Newsroom University of Manchester

Creativity, AI and Collaboration: Looking Back on CreaTech 2026

Wed, 09 Sep 2026 12:27:25 +0100

Between February and June 2026, the CreaTech Network Series brought together researchers, creatives, cultural organisations and industry partners from across Greater Manchester and the North West to explore the opportunities and challenges presented by emerging digital technologies. Delivered by Digital Futures, Creative Manchester and Turing Innovation Catalyst Manchester, the series explored creativity and AI through three events focused on entertainment, cultural heritage, and free and open-source technologies. Each event combined short talks with panel discussions and audience questions, creating space for people from different sectors to share perspectives and experiences.

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Creativity and AI: Entertainment

The series opened at Contact Theatre with a discussion on the growing role of AI across film, television and games. Hame Sehmi, Lead Research Engineer at Epic Games, shared examples of how AI tools are being used in areas such as facial animation and digital production workflows. Tillie Quattrone from Ģ��Ƶ explored the use of AI in digital de-ageing for film and some of the questions these technologies raise around creative work and production. The talks were followed by a panel discussion and audience Q&A, which sparked conversation about how AI is changing the entertainment industry.

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Creativity and AI: Cultural Heritage

The second event took place at Manchester Art Gallery and focused on the use of AI within libraries, archives and museums. Jennie Fletcher and Lesley Gray from the University of Cambridge introduced the AI for Cultural Heritage Hub (ArCH), which is supporting organisations to explore new ways of making collections more accessible. Jason Evans, Open Data Manager and AI Lead at the National Library of Wales, shared examples of how AI is being used to improve access to cultural collections and support new forms of public engagement. Dr Benjamin Wiggins from Ģ��Ƶ also reflected on how AI can work alongside approaches such as crowdsourcing and public participation. Audience questions continued the discussion, with conversations ranging from practical applications of AI through to the challenges and responsibilities that come with its use.

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Creativity and AI: Free and Open-Source Technologies

The final event in the series was held at SISTER and explored the role of free and open-source technologies in creative and cultural practice. Jan Macháček, Principal Engineer and Visiting Professor at Ģ��Ƶ, spoke about the opportunities that open technologies create for learning, experimentation and collaboration. Eriol Fox brought a design perspective to the conversation, discussing accessibility and inclusion in the development of digital tools. The wider panel, which included Mengzhi He and Julian Tait, CEO of Open Data Manchester, explored the importance of community, skills and knowledge sharing across the sector. The event concluded with a panel discussion and audience Q&A, giving attendees the opportunity to reflect on the future role of open technologies in creative practice.

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Across all three events, participants explored how emerging technologies are influencing creative work in different ways, from film production and storytelling to cultural collections and open-source communities. The series created opportunities for knowledge exchange, new partnerships and cross-sector collaboration, helping to strengthen connections across the region's CreaTech ecosystem. We'd like to thank all the speakers, attendees and partners who contributed to the programme, and we look forward to continuing these conversations through future CreaTech Network activities.

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Semi-pessimistic Reinforcement Learning paper accepted in JASA.

Thu, 03 Sep 2026 16:46:31 +0100

Many real-world decision-making problems rely on large amounts of data but only a small proportion of that data is fully labelled. This paper introduces a new reinforcement learning method that can learn effectively from both labelled (with rewards) and unlabelled data, making it better suited to real-world applications where collecting reward information is expensive or impractical, including healthcare.

Reinforcement learning (RL) is a powerful paradigm for policy optimisation in sequential decision making, it is used to train an intelligent agent (policy) to make optimal decisions by maximising some long-term reward. While online RL learns a policy by actively interacting with an environment and collecting new data through exploration and exploitation, offline RL learns a policy from a fixed, pre-collected dataset without further interaction with the environment. A typical challenge in offline RL is distributional shift, where the learned policy may encounter scenarios not covered by the offline data. This paper tackles distributional shift and integration of labelled (with rewards) data and unlabelled (without rewards) data in offline RL.

The proposed method, called semi-pessimistic pseudo labelling (SPL), makes it possible to take advantage of the unlabelled data to find a better policy than would be possible only using the labelled data. This improves the reliability of decision-making by improving estimation and accounting for uncertainty while remaining computationally efficient. The authors provide theoretical guarantees for the method and demonstrate its effectiveness through simulations, standard reinforcement learning benchmarks, and an application to adaptive deep brain stimulation for Parkinson's disease. By making better use of available data, the approach has the potential to improve AI systems in healthcare and other high-stakes domains.

You can find the full ‘Semi-pessimistic Reinforcement Learning’ paper here.

Jin Zhu^1,2, Xin Zhou³, Jiaang Yao⁴, Gholamali Aminian⁵, Omar Rivasplata⁶, Simon Little⁴, Lexin Li³∗, Chengchun Shi¹∗
¹London School of Economics and Political Science, ²University of Birmingham, ³University of California at Berkeley, ⁴University of California at San Francesco, ⁵The Alan Turing Institute, ⁶University of Manchester. *Corresponding authors.

