The University of Southampton

We run a seminar series within the department and also co-organise events with external partners. Please get touch if you are a member of the university and  want to attend our seminar series. Our general events are listed below.

  

Tony Russell-Rose
Martin White

CMI Networking Event

Monday 10th July 2023
5pm
Highfield Campus
Building 2A (The Annex)

Registration HERE.

We would like to invite you to the Centre For Machine Intelligence (CMI) Networking event, which will take place at Highfield Campus of the University of SouthamptonBuilding 2a Arts Annexe at 17:00- 20:00 on 10th July 2023 (Monday),

 This is a good opportunity to meet and connect with academics and practitioners, or just have a social chat. We are privileged to have two speakers to share their insight in Search and AI. 

Agenda

17:00 - 17:15  : Registration & Refreshment
17:15 -17:30   : Welcome & Introduction to CMI and the Board
17:30 -18:00  :  Talk by Martin White,  "Will AI solve the problems of consistently poor enterprise search satisfaction?"
18:00 - 18:30 :  Talk by Tony Russell-Rose,  " Searching fast and slow"
18:30 - 20:00 : Social reception

To secure a place, please register at HERE.

Martin White https://searchresearch.online/
Visiting Professor, Information School, University of Sheffield

Martin graduated from Southampton University with a degree in chemistry in 1970, but inspired by a staff member of the Library immediately embarked on a career as an information scientist. He began using computer-based search services in the late 1970s. From 1999 to 2022 he provided consulting services in information management primarily to multi-national multi-lingual companies, specialising in intranet and enterprise search implementation. He has been a Visiting Professor since 2002 and has served on the Advisory Committee of the Information School. He also lectures at City University, University of London. Martin is the author of ten books, four of them about enterprise search.

 

Tony Russell-Rose https://isquared.wordpress.com/about/
R
eader, Goldsmith University

 Tony joined Goldsmiths, University of London in September 2019 as Reader in Computer Science. He is also Director of UXLabs, a research and design consultancy specialising in complex search and information access applications, and founder of 2Dsearch, a platform applying AI, natural language processing and data visualisation to create the next generation of search experiences. He is vice-chair of the BCS Information Retrieval group and ex-chair of the CIEHF Human-Computer Interaction group. He also holds the position of Royal Academy of Engineering Visiting Professor of Cognitive Computing and AI at Essex University.

 

 

 

Prof. Dr. Dirk Neumann

CMI Seminar: Online Demand Response Programs for Constrained Local Electricity Systems

Thursday 25th August 2022 - 2pm
Room: B32/3077
MS Teams link: To be sent to registered attendees 30min before start
Registration: Online Demand Response Programs for Constrained Local Electricity Systems Tickets, Thu 25 Aug 2022 at 14:00 | Eventbrite

 

 

Speaker:
Prof. Dr. Dirk Neumann
Head of the Institute of Economics and Business Administration
Chair of Information Systems Research
Albert-Ludwigs-Universität Freiburg
(https://www.is.uni-freiburg.de/mitarbeiter-en/team/dirk-neumann)

Abstract:
Renewable energies require new approaches to the operation of power systems. In this talk, I present a novel Demand Response (DR) program to mitigate grid congestion. The program stands out by adjusting electricity prices online and solely based on observed aggregate electricity consumption. It thereby avoids privacy concerns and expensive information system infrastructure investments. Additionally, it can cope with non-elastic and time-interdependent demand—which is typical for storage devices and industrial processes. ) model four flexible load types and provide a unified framework of load modeling under uncertainty and with time interdependencies.
Numerical experiments show that the DR program achieves considerable and stable cost savings of 40% to 60% in comparison to conventional DR programs. Moreover, the solution approach based on Deep Reinforcement Learning reaches these savings after a short learning period corresponding to only 25 simulation days.
Regarding load flexibility, I find that the responses of the four load types strongly differ depending on prices and the lag between the announcement and the application of price changes (`notification interval’) which is an important design parameter. The results imply that system operators should flexibilize their DR programs with the help of learning algorithms and tailor their program to the local load composition, congestion frequency, and forecasting quality.

