The University of Bristol's central hub for data science and data-intensive research, connecting a multidisciplinary community of experts across the University and beyond.
From November 2024 – April 2025, we (the Turing Liaison Team at Bristol) ran a fruitful Turing Seminar Series. This series boasted academics connected to the Turing Institute, speaking about their cutting-edge research in data science and AI.
From Machine Learning, Large Language Models and Digital Twins, to early prediction of dementia, disambiguation in historical texts and evolutionary biology, the range of speaker specialisms reflected the breadth of research at Bristol in this space, reaching academics and early career researchers across the institution.
Audience from Robert Blackwell’s Turing SeminerChristopher Burr’s Turing Seminar
Below are a list of the talks and speakers:
Wednesday 6 November:
Title: Machine Learning and Dynamical Systems meet in Reproducing Kernel Hilbert Spaces
Speaker: Boumediene Hamzi, Marie Curie Fellow, Imperial College London.
Wednesday 20 November:
Title: Trustworthy Digital Twins: designing, developing, and deploying open and reproducible pipelines
Speaker: Chris Burr, Head of the Innovation and Impact Hub, Turing Research and Innovation Cluster for Digital Twins, Alan Turing Institute
Wednesday 4 December:
Title: What can your shopping basket say about your health?
Speaker: Anya Skatova, Senior Research Fellow, Bristol Medical School (PHS)
Wednesday 15 January:
Title: AI-guided tools for early prediction of brain and mental health disorders
Speaker: Zoe Kourtzi, Professor of Computational Cognitive Neuroscience, University of Cambridge
Wednesday 12 February:
Title: Temporal models for Word Sense Disambiguation in historical texts
Speaker: Barbara McGillivray, Lecturer in Digital Humanities and Cultural Computation, Kings College London
Wednesday 26 February:
Title: “If you can’t tell, does it matter?” What should the law say about humanlike AI?
Speaker: Colin Gavaghan, Professor of Digital Futures, Bristol Digital Futures Institute, University of Bristol
Wednesday 12 March:
Title: “Cognition-first evolution”
Speaker: Richard Watson, Professor, (evolutionary biology and computer science), University of Southampton
Wednesday 26 March:
Title: “Big data as propeller for dynamic and time-sensitive service industries: a tourism sector perspective.”
Speaker: Nikolaos Stylos, Associate Professor in Marketing and Digital Innovation, Business School, University of Bristol
Wednesday 9 April:
Title: Can large language models reason about qualitative spatial information?
Speaker: Robert Blackwell, Senior Research Associate, Alan Turing Institute
These seminars have connected external researchers with relevant academics and departments at Bristol, and we have already seen these connections turn into longer-term collaborations. After the talk by Chris Burr, Alan Turing Institute, we organised a workshop between the Alan Turing Institute and the Bristol Digital Futures Institute (BDFI). This workshop provided an insight into digital twin projects run by both institutes, as well as facilitating connections. We took visitors on a tour of BDFI to show the incredible facilities, namely the Reality Emulator – the world’s first large-scale digital twin facility. Staff then went into roundtable discussions delving into shared areas of interest and what a longer-term collaboration could look like.
Over the series, we had 184 internal and external attendees, with 80% feeding back that they found the information / content provided during the event helpful. We are planning on running another series in the 2025-2026 academic year, building on our momentum and further increasing our external and internal networks.
If you have any suggestions of who you would like to see speak as part of next year’s series, please contact Isabelle Halton, Turing Liaison Manager – uob-turing@bristol.ac.uk
You can find out more about Turing events and opportunities at Bristol, including the previous Turing Seminar talks and slides on the Turing web pages.
Dr Leon Danon has been appointed as the new Director of the Jean Golding Institute. Leon is an Associate Professor in Infectious Disease Modelling and Data Analytics in the School of Engineering Mathematics and Technology. He has a PhD in Statistical Physics of Complex Networks but has been working on epidemiology of infectious diseases since 2004. His work combines mathematics, data science and AI with an understanding of behavioural and biological drivers of disease spread to solve pressing problems in public health.
He is Director of Modelling and Data at the Bristol Vaccine centre working with clinicians, immunologists, and statisticians on the epidemiology of vaccine preventable infections.
