School of Computing Science

Events

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Explore upcoming seminars, guest lectures, workshops, and other events hosted by the School of Computing Science.

Our events bring together students, researchers, industry partners, and the wider community to share ideas, showcase research, and foster collaboration.

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This Week’s Events

NetLLM: Adapting Large Language Models for Networking

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Bikram Singh Deol
Date: 12 February, 2026
Time: 10:00 - 11:00
Location: F121 Lilybank Gardens and Online

Many networking tasks now employ deep learning (DL) to solve complex prediction and optimization problems. However, current design philosophy of DL-based algorithms entails intensive engineering overhead due to the manual design of deep neural networks (DNNs) for different networking tasks. Besides, DNNs tend to achieve poor generalization performance on unseen data distributions/environments.

Motivated by the recent success of large language models (LLMs), this work studies the LLM adaptation for networking to explore a more sustainable design philosophy. With the powerful pre-trained knowledge, the LLM is promising to serve as the foundation model to achieve "one model for all tasks" with even better performance and stronger generalization. In pursuit of this vision, we present NetLLM, the first framework that provides a coherent design to harness the powerful capabilities of LLMs with low efforts to solve networking problems. Specifically, NetLLM empowers the LLM to effectively process multimodal data in networking and efficiently generate task-specific answers. Besides, NetLLM drastically reduces the costs of fine-tuning the LLM to acquire domain knowledge for networking. Across three networking-related use cases - viewport prediction, adaptive bitrate streaming and cluster job scheduling, we showcase that the NetLLM-adapted LLM significantly outperforms state-of-the-art algorithms.

Meaningful Human-in-the-Loop Checking of GenAI Synthesis

Group: School of Computing Science
Speaker: Shriram Krishnamurthi, Brown University
Date: 13 February, 2026
Time: 16:00 - 17:00
Location: 422 Sir Alwyn Williams (SAWB), University of Glasgow

Meaningful Human-in-the-Loop Checking of GenAI Synthesis

 

Developers routinely use GenAI tools to generate useful components of programs, such as regular expressions. While pleasant and often effective, this can easily lead to subtle bugs. The developer may have been unclear in their specification, they may not fully understand the language of the output, there may be systematic misconceptions suffered by the user and perhaps even embedded in the language model, and so on.

 

Responsible use of GenAI, therefore, requires humans to be in the loop. To be effective, however, the human’s interaction must be both meaningful and moderate. What methods can we use to achieve this?

 

We have designed a process that weds formal language theory to cognitive science to help with this process. We have applied it to three formal languages: regexps, linear temporal logic, and access-control policies. We show through experiments that this is a significant improvement over showing users the candidate expressions, and also helps catch situations where no output is a match.

 

The case of LTL is especially interesting, because it showcases a rich methodology (that can also be applied broadly) of how to actually harness human misconceptions in the middle of this process. That same knowledge also lends itself well to building other materials, such as novel forms of adaptive tutoring systems. Therefore, this material also connects well to people interested in computing education.

Upcoming events

NetLLM: Adapting Large Language Models for Networking

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Bikram Singh Deol
Date: 12 February, 2026
Time: 10:00 - 11:00
Location: F121 Lilybank Gardens and Online

Many networking tasks now employ deep learning (DL) to solve complex prediction and optimization problems. However, current design philosophy of DL-based algorithms entails intensive engineering overhead due to the manual design of deep neural networks (DNNs) for different networking tasks. Besides, DNNs tend to achieve poor generalization performance on unseen data distributions/environments.

Motivated by the recent success of large language models (LLMs), this work studies the LLM adaptation for networking to explore a more sustainable design philosophy. With the powerful pre-trained knowledge, the LLM is promising to serve as the foundation model to achieve "one model for all tasks" with even better performance and stronger generalization. In pursuit of this vision, we present NetLLM, the first framework that provides a coherent design to harness the powerful capabilities of LLMs with low efforts to solve networking problems. Specifically, NetLLM empowers the LLM to effectively process multimodal data in networking and efficiently generate task-specific answers. Besides, NetLLM drastically reduces the costs of fine-tuning the LLM to acquire domain knowledge for networking. Across three networking-related use cases - viewport prediction, adaptive bitrate streaming and cluster job scheduling, we showcase that the NetLLM-adapted LLM significantly outperforms state-of-the-art algorithms.

