technical tools, including JAX, and contributed to the lab’s JaxMARL framework while exploring research stemming from the lab’s work on algorithms such as CoMA and LOLA.

Lubabah Hossain

Lubabah Hossain worked with Associate Professor Liang He and Dr Chenying Liu on a project focused on the design and manufacture of personalised wrist orthoses using 3D printing. Orthoses are devices or apparatus like a brace or splint, which are used in orthopaedics to support or immobilize the spine or limbs.

Her research involved tuning printing parameters for thermoplastic polyurethane (TPU), a flexible material widely used in wearable devices but known for being challenging to print reliably. Lubabah tested parameters such as temperature, printing speed, grid pattern and line thickness to achieve consistent prints with the desired mechanical properties.

She worked with several desktop 3D printers, including the Prusa XL, Prusa MK4S and Raise3D E2, using slicing software such as PrusaSlicer and ideaMaker to refine printing settings. Over time, the project became more systematic, with Lubabah producing standardised dog-bone specimens for material testing.

She also contributed to a related project on airtight TPU printing, successfully reproducing a technique to manufacture an airtight soft robotic finger.

Lubabah says of her placement, “It was interesting to experience what it would be like to work in a research group. I really enjoyed the group presentation sessions where everyone shared updates and helped troubleshoot.” 

She added that the internship confirmed her interest in pursuing research, and she has since begun a PhD in Civil Engineering at Newcastle University.

Mark Corfe

Mark Corfe worked with Associate Professor Emilio Martínez-Pañeda investigating hydrogen–metal interactions to support the transition to greener energy systems.

His project explored electrochemical hydrogen permeation in binder jet printed 17-4PH stainless steel. The research aimed to better understand how hydrogen interacts with advanced metallic materials, an important challenge for the safe deployment of hydrogen technologies.

He says, “The internship was incredibly engaging and provided a great insight into what studying towards a DPhil at Oxford is like. It changed my view on a doctorate programme and made me consider such a pathway.”

He added that the department was welcoming and collaborative, and that socialising outside the lab helped participants and researchers form strong connections.

Ruhan Mannan

Ruhan Mannan worked with Associate Professor Tingting Zhu and Dr Munib Mesinovic at the Institute of Biomedical Engineering on a machine learning project focused on survival analysis in clinical settings.

His research involved developing a model capable of predicting patient survival curves using both time-series and static data. The approach incorporated competing risks, events that prevent the primary event of interest from occurring, allowing more accurate modelling of complex clinical scenarios.

Ruhan says, “Since I had no prior research experience, this was a great learning opportunity. It allowed me to apply the knowledge from my studies to an impactful topic that I really enjoyed.” 

Professor Zhu added that Ruhan developed a novel deep learning model for time-to-event analysis in intensive care using ordinary differential equations to model multivariate time-series data together with variational inference. “This is a challenging methodological problem in clinical machine learning, and Ruhan approached it with impressive technical maturity and independence”, she says.

James Millar

James Millar worked with Dr Victor-Alexandru Darvariu at the Oxford Robotics Institute on a project investigating how vision–language models can help robots recover from navigation failures. He says: “I had the best summer in Oxford and everyone I met and worked with was lovely. I learned a lot, and it helped develop me not just academically, but as a person too.”

The project aimed to improve long-term autonomy for robots operating in complex environments. Using a dataset of thousands of images captured from a robot’s onboard camera, James evaluated how accurately AI models could answer questions about the scenes. The responses were validated by comparing them with survey responses from people in the office.

After confirming that the models could reliably analyse the images, the project explored whether they could determine if a robot would be able to recover from specific failure events.