During COVID-19 he served on SPI-M-O, the modelling subgroup of SAGE, contributing to scientific advice to government on mitigation policies. He was part of the group awarded the Weldon Memorial Prize for this work, as well as the SPI-M-O Award for Modelling and Data Support (SAMDS). He has secured research funding totalling over £25M and continues to work at the science policy interface.
Leon Danon said: “I’m delighted to be joining the Jean Golding Institute as Director. Having been at Bristol since 2021, I’ve had the opportunity to contribute to the University’s vibrant research environment, particularly in infectious disease epidemiology. I’m now very excited to lead the JGI, building on its existing strengths to drive interdisciplinary data science and AI initiatives across a broad range of activity within the University. The JGI is the ideal setting for deepening existing collaborations across faculties and external partners, as well as building new ones, and I’m eager to get started.“
He continued: “I look forward to working with you all to support the continued success and growth of the Institute, and to support the University’s ambitions in high-impact research and innovation, sustainability, industry and policy partnerships, and local engagement, raising our global leadership and reputation.“
Dr Leon Danonwill commence in his role of Director of the Jean Golding Institute on the 1 May 2025.
The new Ask-JGI helpdesk cohort started in September 2024 and have been busy answering queries from researchers across the university! We introduced half of the team in our January blog. Meet the other half of the team below:
Adrianna Jezierska, PhD candidate in in the School of Business
I’m a PhD student at the University of Bristol Business School. My project focuses on social media influencers and their vegan content on YouTube. Using language derived from video transcripts, I analyse to what extent they legitimise veganism so that it becomes popular and desirable in society. Whilst most organisation and management scholars have developed theories based on qualitative data, resulting in small datasets and case study approaches, in my work, I highlight the role of computational social sciences and big data in helping social scientists answer their research questions.
Coming from a social science background, I was initially hesitant about joining the Ask-JGI team. However, this decision has turned out to be the most rewarding and challenging experience. Being part of the team is a continuous learning journey. The questions we receive span various disciplines, often pushing us out of our comfort zones. The most exciting part of the job is the opportunity to communicate with other researchers and receive their positive feedback. On the other hand, we constantly collaborate with other team members and learn from each other, which makes it a very supportive environment. I’m pleased to see more queries from social scientists and humanities researchers. The growing popularity of computational approaches and the shift towards interdisciplinary research is a trend that I find inspiring and exciting
Fahd Abdelazim (he/him) – Ask-JGI PhD Student
Fahd Abdelazim, PhD student on the Interactive AI CDT in the School of Computer Science
I am a PhD student in the Interactive Artificial Intelligence CDT, specializing in model understanding for Vision-Language models. My research focuses on introducing improvements to Vision-Language models that allow for better linking of specific ideas or attributes to physical items, in order to help models recognize and understand the properties of objects in images.
I first heard of the Ask-JGI team through fellow PhD students, and it was recommended to me as a way to apply data science skills to real-world applications. Joining the Ask-JGI helpdesk has been a unique experience where I’ve been able to delve into various domains and learn about topics that I would otherwise not have had the chance to learn about. The team truly values cross-functional collaboration and encourages tackling new challenges and learning on the job.
Working at Ask JGI is incredibly rewarding. I enjoy the diversity of challenges presented by each query which gives me the chance to improve as a data scientist and gain a better understanding of how data science can help improve academic research. I really enjoy the collaborative spirit within the team. The Ask-JGI team are from many different disciplines and interacting with them allows for interesting exchanges of ideas and problem-solving approaches. This allows me to grow not just as a data scientist but as a researcher as well.
Yujie Dai (she/her) – Ask-JGI PhD Student
Yujie Dai, PhD student in the Digital Health and Care CDT
I am a PhD student in the Digital Health and Care CDT, specializing in population health data science. My research focuses on leveraging large-scale real-world health data to address critical challenges in infectious diseases. Specifically, I utilize explainable AI (XAI) techniques to characterize and diagnose diseases, aiming to bridge the gap between data science and public health.
My journey with Ask-JGI began with a recommendation from a friend who was previously part of the team. They spoke highly of the collaborative and dynamic environment, and I was intrigued by the opportunity to apply my skills in real-world research settings. Joining Ask-JGI is an extension of my academic and research pursuits. I was drawn to the idea of supporting researchers across diverse disciplines, helping them navigate technical challenges in their projects, and learning from their different perspectives. The chance to engage with cutting-edge problems and contribute to solutions beyond the scope of my own research was exciting.