ELLIS Summer School success!

Wed, 29 Jul 2026 09:25:13 +0100

After three successful events between 2023 and 2025, the ELLIS Society approved our fourth summer school on Machine Learning for Healthcare and Biology. As in previous years, this three-day event brought participants up-to-speed on the latest methods and technologies in machine learning with a focus on healthcare and biology.

12 expert researchers visited from 8 European organisations, with sessions covering DNA language models for engineering biology; ‘Swarm’ intelligence; Real-world validation of healthcare LLMs and many more topics. Participants also had an opportunity to showcase their own work at our research poster session. �ċ�ċ

Feedback has been overwhelming! We but here are a couple of quotes that didn't make it into the final edit:

Keep an eye on : we have some big news coming very soon…

Contribute to Shaping the Digital Worlds Theme!

Tue, 28 Jul 2026 15:40:51 +0100

"The funding landscape is moving under our feet. UKRI and the research councils are shifting decisively towards research done with industry. This includes partnership expectations written into calls, co-created programmes, impact measured in adoption and so on.��

It is really important to me that we understand can the theme help you be prepared and build a wider collective UoM collaborative space to be prepared and perhaps discover new ways of working in the process? Our theme has enormous potential in many areas from digital twins, sensing and connected environments, immersive and virtual worlds. Realising that potential often it starts with a conversation with the right partner at the right moment or having assistance in maintaining conversations and partnerships already in place."

, Theme Lead, is inviting Ģ��Ƶ colleagues to complete a short consultation that will help shape how the Digital Worlds theme works with industry and business partners over the coming year.

In return of colleagues completing this short consultation, the intention is to build a recurring offer:

- An annual Digital Worlds Industry Showcase
- Two themed roundtables a year (digital twins; sensing and connected environments; immersive and virtual environments; the physical–virtual interface)
- A live partnership map and case-study repository
- An annual report back to everyone who contribute

Please complete the consultation via the link below:

The survey should take approximately 10–15 minutes to complete.

Alternatively, if you would prefer an informal conversation, David Topping would be pleased to hear from you at david.topping@manchester.ac.uk.

Applications now open: £100,000 investment opportunity for responsible AI innovators

Tue, 14 Jul 2026 10:27:34 +0100

Ģ��Ƶ and The Jeremy Coller Foundation launch new competition to support early-stage ventures utilising AI for the benefit of people and society

Ģ��Ƶ has launched a new responsible AI competition in partnership with the Jeremy Coller Foundation, offering a £100,000 equity investment to support one promising early-stage venture from its global community of students, staff and alumni.

Applications are now open for the Coller AI Competition, which is designed to help innovators develop ventures with real-world potential – ensuring technology empowers rather than excludes. The competition will support solutions that use AI in ways that are fair, transparent, sustainable and focused on social benefit. The winner will benefit from the opportunity to work closely with the Jeremy Coller Foundation team to develop their venture.

The initiative forms part of the University’s Challenge Accepted campaign, which champions ideas with the potential to tackle major global challenges.

Backed by Manchester alumnus and philanthropist Jeremy Coller, the competition brings together the University’s research strength, entrepreneurial talent and commitment to responsible innovation. It aims to identify and support founders developing AI solutions that are not only commercially promising but designed to benefit people and society.

Finalists will pitch their ventures at the University’s Innovation Festival in October, where the winner will be selected to receive the £100,000 investment.

Professor Aline Miller, Associate Vice President (Enterprise) at Ģ��Ƶ, said: “This is an exciting opportunity to back one early-stage venture with the support and investment needed to develop responsible AI with real-world potential. We’re looking for founders who want to build something purposeful, practical and capable of making a positive difference.”

Jeremy Coller said, “The AI revolution is already changing and shaping our world at a dizzying speed. Used smartly and responsibly AI can be the key that unlocks solutions to some of the greatest challenges facing this planet, and the Coller AI Competition will help Manchester students, staff and alumni turn that potential into reality.”

is the philanthropic vehicle of private equity entrepreneur Jeremy Coller. The Foundation works to create positive impact on globally significant issues with a focus on education, entrepreneurship, pensions innovation and the transition to a more sustainable food system. By supporting ambitious ideas, the Foundation helps drive lasting change and empower the next generation of innovators and problem-solvers.

Application timeline – 2026

The competition is open for applications from any students, staff or alumni from across the University who are working on an AI-driven business. At least one founder in each team must be within one of these categories.

14^th July – applications open
1^st September – applications close
21^st September – finalists notified
9^th October – final pitches and award

Find out more and apply now –

Join us for a week-long celebration of innovation, from Monday, 5 to Friday, 9 October 2026.