Department of Computer Science and Technology - Awards and honours

• A Blue Plaque for EDSAC – Cambridge University’s pioneering first computer
  

  A blue plaque was unveiled in this Department today, 23 June 2026, to commemorate the development of EDSAC, a landmark event in the history of modern computing. (See a video of the full unveiling ceremony here.)

  EDSAC - or Electronic Delay Storage Automatic Calculator - was the first electronic computer to go into general use that did not need to be rewired by hand for every new task. Its development marked the birth of everyday computing. 

  EDSAC weighed two tons and took up a whole room at what was then Cambridge University’s Mathematical Laboratory (nowadays the Department of Computer Science and Technology). When it came into operation, in May 1949, it was the first practical machine of its kind: a general purpose digital electronic 'stored-program' computer that could hold both instructions and data in the same memory.

  New fields of science... and Nobel Prizes
  EDSAC was truly groundbreaking: it enabled researchers to do work that had previously been impossible and in so doing, opened up new fields of science. It contributed to three Nobel Prizes in the 1960s and 1970s (for Chemistry, Physiology or Medicine, and Physics, respectively). And its immediate successor, EDSAC 2, was used by Francis Crick and James Watson as they continued their research into DNA, following their discovery of its structure using crystallographer Rosalind Franklin's experimental evidence.

  Though not the first computer built in the UK (Manchester University’s experimental ‘Manchester Baby’ preceded it by 11 months), it was the first fully functional computer to be used practically. And as it was thousands of times faster than the mechanical calculators of the period, EDSAC was immediately put to use to help scientists across the University carry out complex calculations. Real-world problems that had previously been impractical to attempt could now be solved.

  "Every day, billions of people benefit from technologies whose origins can be traced to pioneering computing work carried out in Cambridge."

  Mike Hakata, Cambridge Past, Present and Future

   

  The Blue Plaque to commemorate EDSAC has been created by Cambridge Past, Present and Future. Their Cambridge & District Blue Plaques mark the people and events that have shaped the city and surrounding villages, making history visible in the streets where it happened.

  "I'm absolutely delighted that we're commemorating the EDSAC with a Blue Plaque,” said Professor Alastair Beresford, Head of this Department. "Both the machine and the science it enabled were truly groundbreaking. The legacy of this work can be seen across the Department today, where our staff and students continue to deliver world-class research, actively collaborate with industry, and launch world-changing companies."

  Pioneering computer science in Cambridge 
  Mike Hakata, Chief Executive of Cambridge Past, Present and Future, said: "Every day, billions of people benefit from technologies whose origins can be traced to pioneering computing work carried out in Cambridge. The EDSAC represents a turning point in that story, when computing moved from theory into practical reality. Through our Blue Plaques programme, we aim to connect people with the places, people and ideas that have shaped Cambridge and changed the world. We are delighted to recognise this extraordinary achievement and ensure its story remains visible for future generations."

  EDSAC's creation was led by legendary computer science pioneer Maurice Wilkes (seen above right with EDSAC, during its construction). His work on radar technology during the Second World War gave him the idea for how to create EDSAC's memory. He also benefited from a visit to the USA in 1946 to learn about their world-leading work in computer engineering. The ideas he brought back to Cambridge helped him and his team develop EDSAC and get it into operation in May 1949.

  EDSAC could execute approximately 650 instructions per second. While modern computers operate millions of times faster, in the late 1940s and 1950s EDSAC offered a massive improvement on what was possible at the time. The first computer ever built at the University, it is said to have increased productivity 1,500-fold, transforming scientific research.

  By the standards of today, it was immensely cumbersome to use: researchers had to translate their instructions into a program punched onto paper tape, which was then fed by hand into the machine. And the queue of programs waiting to be run on the computer was no more sophisticated than a washing line, with a series of hooks and clips to hold the tapes.

  Nonetheless, EDSAC was game changing. Ideas about computing that were developed then – such as subroutines – still belong in the basic stock of computing knowledge today. Cambridge computer scientists also contributed to the early development of computer programming languages and operating systems.

  The first in a series of groundbreaking computers
  EDSAC was the first in a whole line of computers created over the years at Cambridge University. Other notable contributions by the Department include working with Acorn on the BBC microcomputer in the 1980s, which, along with an accompanying BBC programme, encouraged huge growth in computing as a hobby. And in the early 21st Century, staff and alumni helped to establish a charity to produce the Raspberry Pi, the best-selling and most successful UK computer of all time.