There’s so much to love about being part of Ask JGI. I love the variety of work. Each question I encounter presents a new challenge, whether it’s developing a data analysis pipeline, troubleshooting code, or brainstorming creative solutions for a computational problem. The variety keeps me constantly learning and growing as a data scientist. I also love the collaborative atmosphere. Working closely with researchers from different fields gives me diverse ways of thinking and problem-solving. It’s an opportunity to not only apply my skills but also to know more about the scientific community.
Huw Day (he/him) – Ask-JGI Lead
Huw Day, JGI Data Scientist
I am a JGI Data Scientist with a background in mathematics, working on a variety of data science projects with researchers across the university using a variety of data science methodologies and techniques. I also help run the Data Ethics Club.
As Ask-JGI Lead, I am responsible for recruiting, training and the general managing of the Ask-JGI team. They’re a fantastic group and I consider myself really lucky to be able to work with them. I support some of the general queries and I’m also responsible for talking with researchers interested in costing out data science support in grant applications.
To me, the Ask-JGI helpdesk is based on the idea that any researcher who wants to do data science should be empowered to do so. Whilst we often do the data science for people, I think the most rewarding outputs from our helpdesk is when we empower researchers to do data science themselves, guiding and validating their work. It’s also a wonderful opportunity for myself and the rest of the helpdesk to learn about research across the university.
All University of Bristol researchers (including PhDs) are entitled to a day of free data science support from the Ask-JGI helpdesk. Just email ask-jgi@bristol.ac.uk with your query and one of our team will get back to you to see how we can support you.
If you’re a PhD student interested in joining the Ask-JGI team, we will do recruiting for the next academic year in summer of 2025 so keep an eye on the JGI mailing list for when we have our recruiting call. We recruit a new cohort every year but do not accept speculative applications outside of the recruiting call.
We are delighted to announce a new pilot training scheme led by our newly-appointed JGI Research Data Science Advocates. This is a new way to take part in training in a low-stress, collaborative and supportive environment, and at the same time form a community of data scientists in your area.
The pilot will run JGI training events over a whole week in Schools, supported by a local Data Science Advocate. They will run sessions to support a cohort to undertake the training together, over the course of a week. The formal training takes only around 2-3 hours to complete, but it is anticipated that this format will allow deeper learning and more useful application to research.
To take part in the pilot (which is aimed at relatively inexperienced coders within a discipline), please email to jgi-training@bristol.ac.uk. If your school doesn’t have a volunteer, you would be welcomed at a research-adjacent community. Bios for our Advocates are below and even if you don’t need this particular training, they would love to include you in an ongoing data science community, so please get in touch.
Ruolin Wu
I am a PhD student of paleobiology diving into the mysteries of evolutionary history. Armed with code, fossils, and molecular data, I craft stories about topological and temporal pattern of animals and plants. Outside of academia, I like climbing, handcrafts, succulents and ferns of any kind.
Zhiyuan Xu
I am a 1st year PhD student focusing on data science and artificial intelligence, with a particular focus on large language models and their applications. My background includes experience in machine learning, data-driven research, and interdisciplinary collaboration to address complex problems.
Bryony Clifton
I’m a PhD student in Biochemistry, studying the molecular details underpinning neurotransmission. My project focuses on identifying the biological role for an uncharacterised intramembrane protease found in the human brain. During my PhD, I have become aware of the importance of developing tools to present complex datasets in a clear and informative way. I am excited to begin my role with the JGI where I can support others to build these skills too.
Catherine Upex
I’m Catherine and I’m a first year PhD student based in the medical school. I’m using data science and AI to understand the shape and movement patterns of the heart over different disease states. I’m also currently working on a mini-project using AI protein folding tools, like AlphaFold, and computer simulations to uncover interactions between synthetic cannabinoids and the hERG potassium channel and its relation to arrythmia risk.
Kaan Deniz
Aerospace Engineer who has intensive industrial experience in numerical modelling with a MSc degree from the University of Bristol/ Aerospace Engineering. Current PhD student in Aerospace Engineering at the University of Bristol. Research focus is numerical modelling of composite manufacturing processes.
Boy Li
I study how to synergize domain-specific knowledge with data-driven deep learning models to extract information from remote sensing imagery.