Bio:

Dirk Neumann has held the Chair of Information Systems Research at the Albert Ludwigs University of Freiburg as a Full Professor since 2008. He studied economics in Gießen and Milwaukee and read his PhD at KIT. The research focus of his working group is, among other things, AI in management. During his stays abroad, he worked with researchers at the University of New South Wales (UNSW) in Sydney, Concordia University in Montreal and Stanford University in Palo Alto.  In his field of research, he is one of the most published researchers in Germany. He has received appointments at Humboldt University Berlin and Johannes Kepler University Linz (Austria).

 

 

CMI Intelligent Remote Sensing "show and tell"

16th June 2021 - 2:00 to 3:30pm
 
Press here to register for the event on Teams
 
Across the breadth of the University and our work with local collaborators there is a massive amount of research looking at extracting information from remotely sensed image and point-cloud data. The imagery being analysed is varied and goes from imagery of the sea floor captured by AUVs through to aerial imagery and LIDAR of land-masses from aircraft, though to multispectral, hyperspectral and RADAR imagery of the entire Earth. Different research groups are tackling the problems of automating the processes of information extraction from these diverse data sources using modern machine learning and deep learning techniques.
 
This CMI event aims to bring together a number of researchers from different groups to enable us to get a big picture of this research area at Southampton. We have arranged short talks covering the gamut of research taking place locally, and hope that this will provide a means to future collaboration and sharing of ideas and data. After the talks, there will be some time for questions, as well as to think about the appetite for more focussed exploration of the synergies across research groups.
 
Speakers:
 
Jonathon Hare - ECS
Blair Thornton - Engineering
Christine Gommenginger - NOC
Fraser Sturt - Archaeology
Isabel Sargent - Ordnance Survey
Paul Kemp - Engineering
Iris Kramer - ECS & ArchAI
Patrick Osborne - Geography

https://teams.microsoft.com/registration/-XhTSvQpPk2-iWadA62p2A,ArQsjSxy...

  

Dr. Edoardo Manino
Dr. Chris Duckworth
Prof. Cecilia Mascolo

28th April 2021 - CMI seminar (virtual): Machine Intelligence for COVID-19

The Centre for Machine Intelligence (CMI) at the University of Southampton invites you to a seminar on the topic of "Machine Intelligence for COVID-19".  As the fight against the COVID-19 continues, a wide range of research efforts are taking place. We are hosting three talks about the latest academic research on how different aspects of machine intelligence are helping with this endeavour, followed by a live Q/A and panel session with the presenters. 

14:00 - 14:05 - Welcome and introduction - Dr. Enrico Gerding (Director of CMI)

14:05 - 14:20 - The sounds of COVID-19: crowdsourcing and analysing respiratory signals for COVID-19 diagnostics -  Prof. Cecilia Mascolo (University of Cambridge) 

Abstract: In this talk I will describe the work we have been doing on crowdsourcing respiratory sounds (coughs, breathing and voice) through a mobile app  (covid-19-sounds.org) and their analysis through audio based machine learning for COVID-19 diagnostics and disease progression. This work is part of a a bigger project which looks at how sounds of the human body (respiratory, cardiovascular, digestive) can be collected through wearables and mobile devices and analysed with the aim of improving automated and efficient medical diagnostics.

Bio: Cecilia Mascolo is the mother of a teenage daughter but also a Full Professor of Mobile Systems in the Department of Computer Science and Technology, University of Cambridge, UK. She is co-director of the Centre for Mobile, Wearable System and Augmented Intelligence and Deputy Head of Department for Research. She is also a Fellow of Jesus College Cambridge and the recipient of an ERC Advanced Research Grant. Prior joining Cambridge in 2008, she was a faculty member in the Department of Computer Science at University College London. She holds a PhD from the University of Bologna. Her research interests are in mobile systems and data for health, human mobility modelling, sensor systems and networking and mobile data analysis. She has published in a number of top tier conferences and journals in the area and her investigator experience spans projects funded by Research Councils and industry. She has received numerous best paper awards and in 2016 was listed in “10 Women in Networking /Communications You Should Know”.  She has served as steering, organizing and programme committee member of mobile, sensor systems, networking, data science conferences and workshops. She has delivered a number of keynote talks at conferences and workshops in the area of mobility, data science, pervasive computing and systems. 

