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NTU RISE-AI 2026

Research Investment in Skills and Expertise in AI

The First NTU Interdisciplinary Conference on Data, Quantitative and Computational Intelligence.  NTU RISE-AI 2026 invites researchers from all disciplines to participate.​

Past event
RISE AI event logo

Type of event: Conferences

From: Wednesday 20 May 2026, 8.45 am

To: Wednesday 20 May 2026, 5 pm

Location: Nottingham Trent University, Pavilion Room 121, Clifton Campus, Nottingham, NG11 8NS

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Event details

This one-day interdisciplinary conference brings together researchers from across NTU who work with data, quantitative methods, computational modelling, or artificial intelligence, regardless of disciplinary background.

The aim of the conference is to build a university-wide community of practice around data-driven research, transparency, reproducibility, and interdisciplinary collaboration.

Researchers from all schools, disciplines, and career stages are warmly invited to participate.

Conference Theme

The conference explores how data, quantitative methods, and computational intelligence are transforming research and decision-making across fields including but not limited to:

  • Health and life sciences
  • Social sciences and humanities
  • Artificial intelligence and machine learning
  • Policy and governance
  • Risk, resilience, and emergency science
  • Environmental and cultural data

Keynote Speakers

The conference features keynote contributions from leading scholars and practitioners working across disciplines:

  • Professor Mazeda Hossain - Professor and Director of the Eastern Africa Centre, Nottingham Trent University
  • Professor Mark Altaweel - Professor of Near East Archaeology and Archaeological Data Science, UCL
  • Dr Lucía Pereira Pardo - Ramón y Cajal Researcher, INCIPIT, Spanish National Research Council (CSIC)
  • Professor Daniel King - Professor of Organisation Studies, Nottingham Trent University

Conference Highlights

The programme will include:

  • Interdisciplinary keynote talks
  • Parallel research presentation sessions
  • Lightning talks
  • Poster session
  • A “Data Failures and Lessons Learned” session promoting research transparency and reproducibility
  • Structured networking and collaboration discussions

The conference will also mark the launch of the: NTU Data, Quantitative & Computational Intelligence Network

Interdisciplinary Organising Committee

  • Dr Damilola Omodara – Public Health
  • Dr Sotiria Kogou – Heritage Science
  • Professor Alex Sumich – Biopsychology
  • Dr Hind Elhinnawy – Criminology
  • Associate Professor Marcello Di Bonito – Environmental Sciences
  • Dr Ben Dickins – Molecular Biology
  • Dr Ayse Ulgen – Data Science
  • Dr  Gadelhag Mohmed – Computational Intelligence
  • Dr Pedro Machado – Neuromorphic Computing
  • Associate Professor Isibor Ihianle – Computational Intelligence
  • Dr Archontis Giannakidis – Artificial Intelligence
  • Associate Professor John Morris – Paediatric Sport Science
  • Associate Professor Golnaz Shahtahmassebi  –  Applied Statistics

Conference Support

NTU RISE‑AI 2026 is supported by the NTU Research Investment in Culture and Environment (RICE) Fund. The Fund recognises RISE‑AI’s strong potential to work across organisational boundaries and to help foster a culture of interdisciplinarity - key priorities that align with NTU’s ambitions to strengthen its research culture and environment.

Who Should Participate?

We welcome:

  • Researchers working with data of any type
  • Quantitative researchers
  • AI and machine learning researchers
  • Social scientists using data
  • Humanities scholars using digital or computational methods
  • PhD researchers and early-career academics
  • Staff interested in data-driven research collaboration

Call for Contributions

We invite contributions from researchers using data, quantitative analysis, computational modelling, or AI methods.

Presentation opportunities include:

  1. Research Presentations: 15-minute presentation plus discussion (Parallel thematic sessions)
  2. Lightning Talks: 3-minute rapid presentations (Ideal for early-stage ideas or collaboration opportunities)
  3. Data Failures and Lessons Learned: 5-minute reflections (Sharing methodological challenges and reproducibility lessons)
  4. Poster Session: Open to all disciplines (Particularly suitable for PhD researchers and early-career academics)

Submit an abstract.

Registration

To register for this event please please complete the Conference Registration form. Due to venue capacity, places will be limited, and early registration is encouraged.