Vaishnudebi Dutta
I am an Engineering Mathematics PhD student working on model and data-driven design of combination therapies for non-small cell lung cancer. Beyond my research, I serve as the School of Engineering Mathematics and Technology (SEMT) PhD Student Representative, advocating for and supporting the academic community. I also hold a key position as the PhD Representative for the Bristol Cancer Research Network where I get the opportunity to share research updates to Clinicians, and others in the network. Additionally, I manage the network’s official X (formerly Twitter) presence, helping to disseminate research developments and maintain engagement with the broader scientific community.
Zhengzhe Peng
I am a PhD student with a diverse background in computer science, business, and over a year of IT work experience. My research applies advanced data science methods, with a focus on AI, to explore real-world challenges. I am dedicated to expanding my knowledge in these fields and eager to help others who are new to data science, working together to advance and explore new possibilities in this ever-evolving domain.
Winfred Gatua
Winfred Gatua is a PhD Fellow at the University of Bristol, specializing in Molecular Genetics and Life Course Epidemiology. Her research focuses on the triangulation of evidence between Mendelian randomization and randomized controlled trials for complex diseases. She holds an MSc in Bioinformatics, a Postgraduate Diploma in Health Research Methods, and a BSc in Biomedical Science and Technology. Transitioning from wet lab biomedical sciences to dry lab bioinformatics, Winfred is a self-taught coder passionate about open science, automation, and reproducible research in genetics. Beyond research, Winfred is dedicated to capacity building, particularly in increasing computational and data literacy among non-computer science researchers. Since 2021, she has been a volunteer instructor with The Carpentries, securing funding, hosting and instructing carpentries lessons that equip researchers with essential skills in data analysis, open science, reproducible research and best practices in scientific computing in different institutions across the globe.
Our Turing Liaison team recently funded a number of PhD students to go to the 2024 Alan Turing PhD Connect Conference. This is one of the range of approaches we are taking to bridging the gap between the Turing’s goals and the University’s research and academics who reflect these goals.
Attendees at a PhD Connect conference. Photo provided by Jingrong Bai.
Supporting PhD students to make connections and discover new collaborations through the Turing will hugely benefit students and the wider data science and AI community, and is an important part of our objective. Below are some statements from the students we funded about their experience at the conference.
Damien Wang
Damien Wangat a poster session at PhD Connect.
I am Damien, a first-year PhD student from University of Bristol and SWDTP who specializing in psychology and artificial intelligence. The past two days at PhD Connect 2024 have been incredibly fulfilling. I had the opportunity to explore a wide range of PhD projects in AI and data science, engaging in discussions with other attendees and collaboratively tackling problems by leveraging our diverse backgrounds.
Conversations with peers and insights from the panel discussions were truly enlightening. I was also fortunate to represent my group during the Mini-DSG session and deliver my own poster presentation. These experiences have boosted my confidence and skills in presenting, and I’m grateful for the valuable feedback I received on my research.
This two-day journey has inspired me to push forward with even greater motivation. A heartfelt thanks to the Alan Turing Institute and everyone I met along the way!
Ming Chen
Ming Chen (left) and Michael Rumbelow (right) attending a drinks reception at PhD Connect.Ming Chen (centre) attending a session at PhD Connect.
The PhD Connect 2024 conference was an incredible opportunity to engage with peers, learn from industry experts, and explore real-world applications of data science and AI. My research interests include learning sciences and emerging technologies in language learning. I would say that one of the highlights for me was participating in group research discussions, which broadened my understanding of AI’s role in addressing societal challenges.
I also appreciated the networking opportunities and the chance to discuss my research with fellow attendees and professionals from diverse sectors. Another interesting part of the conference is the Research Karaoke, which is a great experience for people to have fun and practise doing presentations.
Jizhao Niu
Left to right: Yunwen Zhou, Jizhao Niu, Kerstin Nothnagel, and Michael Rumbelow.
I am grateful to The Jean Golding Institute for funding my attendance at the conference. It was a fantastic opportunity to meet many PhD students from Bristol and beyond, engaging in discussions on health sciences-related projects.
A highlight for me was the training session on how to pitch research effectively, which provided valuable insights and practical skills. We worked as a team to sell an item to other groups, which was both enjoyable and educational.