14:20 - 14:35 - Emergency department admissions in COVID-19 and explainable machine learning to understand changes in clinical decision making - Dr. Chris Duckworth (IT Innovation Centre)

Abstract: The COVID-19 pandemic has created rapid and unprecedented changes in how services across the NHS are used. Emergency departments (EDs) have seen a 57% decrease (April 2020) in visits, with indications that patients in need of medical intervention have avoided coming to hospital for reasons unrelated to COVID, as COVID admissions have soared. This changing patient landscape has led to an overhaul in hospital operations and procedure. Decision support systems learn from historical ED operations, to enable early identification of patients who are at high risk of hospital admission, enabling ahead-of-time logistical planning. We test a machine learnt admission model's performance (trained pre COVID), pre COVID, and during the first wave, to understand how decision support systems are impacted by changing patient landscape and operational change. Using explainable machine learning, we understand how different hospital records (used as features) become more (or less) predictive of admission risk. We introduce the idea of using explainable admission models to track and understand changes in clinical decision making over time.

Bio: Chris is a Research Engineer (Healthcare) based in the IT Innovation Centre, as part of the School of Electronics and Computer Science. Since joining the centre in early 2021, his focus has been on the impact of COVID-19 on Emergency Department admissions and developing machine learning models for clinical decision making support. Chris' background in data science comes from a PhD (University of St Andrews) and employment at the Flatiron Institute (Simons Foundation) working in computational Astrophysics.

14:35 - 14:50 - Indirect disease mitigation using targeted interventions - Dr. Edoardo Manino (University of Manchester)

Abstract: The current COVID-19 pandemic is fought on two fronts: reducing the spread of the disease, and educating the population on the importance of vaccines and face masks. Both contribute to curbing the total number of cases, but how do these two factors interact? In this talk I present a mathematical model of coupled disease-awareness systems and propose strategies for optimal control. This is joint work with Dr Markus Brede (University of Southampton).

Bio: Edoardo Manino is a Research Associate in the Computer Science department of the University of Manchester. He is part of the EnnCore project and focuses on automated verification of neural network architectures. His background is in Bayesian machine learning, a topic he recently got awarded a PhD from the University of Southampton. His other research interests range from network science to algorithmic game theory and reinforcement learning.

14:50 - 15:30 - Panel discussion and Q/A - Chair: Dr. Kate Farrahi (University of Southampton)

Machine Intelligence Showcase 2019

Machine Intelligence experts will demonstrate the latest advances from revolutionary new technologies in a packed showcase event at the University of Southampton.

A distinguished panel of AI pioneers and government chiefs will discuss the research field’s expected impact on the UK economy and the necessary strategies to fulfil this potential at the all-day event, hosted by the University’s Centre for Machine Intelligence (CMI). The showcase takes place on Tuesday 22nd of October 2019. 

Machine Intelligence, which includes the development of Artificial Intelligence (AI), Machine Learning and Autonomous Systems, is using science to build a safer and smarter society. Researchers from Southampton’s School of Electronics and Computer Science (ECS) are leaders in several pioneering live projects and outlined the latest progress before an audience of around 200 industry attendees, government representatives and academic peers in our last year's event.

24th June 2019 - Data Infrastructures for the AI Economy

With attendees ranging from researchers, local authorities, SMEs and large corporates the event brough together a line up of lightning talks and breakout sessions dealing with the cutting edge challenges and opportunities of AI and how we can work together. Breakout sessions included Data Bias and Inclusion in AI; Privacy, Law and AI; Data Provenance and Governance; and Data Sharing Platforms – technological, legal and ethical challenges.

In line with the UK’s Industrial Strategy, we’re keen to foster academic-industry partnerships with a socio-technical angle and will be providing seed-funding opportunities for building collaborative teams from the sparks of shared interest we hope to generate at the event.  Attendees included the Office for AI, Southampton Connect, Hampshire County Council, