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X-ORIGINAL-URL:https://sicsa.ac.uk
X-WR-CALDESC:Events for SICSA
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260415T040000
DTEND;TZID=UTC:20260415T170000
DTSTAMP:20260609T033157
CREATED:20260407T164551Z
LAST-MODIFIED:20260407T164812Z
UID:10000101-1776225600-1776272400@sicsa.ac.uk
SUMMARY:SICSA Seminar - Dr Carl Strathearn presents AI-driven Humanoid Robots for Education
DESCRIPTION:AI-driven Humanoid Robots for Education: Insights from UK Rapid Technology Assessments with Dr Carl Strathearn\nAbstract:\nAI-driven humanoid robots are gradually moving out of laboratories and into factories around the world. However\, more challenging domains such as education\, domestic environments\, and healthcare are significantly more unpredictable and difficult to evaluate in terms of effectiveness\, social interaction\, and risk.\nLast year\, Dr Strathearn contributed to the development of two rapid technology assessments published by the UK Government Office for Science on humanoid and AI-driven robots. These reports examined the feasibility and challenges of deploying such systems in their current state to help inform policymakers across government. In this talk\, he will provide a deep dive into the current state of the art in humanoid robotics\, covering large language models (LLMs)\, vision-language models (VLMs)\, and emerging vision-language-action (VLA) models\, and discuss some of the key challenges involved in deploying this technology in education going forward.\nDr Carl Strathearn is a lecturer in computer science and researcher in AI and humanoid robots at Edinburgh Napier University.\nThis seminar will be hybrid from Edinburgh Napier University’s Merchiston Campus. Register to receive meeting link.
URL:https://sicsa.ac.uk/event/sicsa-seminar-dr-carl-strathearn-presents-ai-driven-humanoid-robots-for-education/
LOCATION:Merchiston Campus\, Edinburgh Napier University\, 10 Colinton Road\, Edinburgh\, EH10 5DT
CATEGORIES:Event,Seminar
ATTACH;FMTTYPE=image/png:https://sicsa.ac.uk/wp-content/uploads/2026/04/sicsa-education-seminar-20260415-strathearn-humanoid-robots.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260327T100000
DTEND;TZID=UTC:20260327T143000
DTSTAMP:20260609T033157
CREATED:20260323T163815Z
LAST-MODIFIED:20260323T163815Z
UID:10000100-1774605600-1774621800@sicsa.ac.uk
SUMMARY:SSBSE 2026 Challenge Track Workshop 2
DESCRIPTION:About\nThis workshop series is a hands-on\, team-forming sprint. \nYou will meet potential collaborators\, shape a concrete research idea and leave with a realistic plan and division of labour toward a Challenge-Track submission for SSBSE 2026. \nThe SSBSE 2026 Challenge Track explores how Search-Based Software Engineering (SBSE) can optimize agentic AI systems (LLM-powered agents with tools\, memory\, planning\, and autonomy) for real software engineering tasks. You can read more about the challenge and its three themes at:  https://conf.researchr.org/track/ssbse-2026/ssbse-2026-ssbse-challenge. \nWho can participate?\nThe workshops are free and open to all. We particularly encourage academics and their PGR students to attend\, alongside industry practitioners and anyone interested in SBSE techniques for agentic AI systems\, especially undergraduate students interested in conducting research at the intersection of AI and Software Engineering. \nNo prior experience with specific agent frameworks or search based method is required. The workshop aims to find complementary expertise to provide solutions.  We will provide short technical briefings and a Discord channel for the workshop to provide timely technical and scientific support for the participants. \nFunding to support travel for staff and students at Scottish universities is available.   See event page for full details and registration.