I learned the importance of tailoring research presentations to audiences with diverse backgrounds — a skill I look forward to applying in the future!
Jingrong Bai
During the conference, we got insightful points on AI-human by Piotr Mirowski from DeepMind. Then, we interacted with the group work and presented karaoke, which was good for us to connect with other PhD students across the UK, also, learned how to prepare a good presentation by Beatriz Costa Gomes. Last but not the least, we shared our research ideas through the poster session. All in all, it is a valuable experience for me to know the AI field and meet all of the awesome people, really appreciate all of the speakers, organizers and students.
Jingrong Bai (second on the left) with other PhD students at a networking session.Jingrong Bai (left) discussing the posters on display with other attendees.
Zia Saylor
Zia Saylor (left), Kerstin Nothnagel (centre) and Michael Rumbelow (right) at PhD Connect.
Perhaps my favorite session was the one on day 2 morning of the conference when we discussed the principles of a good academic presentation. Focusing on basics like practice, maintaining relevancy to the audience, and ensuring that materials were packaged in an alluring way were key methods discussed. Looking at the AI aspect of our learning opportunities, much of the conference consisted of hands-on opportunities to engage with the materials, from designing a workflow that would integrate AI into academia without infringing on the rights and words of academics to developing a mechanism to integrate data on building pricing into an AI cost estimation algorithm that could be made. This enabled us as students to learn more about AI in its many forms and potential for interdisciplinary applications.
Jay Liu
It has been a wonderful journey for me to attending the 2024 Alan Turing AI PhD Conference at Horizon Leeds. It is my first time travelling to Leeds, a fantastic city with fancy malls and restaurants. I am grateful for the great opportunity and generous funding for the program!
I am a PhD student in Finance at the University of Bristol Business School, focusing on understanding the effects of AI and algorithmic decision making in the financial markets. I believe the conference can further improve my understanding on AI and the application of AI on interdisciplinary research!
Jay Liu standing in front of a digital screen at PhD Connect.Alan Turing Institute tote bag and Jay Liu’s name badge for PhD Connect.
Zhengzhe Peng
Session from PhD connect with multiple speakers.
Attending the PhD Connect Conference organized by the Alan Turing Institute was an enriching experience. I particularly appreciated the diverse perspectives shared during interdisciplinary discussions on data science applications. The keynote sessions inspired new ideas for integrating AI into my research, while the networking opportunities allowed me to connect with peers tackling similar challenges. I gained valuable insights into emerging methodologies and practical approaches that will enhance my PhD work.
Boyang Yu
This conference let me engage with the Mini-data group to explore data science applications in real-world challenges, which is what I’m doing as a PhD. I enhanced my presentation skills and learned to communicate complex ideas to a broader audience, inspired by a standout example from the presenter (Dr Beatriz Costa Gomes). I saw some very nice posters and great to have a picture with one of my most favourite poster (and its owner).
Damien Wang (left) and Boyang Yu (right) at a poster session at PhD Connect.Beginning of the day outlining the agenda.
Ding Li
Attending the 2024 Turing Phd connect conference is such an unforgettable experience. I have met a bunch of bioinformatics students from various universities and institutions sharing their research with AI and Machine Learning. The poster and presentation session left me with impression on how research from other fields could help with my own PhD project. During the session, I discussed with Mr Muizz who is also from University of Bristol, but another school of Engineering Mathematics, and heard about how he applied AI on topology of insects’ wings in traditional species classification and phylogeny. It would never happen if there were no such an opportunity.
Ding Li (Left) listening to talks given by data scientist Dr Piotr Mirowskifrom Google Deepmind.Ding Li attending the poster session and discussing with the presenters on their research.
Kerstin Nothnagel
Attending the Alan Turing Institute PhD Connect Conference was an incredible experience. Highlights included Dr Piotr Mirowski’s inspiring keynote on human-machine collaboration and the ‘Mini Data Study Group,’ where we tackled real-world challenges like ICU surge prediction and cancer forecasting.
This event was a perfect prelude to my upcoming ATI funded UK-Italy Trustworthy AI Visiting Researcher Programme in Milan, where I’ll collaborate with global researchers to explore ‘Global AI Policies and Regulations and Their Impact on Healthcare.’ The project is reinforced by the importance of unifying AI policies to ensure technology benefits everyone equally, closing economic gaps rather than widening them.