Key Dates

  • 20 March 2026 – Abstract submission and conference registration open
  • 20 April 2026 – Abstract submission deadline
  • 5 May 2026 – Notification of acceptance
  • 20 May 2026 – Conference

Conference Schedule

TimeSessionDetails
08:45 - 9:15Registration and CoffeeInformal networking
09:15 - 09:50Welcome and Vision
  • Professor Neil Mansfield (Executive Dean of Research and International Reputation) -  NTU’s Vision for AI, Data, and Research Leadership
  • Professor Kirsty Smallbone (Executive Dean School of Science and Technology) -  The School of Science & Technology as an Innovation Enabler
  • Fiona McKerlie (Head of Researcher Development) - Research Culture, Environment, and Community
09:50 – 10:30Keynote 1 – Professor Mazeda HossainThe Global Wellbeing and Resilience Index: A Mixed-Methods Framework for Mapping Structural Vulnerabilities Across 120 Countries
10:30 – 11:30Parallel Session Block 1
  • Session 1: Health, Medicine & Life Sciences Data
    • Anil Babu Katiki -  An AI/ML-Driven Framework for Peptide Selection and AAV9 Capsid Engineering for Targeted Gene Delivery
    • Dr Mark Andrews -  Deep Learning Models for Language Data Analysis in Psychology and the Social Sciences
    • Professor Amin Al-Habaibeh -  The Application Of Artificial Intelligence In The Medical, Energy And Manufacturing Sectors - Case Studies
  • Session 2: Humanities, Social Sciences & Cultural Data
    • Professor Vangelis Tsiligkiris - From Prompts to Performance: Predicting Learning Outcomes from LLM Interaction Depth in Higher Education
    • Dr Yun He - Network analysis of small community businesses in Kenyan slum neighbourhoods
    • Dr Geoffrey Castillo -  From lab to field: Behavioural economics research at the BEAR group
11:30 – 11:45Coffee Break 
11:45 – 12:30Keynote 2 – Professor Mark AltaweelHeritage, Archaeology, and History in the Age of AI
12:30 – 13:30Lunch and Poster Discussion
  • Parvathy Kizhakke Covilakam - Digital Transformation and Labour Market Dynamics: An analysis on the impact of the NHS App, 2011-2024.
  • Dr Doratha Vinkemeier -  Automated analysis of protein-protein interactions - the case of STAT1 gain of function disease
  • Professor Rebecca Parry - Institutional Limits of AI in Law: Evidence from Insolvency Practice
  • Dr Lee Mattocks - What Makes Clothes Last? Analysing Garment Retention through Qualitative Data and Wardrobe Studies
13:30 – 13:50Lightning Talks
  • Dr Grace Guan - Data-Driven Life Cycle Assessment for Circular Fashion: Evaluating a Novel Fibre-to-Fibre Recycling approach and Its AI-Enabled Processes
  • Rajapakse Appuhamilage Dinith Sathsara Arunasiri - Towards Digital Twins for Second-Life Battery Management
  • Malsha Nadeeshani Wickramasinghe Rathnawalli Abarana Polwaththegedara - Role of corporate governance in ethical AI adoption
13:50 – 14:45Parallel Session Block 2
  • Session 5: AI, Machine Learning & Computational Modelling
    • Sina Khoshgoftar - An Autonomous Agentic Approach for Anomaly Management via Multi-Modal Learning in Smart Transportation Systems
    • Dr Chaimaa Essayeh - MARLEM: Multi-agent Reinforcment Learning for Local Energy Markets
    • Dr Song Wu - Agentic AI as a Research Collaborator: A Case Study in Railway Cable Failure Prediction
  • Session 6: Policy, Risk, Resilience & Applied Data
    • Fatima Zafar - Integrated process development for converting plastic waste into sustainable aviation fuel with techno economic and environmental assessment
    • Dr Farhad Fassihi Tash - The Knowledge Gap Trap: Risks of Governance Failure in the age of AI
    • Dr Pedro Machado - Architecting Scrutinisable Semi-Autonomous Multi-Agent AI Systems through Reactive-Deliberative Constraints
14:45 – 15:00Coffee Break 
15:00 – 15:40Keynote 3 – Dr Lucía Pereira PardoScaling up Heritage Science: AI-assisted processing of spectral images from large-scale collections in archives and libraries
15:40 – 16:20Keynote 4 – Professor Daniel KingProviding a data solution to public, community and voluntary sectors
16:20 – 16:50Collaboration Tables'Meet a Researcher / Meet a Data Expert' Themed Networking
16:50CloseLaunch of NTU Data, Quantitative and Computational Intelligence Network

Location details

Address:

Nottingham Trent University
Pavilion Room 121
Clifton Campus
Nottingham
NG11 8NS

Still need help?

Assoc. Prof. Golnaz Shahtahmassebi (Chair)

Golnaz.Shahtahmassebi@ntu.ac.uk