Meaningful Human-in-the-Loop Checking of GenAI Synthesis

Group: School of Computing Science
Speaker: Shriram Krishnamurthi, Brown University
Date: 13 February, 2026
Time: 16:00 - 17:00
Location: 422 Sir Alwyn Williams (SAWB), University of Glasgow

Meaningful Human-in-the-Loop Checking of GenAI Synthesis

 

Developers routinely use GenAI tools to generate useful components of programs, such as regular expressions. While pleasant and often effective, this can easily lead to subtle bugs. The developer may have been unclear in their specification, they may not fully understand the language of the output, there may be systematic misconceptions suffered by the user and perhaps even embedded in the language model, and so on.

 

Responsible use of GenAI, therefore, requires humans to be in the loop. To be effective, however, the human’s interaction must be both meaningful and moderate. What methods can we use to achieve this?

 

We have designed a process that weds formal language theory to cognitive science to help with this process. We have applied it to three formal languages: regexps, linear temporal logic, and access-control policies. We show through experiments that this is a significant improvement over showing users the candidate expressions, and also helps catch situations where no output is a match.

 

The case of LTL is especially interesting, because it showcases a rich methodology (that can also be applied broadly) of how to actually harness human misconceptions in the middle of this process. That same knowledge also lends itself well to building other materials, such as novel forms of adaptive tutoring systems. Therefore, this material also connects well to people interested in computing education.

The Computational Intractability of Not Worst Responding

Group: Formal Analysis, Theory and Algorithms (FATA)
Speaker: Edwin Lock, King’s College London
Date: 17 February, 2026
Time: 15:00 - 16:00
Location: Room 422, SAWB

It is well-known that deciding, finding, and counting Nash equilibria in succinctly represented games is computationally hard. We ask whether weakening optimality to merely requiring each player to avoid worst responses - the weakest meaningful rationality criterion - yields tractable solution concepts. It does not. Any solution concept with this minimal universal rationality guarantee is "as intractable" as pure Nash equilibrium. For general games, deciding existence of a not-worst-response outcome is NP-complete, finding one is NP-hard, and counting them is #P-complete. For potential games, the search problem is PLS-complete. These results hold even when the number of actions per player is fixed.

Computational hardness thus does not stem from optimization but rather from requiring guarantees for all players. We identify a sharp threshold: the problem of finding an outcome where a fraction alpha of players play one of their top fraction beta actions is in RP (i.e., tractable subject to a small error probability) if alpha<=beta, and NP-hard (i.e., intractable) if alpha>beta. This implies that finding outcomes where almost nobody worst-responds is tractable, while finding outcomes where any positive fraction of players best-respond is intractable. Finally, the associated search and counting problems are NP-hard and #P-hard, respectively.

From AI Algorithms and Software to AIware

Group: Systems Seminars
Speaker: Tao Chen, University of Birmingham
Date: 19 February, 2026
Time: 14:00 - 15:00
Location: Room 422, Sir Alwyn Williams Building and Zoom

Software is eating the world, but AI is eating the software. Indeed, AI is now an integral part of software engineering (SE) research, and it may not be long before the synergy between AI and SE becomes a dominant field. However, this raises a big question: what role does AI play in SE? In this talk, through an overview of the recent works from my group, I will go through the three stages of AI and SE: “using/specialising” AI for SE tasks (AI for SE); “questioning” the relationship between AI and SE (SE for AI); and possibly “changing” the synergy thereof. What I advocate is that SE problems are not only an application area of AI while SE or AI methods alone cannot fully address the true problems in AI applications, rather, both SE and AI should be part of the problem and solution.
 
Dr. Tao Chen is an Assistant Professor in the School of Computer Science, University of Birmingham, where he leads the Intelligent Dependability Engineering for Adaptive Software (IDEAS) group. His main research interests are the synergy between AI and Software Engineering, particularly related to the dependability of software systems. He has published over 70 peer-reviewed papers in the relevant fields. Dr. Chen serves/has served as the Associate Editor for ACM TAAS; the Publicity Chair for IEEE SERVICES'17, and the PC member for many major conferences (2018-now), such as ICSE, FSE, ASE, and GECCO. Together with his students/collaborators, his works have been included in the ACM SIGSOFT Empirical Standards for Software Engineering, received the best paper award from SEAMS, and received the Kaivalya Dixit Award from SPEC. His research has been funded by UKRI and DSTL. 

Embodied Harassment in Social VR: Challenges, Solutions, and Future Directions

Group: Human Computer Interaction (GIST)
Speaker: Guo Freeman, Human-Centered Computing Division, School of Computing, Clemson University
Date: 23 February, 2026
Time: 10:00 - 11:00
Location: 423 SAWB

Abstract
The growing popularity of commercial social VR platforms such as VR Chat, RecRoom, and Meta Horizon Worlds is dramatically transforming how people meet, interact, play, and collaborate online. Unlike in traditional online social spaces, where one’s social interactions are mediated by a screen, social VR arguably offers heightened social experiences through a unique combination of partially or fully body-tracked avatars, synchronous voice conversations, and simulated touch and grab features. These novel characteristics have led to varied safety issues, including intensified and more physicalized forms of online harassment. In this talk, Professor Guo Freeman will introduce her multi-year research on challenges in understanding and effectively mitigating “embodied harassment” in social VR. She will also explain her ongoing work on developing nuanced sociotechnical solutions to address such harassment and highlight future directions to explore the evolution of these risks, which can transmit outside social VR and cause even broader damage.

Bio
Dr. Guo Freeman is a Dean’s Associate Professor in Human-Centered Computing at Clemson University in the United States. At Clemson, she directs the Gaming and Mediated Experience Lab (CUGAME). Her work focuses on how interactive technologies such as multiplayer online games, live streaming, social VR, and generative AI shape interpersonal relationships and group behavior. She has authored over 130 peer-reviewed publications and won 15 Best Paper or Honorable Mentions Awards (top 3%-5%). She has secured $30 million in external grant funding from the US National Science Foundation (NSF), the US Army, and the Air Force Office of Scientific Research, and was awarded the Clemson University College of Engineering, Computing, and Applied Sciences (CECAS) Junior Researcher of the Year in 2023

TBC

Group: Systems Seminars
Speaker: Tom Spink, University of St. Andrews
Date: 24 February, 2026
Time: 14:00 - 15:00
Location: Room 422, Sir Alwyn Williams Building and Zoom

TBC

SICSA Seminar - From Large to Small: Building Affordable Language Models with Limited Resources

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 25 February, 2026
Time: 16:00 - 17:00
Location: https://sicsa.ac.uk/event/sicsa-seminar-20260225-burcu-can/

Register to attend Join us on Wednesday, 25 February for an AI & Data Science Seminar. Dr Burcu Can of University of Stirling presents From Large to Small: Building Affordable Language Models with Limited Resources This talk aims to question the limitations and harms of Large Language Models, followed by a review of Small Language Models, covering prominent examples, their key techniques, and their capabilities. It will also give an overview of even smaller ‘baby’ language models. Finally, the talk will conclude by presenting some recent studies in which we developed baby language models using very small amounts of data.

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Anthony Rainey
Date: 26 February, 2026
Time: 10:00 - 11:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

TBC

Group: Systems Seminars
Speaker: Youssef Moawad, University of Glasgow
Date: 03 March, 2026
Time: 12:00 - 13:00
Location: Room 422, Sir Alwyn Williams Building and Zoom

TBC

TBC

Group: Systems Seminars
Speaker: Xiangmin XU, University of Glasgow
Date: 10 March, 2026
Time: 14:00 - 15:00
Location: Room 422, Sir Alwyn Williams Building and Zoom

tbc

Pallas: A Data-Plane-Only Approach to Accurate Persistent Flow Detection on Programmable Switches in High-Speed Networks

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Weihe Li, University of Edinburgh
Date: 12 March, 2026
Time: 12:00 - 13:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

Abstract:

In high-speed data center networks, persistent flows are repeatedly observed over extended periods, potentially signaling threats such as stealthy DDoS or botnet attacks. Monitoring every flow in production-grade hardware switches that feature limited memory, however, is challenging under typical high flow rates and data volumes. To tackle this, approximate data structures, like sketches, are often employed. Yet many existing methods rely on per-time-window flag resets, which require frequent control-plane interventions that make them unsuitable for high-speed traffic. This paper introduces Pallas, a fully data-plane-implementable sketch for detecting persistent flows in high-speed networks with high accuracy, obviating the need for time-window-based resets. We further propose Opt-Pallas, an enhanced variant of Pallas that improves detection accuracy by incorporating flow arrival patterns. We present a rigorous error bound analysis for both Pallas and Opt-Pallas, along with extensive performance evaluations using a P4-based prototype on an Intel Tofino switch. Pallas scales persistent flow detection to line-rate capacity, while state-of-the-art solutions fail to operate beyond a few Mbps. Our results show that Pallas and Opt-Pallas can accurately detect persistent flows in traffic volumes over 60× higher than those handled by the best existing approach. Additionally, even under low-speed traffic, Pallas and Opt-Pallas achieve 4.21% and 7.85% higher lookup accuracy while consuming only 8.5% and 9.7% of switch resources, respectively. Extensive trace-driven results on a CPU platform further validate the high detection accuracy of Opt-Pallas compared to existing methods.

Bio:

Weihe Li is a postdoctoral researcher at the University of Edinburgh. He received his Ph.D. in Informatics from the University of Edinburgh in 2025. His research focuses on the design of approximate data structures for fast and accurate flow detection in high-speed networks, with an emphasis on practical deployment on programmable switches. His first-author work has appeared in top-tier venues, including ACM SIGMOD 2025, ACM WWW 2024 and 2025 (Best Student Paper Award, 2024), IEEE ICNP 2025, IEEE/ACM Transactions on Networking (ToN), and IEEE Transactions on Computers (TC). He has also conducted research in related networking areas, including video streaming and load balancing in data center networks.

HRI 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 16 March, 2026
Time: 00:00 - 00:00
Location: TBA

The ACM/IEEE International Conference on Human-Robot Interaction (HRI) is the premier venue for innovations on human-robot interaction. Sponsored by the ACM special interest groups on computer-human interaction (SIGCHI) and artificial intelligence (SIGAI) as well as the IEEE robotics and automation society (RAS), HRI brings together researchers spanning robotics, human-computer interaction, human factors, artificial intelligence, engineering, and social and behavioral sciences. The theme of the 21st edition of HRI is HRI Empowering Society. Our field has the potential to bring about positive change in many areas of our societies such as healthcare, transport, remote working, agriculture and industry. However, this change cannot happen if we do not engage properly with the end users who will potentially utilize robots in their jobs and daily lives. For this reason, HRI 2026 will focus on: 1) how we can ethically integrate robots in everyday processes without creating disruptions or inequalities, carefully thinking at the future of work and services; 2) how we can make them accessible to the general public (in terms of design, technical literacy and cost) with the final aim to make robots more willingly adopted as technological helpers. More information is available on the HRI 2026 website

(Backup) Pallas: A Data-Plane-Only Approach to Accurate Persistent Flow Detection on Programmable Switches in High-Speed Networks

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Weihe Li, University of Edinburgh
Date: 26 March, 2026
Time: 10:00 - 11:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

Abstract:

In high-speed data center networks, persistent flows are repeatedly observed over extended periods, potentially signaling threats such as stealthy DDoS or botnet attacks. Monitoring every flow in production-grade hardware switches that feature limited memory, however, is challenging under typical high flow rates and data volumes. To tackle this, approximate data structures, like sketches, are often employed. Yet many existing methods rely on per-time-window flag resets, which require frequent control-plane interventions that make them unsuitable for high-speed traffic. This paper introduces Pallas, a fully data-plane-implementable sketch for detecting persistent flows in high-speed networks with high accuracy, obviating the need for time-window-based resets. We further propose Opt-Pallas, an enhanced variant of Pallas that improves detection accuracy by incorporating flow arrival patterns. We present a rigorous error bound analysis for both Pallas and Opt-Pallas, along with extensive performance evaluations using a P4-based prototype on an Intel Tofino switch. Pallas scales persistent flow detection to line-rate capacity, while state-of-the-art solutions fail to operate beyond a few Mbps. Our results show that Pallas and Opt-Pallas can accurately detect persistent flows in traffic volumes over 60× higher than those handled by the best existing approach. Additionally, even under low-speed traffic, Pallas and Opt-Pallas achieve 4.21% and 7.85% higher lookup accuracy while consuming only 8.5% and 9.7% of switch resources, respectively. Extensive trace-driven results on a CPU platform further validate the high detection accuracy of Opt-Pallas compared to existing methods.