URL:https://sicsa.ac.uk/event/ssbse-2026-challenge-track-workshop-2/
LOCATION:Merchiston Campus\, Edinburgh Napier University\, 10 Colinton Road\, Edinburgh\, EH10 5DT
CATEGORIES:Event,Workshop
ATTACH;FMTTYPE=image/png:https://sicsa.ac.uk/wp-content/uploads/2026/03/sicsa-ssbse-challenge-workshop-sprint-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260325T160000
DTEND;TZID=UTC:20260325T170000
DTSTAMP:20260609T033157
CREATED:20260304T165342Z
LAST-MODIFIED:20260304T165354Z
UID:10000098-1774454400-1774458000@sicsa.ac.uk
SUMMARY:SICSA Seminar - Can Evolution Develop Public Transport Networks?
DESCRIPTION:Register to attend \nJoin us on Wednesday\, 25 March for an AI & Data Science Seminar. \nDr Neil Urquhart of Edinburgh Napier University presents \nCan Evolution Develop Public Transport Networks? \nPublic transport networks by their very nature evolve over time to meet the needs of travellers\, fit the constraints of operators and meet the aspirations of politicians. This talk examines the use of novelty search to explore changes to the bus network in the centre of Edinburgh. The existing solution has been evolving since 1871 matching the changing nature of the city and transportation technologies. We harness geospatial data to evaluate the existing solution and then use novelty search to find modified solutions and examine their relationship to the existing solution. We are particularly interested in balancing the novelty of proposed changes with the distance from the current trusted solution. \nThis talk will demonstrate the potential for novelty search to assist with the design and modification of public transport routes and set and agenda for future research which will aim to cover larger areas and encompass multiple transport modes. \nDr Neil Urquhart is Associate Professor of Computer Science at Edinburgh Napier University\, his research interests include real-world applications of Artificial Intelligence particularly in the transport sector. \n 
URL:https://sicsa.ac.uk/event/sicsa-seminar-from-large-to-small-building-affordable-language-models-with-limited-resources/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://sicsa.ac.uk/wp-content/uploads/2026/03/sicsa-speaker-ai-neil-urquhart-napier-1.png
LOCATION:https://sicsa.ac.uk/event/sicsa-seminar-from-large-to-small-building-affordable-language-models-with-limited-resources/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260312T090000
DTEND;TZID=UTC:20260312T170000
DTSTAMP:20260609T033157
CREATED:20260304T153448Z
LAST-MODIFIED:20260304T153448Z
UID:10000097-1773306000-1773334800@sicsa.ac.uk
SUMMARY:SSBSE 2026 Challenge Track Workshop
DESCRIPTION:About\nThis workshop series is a hands-on\, team-forming sprint. \nYou will meet potential collaborators\, shape a concrete research idea and leave with a realistic plan and division of labour toward a Challenge-Track submission for SSBSE 2026. \nThe SSBSE 2026 Challenge Track explores how Search-Based Software Engineering (SBSE) can optimize agentic AI systems (LLM-powered agents with tools\, memory\, planning\, and autonomy) for real software engineering tasks. You can read more about the challenge and its three themes at:  https://conf.researchr.org/track/ssbse-2026/ssbse-2026-ssbse-challenge. \nWho can participate?\nThe workshops are free and open to all. We particularly encourage academics and their PGR students to attend\, alongside industry practitioners and anyone interested in SBSE techniques for agentic AI systems\, especially undergraduate students interested in conducting research at the intersection of AI and Software Engineering. \nNo prior experience with specific agent frameworks or search based method is required. The workshop aims to find complementary expertise to provide solutions.  We will provide short technical briefings and a Discord channel for the workshop to provide timely technical and scientific support for the participants. \nFunding to support travel for staff and students at Scottish universities is available.   See event page for full details and registration.
URL:https://sicsa.ac.uk/event/ssbse-2026-challenge-track-workshop/
LOCATION:Merchiston Campus\, Edinburgh Napier University\, 10 Colinton Road\, Edinburgh\, EH10 5DT
CATEGORIES:Event,Workshop
ATTACH;FMTTYPE=image/png:https://sicsa.ac.uk/wp-content/uploads/2026/03/sicsa-ssbse-challenge-workshop-sprint-1.png
END:VEVENT
END:VCALENDAR