  Today, Cambridge University’s Department of Computer Science and Technology remains a world leader in its field, conducting pioneering research across many areas of computer science, including computer architecture.

  The EDSAC Blue Plaque will be unveiled today at a special ceremony here. Later this summer, it will be installed on the David Attenborough Building, a University building in the centre of Cambridge where the machine was originally built.

   

• OBE for leader in computing education

  Many congratulations to our colleague Professor Sue Sentance who has been awarded an OBE in the 2026 King’s Birthday Honours! She is recognised for her services to education.

  Sue is a Research Professor in the Department of Computer Science and Technology and Director of the Raspberry Pi Computing Education Research Centre here.

  The Centre, a joint initiative between the University of Cambridge and the Raspberry Pi Foundation, aims to increase our understanding of teaching and learning computing, computer science, and associated subjects, with a particular focus on young people who are from backgrounds traditionally under-represented in computing or who experience educational disadvantage.

  Since being established in 2021, the Centre has rapidly become one of the largest computing education research groups in Europe. Previously Sue was Chief Learning Officer at the Raspberry Pi Foundation from 2018-2023, and in that period played a leading role in the establishment of the DfE-funded National Centre for Computing Education and led the Gender Balance in Computing (GBIC) research project. 

  Sue says: "I am deeply honoured to accept this recognition, which reflects the work of many people across education who support young people learning about computing and technology. I am grateful to have worked with so many talented and passionate colleagues in schools and the research community – including the team at the Raspberry Pi Computing Education Research Centre – who share a commitment to broadening participation in computing education. More than ever, educators, policymakers, and researchers must work together to ensure that all children, everywhere, have access to a high-quality computing education."

  Sue is an experienced educator, researcher and leader in computing education, committed to making computing accessible to learners and teachers globally. Over the last 15 years, she has published widely on the teaching of programming, teacher professional development, physical computing and AI education. She is Chair of the BCS Schools and Colleges Committee and was a member of the Department for Education’s Digital, AI and Technology Task and Finish Group in 2025.  

   In 2024, Sue was awarded the BCS Lovelace Medal for Computing Education, presented annually to recipients for their outstanding contributions to the advancement of computing. Sue received it in recognition of her exceptional contributions and research in computing education, particularly her PRIMM  ('Predict, Run, Investigate, Modify and Make') approach to teaching programming, which has been adopted by teachers globally.

• Royal Society Fellowships honour two Computer Scientists

  

  The Royal Society has today (Wednesday 27 May) honoured two of our colleagues by electing them as Fellows: Professors Anuj Dawar and Srinivasan Keshav. Many congratulations to them both.

  A Royal Society Fellowship is an accolade awarded to pioneers and leaders in their scientific fields. Anuj is a theoretician who has developed new methods to study computational complexity. Keshav is a researcher passionate about using our computational capabilities to tackle climate change and biodiversity loss.

  The Royal Society is the UK’s national academy of sciences and the oldest science academy in continuous existence. Its aim is to recognise, promote and support excellence in science, and to encourage the development and use of science for the benefit of humanity.

  Over 90 outstanding researchers from across the world have this year been elected to the Fellowship of the Royal Society. They work in areas from astronomy and cancer research to mathematics and biotechnology.

  Sir Paul Nurse, President of the Royal Society, said: "I am delighted to welcome this newest group of exceptional scientists to the Fellowship of the Royal Society. Their contributions reflect the highest standards of scientific endeavour.

  "Whether advancing our understanding of vaccines or exploring the transformative potential of mathematics and computation, their work exemplifies the enduring value of curiosity, creativity and rigorous inquiry."

  Anuj Dawar

  Anuj is Professor of Logic and Algorithms here and a Fellow of Robinson College.  A theoretical computer scientist, he has developed fundamental new methods, rooted in mathematical logic, for the study of computational complexity. 

  He is a key figure in the development of symmetric complexity, proving unconditional hardness results for a notion of computation rich enough to express many of the most important algorithms used in combinatorial optimisation.

  Anuj holds a Bachelor's degree from the Indian Institute of Technology (IIT) Delhi, a Master's degree from the University of Delaware and a PhD from the University of Pennsylvania. After working at Swansea University as a postdoctoral researcher and a lecturer, he moved to the University of Cambridge in 1999.

  He served for five years as president of the European Association for Computer Science Logic.  He has also, at various times, chaired the major award committees in theoretical computer science, including the Gödel Prize, the Alonzo Church Award, the Nerode Award, the Ackermann Award and the Barry Cooper Prize.

  "I am honoured to be elected a Fellow of the Royal Society," he says. "It feels wonderful to have my many years of work recognized in this way. This wouldn't have been possible without the many colleagues and collaborators I have had the privilege to work with, especially the brilliant research students and postdocs who have been part of my research group."

  Srinivasan Keshav 

  Keshav is the Robert Sansom Professor of Computer Science here and a Professorial Fellow at Fitzwilliam College. Over four decades, his research has broadened from computer networking to energy informatics and Earth system science, combining mathematical rigour with practical societal benefit. His current work lies broadly at the intersection of computer science and sustainability.

  His doctoral work established the foundations for fairness and flow control in the internet. He subsequently helped to found the academic discipline of energy informatics and shape smart-grid research. He now co-leads the TESSERA project, a foundation model applying self-supervised learning to global Earth observation in support of ecologists, plant scientists, and policy makers.

  Keshav is the author of two widely used graduate textbooks on networking. His honours include the Sakrison Prize, the inaugural Achievement Award from the ACM Special Interest Group in Energy Systems and Informatics, and Fellowships of the Royal Society of Canada, the IEEE, and the ACM.

  "It's a great honour," says Keshav of his election as a Royal Society Fellow. "I am happy that it recognises the area of sustainability and gives an imprimatur of quality to this area of work."

• 'Test of Time' Award for research into why we can't do without passwords

  Passwords are irritating to manage and can be a weak link in security. Yet they still play a key role in protecting our online identities. Now, research explaining why we're still using them and why they're so difficult to replace has won a prestigious award... 14 years after it was first published.

  The Quest to Replace Passwords: A Framework for Comparative Evaluation of Web Authentication Schemes was originally presented at the 2012 Symposium on Security and Privacy run by the IEEE, the world's largest technical professional organisation. 

  The research explored whether there were better tools that were more secure and easier to use and deploy than passwords. But after examining more than 30 proposed replacements, and judging them against the benefits an ideal scheme might provide, the authors' conclusion was a resounding 'no'. 

  At the 2026 Symposium that is taking place today (18 May 2026), the paper was honoured with an IEEE Test of Time Award in recognition of the lasting impact it has had in the field of security and privacy.

  "Not only does no known [password replacement] scheme come close to providing all desired benefits," the authors said in the paper, "none even retains the full set of benefits that legacy passwords already provide."

  The paper has now accumulated over 1700 citations on Google Scholar. And its central argument – that most proposed password replacements fail not because they are insecure, but because they ignore real-world constraints around usability and deployability – has been validated by evidence.

  "Not only does no known scheme come close to providing all desired benefits, none even retains the full set of benefits that legacy passwords already provide."

  Authors Joseph Bonneau, Cormac Herley, Paul C. van Oorschot and Frank Stajano

   

  The authors were Joseph Bonneau (then a PhD student here and now an associate professor at New York University), Cormac Herley (principal researcher at Microsoft Research), Paul C. van Oorschot (professor at Carleton University and a pioneer in graphical password schemes), and Frank Stajano (then a senior lecturer, and now professor of security and privacy, here).

  In search of a password replacement system

  The paper grew out of an earlier project by Frank Stajano. In 2011, he'd designed Pico, a password replacement system intended to provide better usability and security. It was based on per-account public-key pairs managed by a trusted personal device, a design that anticipated the passkey systems that are now finally gaining acceptance in the marketplace.

  As part of his design process, Stajano developed a set of 25 desirable properties for any password replacement system. These included being memoryless, so that users shouldn't have to memorise any secrets, and theft-resistant, so that if a token is stolen, the thief cannot impersonate the user. But when Stajano was writing his paper on it – Pico: no more passwords! – and considering related work, he realised the task really called for a full-length survey. So he assembled a team to do just that.

  Together, the four authors refined and formalised the list of desirable properties for password replacement systems, and also decided early on that deployability should be just as important a concern as security and usability. Having done this, they applied their list of important properties to 35 schemes they had chosen from the literature to represent all the mainstream approaches to user authentication. These ranged from tokens to biometrics to single-sign-on systems.

  Over the following months, through deliberate analysis and weekly debates, they populated their long table of results – and came to a startling conclusion. None of the schemes they'd examined came close to offering all 25 desirable benefits. None even matched the full set of benefits that ordinary passwords already provided.

  Where do replacement schemes go wrong?

  The paper identified precisely where each proposed replacement made trade-offs, and why schemes that looked good on paper had consistently failed to gain adoption. That analysis has held up. Fourteen years on, passwords are far from dead, and specific friction points identified by the paper (such as deployment cost, compatibility with existing infrastructure, and users' resistance to carrying dedicated hardware) are still the obstacles that password alternatives must overcome.

  Part of the paper's lasting influence is practical rather than predictive: the framework proved sufficiently useful and informative that many subsequent papers proposing alternatives to passwords spontaneously adopted it to rate their own systems, making it a de facto standard for the field.

  Further reading

  • An extended version, with full analysis of all 35 schemes, is available here.
  • There is a follow-up paper by the same research team here: Passwords and the evolution of imperfect authentication.
• Celebrating a 'culture of innovation' at our Hall of Fame Awards

  A semiconductor company distinguished for its rapid growth and the important role it plays in the open hardware movement; a research team turning ordinary earbuds into health sensors; an advance in the field of AI-assisted drug discovery; and a tool used by millions of developers to build, share and run software stacks.

  These are the latest winners of our Hall of Fame Awards, which celebrate the 370+ companies started up by current and former members of this Department.

  The 2025 awards were presented on Wednesday 15 April during the annual gathering of the Cambridge Ring, our alumni association. At the event, our Head of Department Prof Alastair Beresford discussed the Department's 'culture of innovation' and reflected that "we have always been defined by a willingness to challenge conventional wisdom and our drive to solve practical problems."

  He added: "We're immensely proud of our tradition of innovation, but we recognise that it's a living thing, sustained by the people in this room. So thank you and congratulations not only to those of you receiving awards tonight, but all our alumni and friends who continue to contribute to our collective success."

  Company of the Year: Rivos

  Semiconductor company Rivos is distinguished for its rapid growth and the important role it plays in the open hardware movement. Since it was founded in 2021 by Mark Hayter, Puneet Kumar and Belli Kuttanna, Rivos has revolutionised high-performance computing by designing GPGPUs and AI accelerators based on the RISC-V open standard. Their 'software-first' approach to silicon allows for seamless integration of heavy LLM workloads, a breakthrough that fuelled their rapid global expansion – including an engineering office in Cambridge. Following a $250M Series A.3 round in 2024, Rivos' industry-leading expertise culminated in an acquisition by Meta in late 2025. The award was collected by Mark Hayter and Tim Ramsdale.

  Product of the Year: auryx for auryx

  Cambridge-based AI health tech start-up auryx redefines wearable technology by turning everyday earbuds into health monitoring devices. It uses advanced AI algorithms and the built-in microphones in earbuds to monitor wearers' vital signs (heart rate, and breathing rate and volume) with unprecedented accuracy. This enables non-invasive health sensing that doesn't require users to change their daily habits.

  auryx’s core technologies are derived from high-impact research publications. Its team (Cecilia Mascolo, the Department’s Professor of Mobile Systems, and two of her former PhD students, Erika Bondareva and Kayla-Jade Butkow) have deep expertise in signal processing and machine learning. This allows the company to deliver robust and reliable physiological sensing using low-cost, widely-available devices. Unlike other approaches, auryx offers a software-only solution. The fact that it doesn't require hardware modification significantly lowers adoption barriers and enables seamless integration with existing earphone products.

  Founded in 2025, over the past year the company has successfully raised funding to further refine its algorithms and advance product development and is in active engagement with industry partners. All three of the team came along to collect their award.

  Better Future Award: David Buterez, Jon Paul Janet, Dino Oglic & Pietro Lio for: 'An end-to-end attention-based approach for learning on graphs'.

  Innovative research conducted in collaboration between a graduate student and the global biopharmaceutical leader AstraZeneca has led to an important advance in the field of AI-assisted drug discovery. As published in Nature Communications in 2025, a novel AI approach has been developed that outperforms existing methods to predict the key properties of molecules and identify promising drug candidates.

  Graph-based AI models have emerged as promising tools for molecular prediction. In his PhD research, conducted in collaboration with AstraZeneca, student David Buterez (pictured right) developed and trained new graph-based AI models on large, real world drug discovery datasets to see if they could make improved predictions about key properties of molecules, which inform their potential in therapeutic applications. Initial results from the research showed ways that resource-intensive drug discovery processes could be optimised to run more efficiently – and even, David says, to "suggest new active compounds that would likely be missed by traditional drug development techniques".

  When he went on to design a new 'Edge Set Attention' model, it set new state-of-the-art results on several molecular benchmarks, outperforming other methods across more than 70 tasks. According to Dino Oglic, Senior Director of Machine Learning & AI at AstraZeneca and a co-author on the paper, "This could accelerate the transition from traditional wet lab work to more sophisticated in silico methods." David Buterez and Prof Pietro Liò collected the award.

  Publication of the Year: Anil Madhavapeddy, David J Scott, Patrick Ferris, Ryan T Gibb, Thomas Gazagnaire for: 'Functional Networking for Millions of Docker Desktops'

  Docker is a developer tool used by millions of developers to build, share and run software stacks. The Docker Desktop clients for Mac and Windows have long used a novel combination of virtualisation and OCaml unikernels to seamlessly run Linux containers on these non-Linux hosts. This paper reflected on a decade of shipping this functional OCaml code into production across hundreds of millions of developer desktops, and discussed the lessons learnt from the researchers' experiences in integrating OCaml deeply into the container architecture that now drives much of the global cloud. It concluded by observing just how good a fit for systems programming the unikernel approach has been, particularly when combined with the OCaml module and type system. David J Scott and Prof Anil Madhavapeddy collected the award.

  There were also three runners-up for the Publication of the Year Award:

  • Joseph Gentle & Martin Kleppmann for: Collaborative Text Editing with Eg-walker: Better, Faster, Smaller
  • Andrew Slattery & Jonathan Sterling for: Hofmann–Streicher lifting of fibred categories  
  • and Anh V Vu, Ben Collier, Daniel R Thomas, John Kristoff, Richard Clayton & Alice Hutchings for: Assessing the Aftermath: the effects of a global takedown against DDoS-for-hire services 
• Student-designed technology aids beekeepers and blind learners
  

  An app that assists beekeepers in identifying sick bees, and an open-source tool to help blind people learn how to program from scratch, were two of the winning Group Design Projects created by second-year students this year. 

  There was also an award for a contribution by students to the challenge of building reliable, open compiler infrastructure that can handle the complexity of modern hardware description languages like SystemVerilog.

  All our undergraduates complete Group Design Projects during their second year. Doing so gives them experience of working on a real software development project and a taste of what it's like to work with professional clients. This year clients ranged from industry to academia and included Nokia Bell Labs, Bending Spoons (the company behind Vimeo, Eventbrite and WeTransfer), Cambridge University Library and the French Space Academy, to name just a few. 

  The projects spanned a wide spectrum of topics. These included creating more energy-efficient homes (for example, through the development of a Draught Detective phone app for builders) as well as helping students manage their finances better through a Wise Banking app.  

  Awards were given in three categories:

  The Most Impressive Technical Achievement Award.
  Runners up were Team Hotel for their project Digging for Data, a project focused on methods of retrieving data from obsolete floppy disks, including data from a collection of papers by former Labour Party leader Neil Kinnock that are held in the archives at Churchill College. The challenge included reverse-engineering texts and tables from the disks.

  The winner was Team Sierra for their compiler infrastructure project System Verilog for CIRCT, which extended the CIRCT-Verilog compiler so that a wider range of 'real world' SystemVerilog examples can be compiled in CIRCT's core MLIR dialects.

  The Most Impressive Professional Achievement Award.
  Runners up were Team Mike for their project Intuitive Business Data, in which they were challenged to create a novel programming tool for business data processing that would be easier for non-technical businesses users to use.

  The Winner was Team Kilo for their project From AI to BI. In this, they worked with the Cambridgeshire Beekeepers Association to create an app that analyses photos of their hives taken by beekeepers and help them detect if their bees are infected by serious diseases like European foulbrood.   

  The Best Contribution to a Better Future Award. 
  Runners up were Team Echo for their project Cold Bridge Diagnostics, which uses computer vision methods to analyse photos of houses and spot 'cold bridges' that are leaking heat from inside the house on winter days.

  The winner was Team Delta for their project on Coding for Blind Learners, which involved creating an open-source tool to help blind people learn to program from scratch in a text-based language.  

  Many congratulations to all the winning teams and everyone who participated.

  • See video presentations of all this year's Group Design Projects here

   

• Google Fellowship highlights 'unloved' AI research field

  A PhD student who would like to encourage more researchers into his – currently under-explored – area of AI research is delighted to have won the support of Google.

  Xiangjian Jiang, who is developing foundational AI models to analyse and understand tabular data (i.e. data stored in tables and spreadsheets) has just been named as a 2025 Google PhD Fellow.

  This prestigious Fellowship will support his studies for the next two years, providing him not only with funding and computational resources, but also connections with other researchers.

  Receiving the two-year Fellowship is a very significant accolade. As Google says, the Fellowships are awarded to "exceptional graduate students pioneering research in computer science and related fields." The goal, it adds, is "supporting the next generation of scientists focused on critical foundational science".

  In Xiangjian's case, the foundational work that he is conducting with his supervisors – Mateja Jamnik, Professor of Artificial Intelligence here, and Nikola Simidjievski, Associate Professor of AI for healthcare at Télécom Paris, Institut Polytechnique de Paris – is in developing entirely new AI models that can understand and reason about data derived not from text or images, but from tables.

  "This work is both timely and important," Prof Jamnik says. "Tabular data is highly under-explored compared to text and images, yet it's central to many real-world applications. For example, we have medical collaborators who are collecting data that goes beyond text and images, including highly dimensional tables derived from patients' genomic profiles, covering around 20,000 genes. Xiangjian is developing solutions to tackle such complex tabular data, including a tabular foundation model that can handle these challenges effectively."

  But it's a demanding challenge and one that requires a step change in the way the AI models are developed.

  This area of research is a bit unloved at the moment, but we hope one day that Large Tabular Models will be as important as Large Language Models.

  Xiangjian Jaing

   

  "A tabular foundation model is not an easy thing to develop," Xiangjian explains. "You can't simply take an existing Large Language Model and adapt it to read a spreadsheet – or apply strategies from analysing textual or image data to analysing tabular data – because there are fundamental differences between the way the information is expressed in these different forms."

  And he is hoping that the Fellowship will really help him make progress in his research as well as fostering broader interest in this field. He is well aware that as an area of research, it’s dwarfed by the size of the research community around Large Language Models (LLMs).

  "It used to be the case that I would reach out to other researchers about our work and ask them to join our research community," he says. "But hopefully now with the impact of the Google Fellowship, it could be the other way around and there may be more people approaching us." He sees this as a highly positive step. "This area of research is a bit unloved at the moment, but we hope one day that Large Tabular Models will be as important as Large Language Models."

  Health and financial data
  Currently, huge amounts of important data are stored in the form of tables, ranging from hospital patients' test results to stock prices on the world’s financial markets. So having AI tools that could analyse and understand the tables and then reason about the data and make predictions would be highly valuable. "In the case of health information, for example," Xiangjian points out, "the model could analyse historic health data about diseases and their treatments and then predict which therapies would lead to a good outcome for a patient."

  Early on in his research, Xiangjian realised "that tabular data is important, and healthcare information is primarily held as tabular data". His father is a doctor, specialising in diabetes, and "diabetes is a good example of a medical condition that is quite hard to diagnose solely from images or textual descriptions. Lots of tests are needed in order to diagnose it and those results are held in the form of tabular data."

  But tabular data is much harder for humans to understand than text or images. "So this is an area where we really need assistance from computers," Xiangjian says. However, it's also hard for AI models currently to process the data from tables, not least because the data is highly heterogeneous.

  As Xiangjian puts it, "the columns in a table might have different types of information in them, or be labelled with different names, and you might be working across a whole range of datasets." So a completely new model is needed.

  Avoiding misleading predictions
  It turns out that you can't ask a Large Language Model that has been trained to read textual data and then predict the next sentence to read a row of data from a table and accurately predict what’s on the next row. "Well, it might come up with a prediction,” Xiangjian laughs, "but it is very likely to provide misleading guidance for practitioners and researchers."

  So how can such a tabular model be developed? Xiangjian is focusing on the causal relationships between the data in a table. "That's what really matters," he explains. "The model needs to understand the underlying relationships between the data. If it can uncover the rules behind the way a world operates, and understand them, then it can understand the world itself."

  The approach he is taking to uncovering these causal relationships is statistical. "We're looking at the real values of a table and trying to discover the causal relationships across different variables through using statistical methods and techniques. Doing this, we have shown that it can help unlock a fundamental learning capability of tabular models.

  Causal relationships
  "And once we've uncovered the causal relations, the model can do a lot of things including reasoning about the data and making predictions. And this could lead to a tabular foundation model."

  Receiving the Google Fellowship is a great boost to Xiangjian's confidence in his research. "Undoubtedly, this Fellowship will help make more people aware of this under-explored domain of work. And for me personally, that feels like great moral support. It's good to know that this field of research matters to other people and not just me."

  His co-supervisor Mateja Jamnik agrees. "I'm very proud he has been awarded the prestigious Google Fellowship," she says. "He's ambitious, creative and technically outstanding in his work and the connections offered through the Google Fellows programme will help broaden his collaborations, his visibility, and ultimately the impact of his research." 

• Professor Emily Shuckburgh appointed Chief Scientific Adviser

  Professor Emily Shuckburgh has been appointed as the new Chief Scientific Adviser at the Department for Energy Security and Net Zero (DESNZ).

  Emily Shuckburgh, Professor of Environmental Data Science here – and Director of Cambridge Zero, Cambridge University's major climate change initiative – will join DESNZ in November. 

  The role of Chief Scientific Adviser is to deliver independent and impartial science and engineering advice to UK ministers and policymakers.

  "It's a great honour to join the Department for Energy Security and Net Zero as Chief Scientific Adviser at a time when scientific evidence is so crucial to informing the UK’s response to the twin challenges of climate change and energy security," Emily said.

  "I warmly congratulate Professor Shuckburgh," University of Cambridge Vice-Chancellor Deborah Prentice said. "Her appointment as Chief Scientific Adviser to the Department for Energy Security and Net Zero recognises not only her outstanding academic leadership in tackling the climate and biodiversity crises, but also the vital role that Cambridge plays in shaping Britain's future."

  Emily was awarded a CBE in the 2025 King's Birthday Honours for the Public Communication of Climate Science and was appointed, alongside two other Cambridge academics, to the DESNZ Science and Technology Advisory Council in July.

  She has acted as an adviser on climate to the UK Government in various capacities, including as a Friend of COP26. Before founding Cambridge Zero in 2019, Emily worked for more than a decade at the British Antarctic Survey where her work included leading a UK national research programme on the Southern Ocean and its role in climate.

  Emily was awarded an OBE in 2016 and is co-author with HM King Charles III and British environmentalist Tony Juniper of A Ladybird Book on Climate Change. She is a mathematician and climate scientist, a Fellow of Darwin College and an alumna of Trinity College, Cambridge.

  She is President-elect of the Royal Meteorological Society, a Fellow of the Cambridge Institute for Sustainability Leadership (CISL), a Fellow of the British Antarctic Survey, a Fellow of the Royal Geographical Society, and an Honorary Fellow of the Energy Institute.

  As well as being Professor of Environmental Data Science in this Department, Emily is also Academic Director of the Institute of Computing for Climate Science (ICCS), co-Director of the Centre for Landscape Regeneration (CLR) and the UKRI Centre for Doctoral Training on the Application of AI to the study of Environmental Risks (AI4ER).

   

   

• Royal Academy of Engineering Fellowship honours Professor of Mobile Systems

  Prof Cecilia Mascolo has just been elected as a Fellow of the Royal Academy of Engineering. She is one of 74 leading figures in the field of engineering and technology to be elected to the Academy Fellowship this year.

  The new Fellows are drawn from every specialism from within the engineering and technology professions and cover sectors ranging from energy and defence to new materials. 

  "They have made exceptional contributions to their field," the Academy says, "pioneering new innovations within academia and business, providing expert advice to government, and fostering a wider comprehension of engineering and technology."

  Cecilia is Professor of Mobile Systems here. She also co-directs the Centre for Mobile, Wearable Systems and Augmented Intelligence here, which focuses on next-generation mobile and wearable technology, as well as mobile applications. 

  In its citation, the Academy says that "Cecilia has contributed fundamental building blocks critical to the successful functioning and adoption of wearable and mobile devices, which have also influenced the scientific methods of other disciplines. Her work on mobile systems for audio diagnostics has led to substantial contributions in the context of respiratory health and on hearable computing for health and fitness."

  Cecilia is a pioneer in devising frameworks to collect sensing data from devices such as phones and wearables with the purpose of developing models to understand behaviour and health. During the pandemic, she and her colleagues developed the COVID-19 Sounds App which collects and analyses short recordings of users coughing and breathing to detect if they are suffering from COVID-19.

  Since then, she has been working on ways to turn the devices we wear – such as earbuds – into mobile monitors that can collect data about our state of health, and developing cutting edge machine learning tools to evaluate that data on the device itself.

  In March this year, Cecilia and two former PhD students (Erika Bondareva and Kayla-Jade Butkow) set up auryx to take this work forward and use machine learning to turn regular existing earbuds into health and fitness sensors, tracking heart rate, HRV, respiration, and advanced cardiovascular parameters.

  Many congratulations to Cecilia on her RAEng Fellowship. 

• A summer of accolades for our researchers

  Research by Department members was honoured by several leading conferences and organisations in August.

  The CHERI project

  There was an award in August for the researchers behind the CHERI ('Capability Hardware Enhanced RISC Instructions') technology. This pioneering cybersecurity technology focuses on new ways to design the architecture of a computer’s central processing unit – its brain – to make software less vulnerable to security breaches.

  The researchers have been particularly interested in increasing memory safety since memory safety bugs in software are repeatedly exploited by hackers to cause major security issues. (Research from Google and Microsoft shows that 70% of ongoing cyber vulnerabilities are memory safety bugs.) The CHERI technology extends conventional architectures and software stacks with novel hardware support for memory protection and secure encapsulation. 

  In August, the Institute of Electrical and Electronics Engineers (IEEE) presented the 2024 Best Paper Award in Security and Privacy to researchers working on the CHERI project. They were recognised for their paper CHERI: Hardware-Enabled C/C++ Memory Protection at Scale. 

  This was the second major IEEE accolade this year for the CHERI researchers. They had also received a 10-year Test of Time Award at the IEEE Symposium on Security and Privacy in May. This was in recognition of the long-term success of their 2015 paper CHERI: A Hybrid Capability-System Architecture for Scalable Software Compartmentalization. 

  Affective Intelligence and Robotics

  Also in August, the IEEE International Conference on Robot and Human Interactive Communication honoured a paper on 'Robot-Led Vision Language Model Wellbeing Assessment of Children'. This work explores how robots powered by Vision Language Models could support the assessment of children's wellbeing, while also reflecting on the potential biases such systems might introduce. (See the pre-print here.) 

  It was a finalist for the Best Paper Award, and won the KROS Interdisciplinary Research Award in Social Human-Robot Interaction.

  The paper was co-authored by researchers in Prof Hatice Gunes' Affective Intelligence and Robotics Lab along with their collaborators in the Cambridge University Department of Psychiatry. 

  Artificial Intelligence

  There was also recognition for Prof Fermín Moscoso del Prado Martín, Associate Professor here of Computational Linguistics.

  Fermín formerly led the AI Team at Alpha (part of Spain's multinational telecomms company Telefónica) where he headed up research and development in affective AI, privacy-preserving AI and explainable AI. At the International Joint Conference on Artificial Intelligence, he and former colleagues from Alpha received the Artificial Intelligence Journal 2025 Prominent Paper Award.

  It honoured their 2021 paper Using Ontologies to Enhance Human Understandability of Global Post-Hoc Explanations of Black-Box Models. This award recognises outstanding papers published within the previous seven years that are "exceptional in their significance and impact".

  Best Artifact Award

  Eric Chun-Yu Peng and Markus Kuhn from the Security Research Group won the Best Artifact Award at the Cryptographic Hardware and Embedded Systems Conference 2025 conference in Kuala Lumpur in mid-September. Their paper – on Adaptive Template Attacks on the Kyber Binomial Sampler – demonstrates a new type of power-analysis side-channel eavesdropping risk that microcontroller implementations of the cryptographic key encapsulation mechanism ML-KEM/Kyber need to be protected against.

  Kyber is the first of a new generation of public-key encryption standards especially hardened against the threat of being broken by future quantum computers. Along with their open-access paper in IACR Transactions on Cryptographic Hardware and Embedded Systems, Peng and Kuhn also published their experimental dataset, along with the Julia code needed for independent researchers to reproduce the results. The award was given for the high standard of reproducibility of their work.

  Many congratulations to all our colleagues on their awards.