Bio:

Weihe Li is a postdoctoral researcher at the University of Edinburgh. He received his Ph.D. in Informatics from the University of Edinburgh in 2025. His research focuses on the design of approximate data structures for fast and accurate flow detection in high-speed networks, with an emphasis on practical deployment on programmable switches. His first-author work has appeared in top-tier venues, including ACM SIGMOD 2025, ACM WWW 2024 and 2025 (Best Student Paper Award, 2024), IEEE ICNP 2025, IEEE/ACM Transactions on Networking (ToN), and IEEE Transactions on Computers (TC). He has also conducted research in related networking areas, including video streaming and load balancing in data center networks.

Pre-CHI Day 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 01 April, 2026
Time: 10:00 - 15:00
Location: Stirling Court Hotel, University of Stirling, Airthrey Rd, Stirling, FK9 4LA

The ACM CHI conference is the premier publication venue in the field of HCI, and Scotland-based researchers are contributing extensively to the programme for the 2026 conference which will be held in Barcelona, Spain in mid-April. The Pre-CHI Day is a chance for the Scottish HCI community to see some of the world-leading research going on across Scotland, and allow those not travelling to Spain to talk to authors first-hand and hear about their work. Over the day, we will have presentations from ACM CHI 2026 full paper authors, with the potential for also having a poster or interactivity session as well (depending on numbers). The event will be hybrid, and virtual attendance and virtual presentation will both be supported. We expect a mixed audience, including researchers of the Scottish HCI community as well as interested students, designers, industry, practitioners etc., as well as newcomers to the field of HCI. Register by 31 March to attend in-person or onlin Submit a paper or poster by 22 March to be included in the programme.

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: TBC
Date: 09 April, 2026
Time: 11:00 - 12:00
Location: Lilybank Gardens, F121 Conference Room

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: TBC
Date: 23 April, 2026
Time: 11:00 - 12:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

SICSA Writing Retreat 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 27 April, 2026
Time: 15:00 - 14:00
Location: Scottish Centre for Ecology and the Natural Environment (SCENE), G63 0JS

The 2026 SICSA Writing Retreat will bring together researchers from across Scotland for a two-day intensive writing event. The programme will consist of networking and skill sharing activities, in addition to individual and group writing blocks. Postdoctoral researchers from any SICSA institution are invited to apply to attend the writing retreat by completing the online form by 1 February 2026. Spaces are very limited and the SICSA Directorate will be judging applications based on clear and achievable writing plans, quality outputs and benefits to both individual researchers and wider groups. Proposals that involve and benefit multiple SICSA institutions are particularly encouraged. Apply Date Start: 15:00 Monday 27 April 2026 Finish: 14:00 Wednesday 29 April 2026 Location Scottish Centre for Ecology and the Natural Environment (SCENE)

SICSA Writing Retreat 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 27 April, 2026
Time: 15:00 - 14:00
Location: Scottish Centre for Ecology and the Natural Environment (SCENE), G63 0JS

The 2026 SICSA Writing Retreat will bring together researchers from across Scotland for a two-day intensive writing event. The programme will consist of networking and skill sharing activities, in addition to individual and group writing blocks. Postdoctoral researchers from any SICSA institution are invited to apply to attend the writing retreat by completing the online form by 1 February 2026. Spaces are very limited and the SICSA Directorate will be judging applications based on clear and achievable writing plans, quality outputs and benefits to both individual researchers and wider groups. Proposals that involve and benefit multiple SICSA institutions are particularly encouraged. Apply Date Start: 15:00 Monday 27 April 2026 Finish: 14:00 Wednesday 29 April 2026 Location Scottish Centre for Ecology and the Natural Environment (SCENE)

Theory Day 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 07 May, 2026
Time: 01:00 - 01:00
Location: University of Strathclyde, United Kingdom

Join us on 7 May 2026 for Theory Day, bringing together researchers from across Scotland working on Theory and adjacent topics. Staff and students are encouraged to register and submit a proposal to be included in the programme.

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: TBC
Date: 07 May, 2026
Time: 11:00 - 12:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: TBC
Date: 21 May, 2026
Time: 11:00 - 12:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

Scottish Argumentation Day 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 29 May, 2026
Time: 01:00 - 01:00
Location: University of Dundee

Scotland has a particularly high concentration of research groups working in the AI subfield of computational argumentation. Scottish Argumentation Day has previously been attended by researchers based both in Scotland and further afield, and has enabled the Scottish argumentation community to present their work in an informal setting, share feedback, and strengthen professional links. SAD began with Aberdeen 2011, and most recently took place in Edinburgh 2024. In continuing this series, our aim is threefold: (i) enable Scottish argumentation researchers, and especially PhD students, to mutually present their work; (ii) affirm Scottish argumentation research as a recognisable presence; (iii) provide a concrete opportunity for Scottish researchers to network. At SAD 2026 we aim to improve visibility for Scotland-based researchers, especially PhD students and early-career researchers, to encourage knowledge- and skill-exchange at all levels, and to foster cross-institution relations and collaborations. Participation is free but registration is required.

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: Jinming Yang
Date: 04 June, 2026
Time: 11:00 - 12:00
Location: Sir Alwyn Williams Building, 423 Seminar Room

EASE 2026: International Conference on Evaluation and Assessment in Software Engineering

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 09 June, 2026
Time: 01:00 - 01:00
Location: James McCune Smith Learning Hub, University Avenue, Glasgow, G12 8QW

EASE is an internationally leading venue for academics and practitioners to present and discuss their research on evidence-based software engineering, and its implications for software practice. EASE is ranked as A conference in CORE. The 30th edition of EASE will take place in Glasgow, Scotland. EASE 2026 welcomes high-quality submissions, describing original and unpublished research for the following tracks: full research papers, short papers & emerging results, industry, posters & vision, journal-first, and a doctoral symposium. There will also be co-located events, including workshops and tutorials, and a track planned for journal-first presentations. See conference website for submission tracks and deadlines. EASE 2026

S3CIX 2026 - Symposium and Summer School on Computational Interaction

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 16 June, 2026
Time: 01:00 - 01:00
Location: Sir Alwyn Williams Building, University of Glasgow, 18 Lilybank Gardens, Glasgow, G12 8QN, United Kingdom

Registration for the 10th Symposium and Summer School on Computational Interaction will open 1 February and close 14 March 2026. View programme, event details and registration process at S³CIX 2026. This year S³CIX is expanding from a Summer School format to also include a 4 day long academic Symposium. We anticipate about 30 students and 40 academics and invited speakers to attend. There will also be two workshops. Computational interaction often involves elements from machine learning, signal processing, information theory, optimisation, inference, control theory and formal modelling. Computational interaction would typically involve at least one of: an explicit mathematical model of user-system behaviour; a way of updating that model with observed data from users; an algorithmic element that, using this model, can directly synthesise or adapt the design; a way of automating and instrumenting the modelling and design process; the ability to simulate or synthesise elements of the expected user-system behaviour.”

TBC

Group: Networked Systems Research Laboratory (NETLAB)
Speaker: TBC
Date: 18 June, 2026
Time: 11:00 - 12:00
Location: Lilybank Gardens, F121 Conference Room

10th Summer School and Symposium on Computational Interaction (S³CIX)

Group: Inference, Dynamics and Interaction (IDI)
Speaker: multiple
Date: 20 June, 2026
Time: 09:00 - 16:00
Location: Sir Alwyn Williams Building, 422 Seminar Room

Welcome to the Symposium and Summer School on Computational Interaction! This year we are expanding from a Summer School format to also include a 4 day long academic Symposium. We anticipate about 30 students and 40 academics and invited speakers to attend. There will also be two workshops.

SPLV’26: Scottish Programming Languages and Verification Summer School 2026

Group: Scottish Informatics and Computer Science Alliance (SICSA)
Speaker: SICSA Event, SICSA
Date: 03 August, 2026
Time: 01:00 - 01:00
Location: TBA

The 2026 edition of SPLV will be held at the University of Glasgow, with the main courses running from within the Gilbert Scott Building. The school is aimed at PhD students in programming languages, verification and related areas. Researchers and practitioners are welcome, as are strong undergraduate and masters students with the support of a supervisor. Participants should have a background in computer science, mathematics or a related discipline. Prospective students may contact the organisers if they have any concerns about background knowledge. Registration will open March 2026. View full programme at SPLV 2026 | SPLV

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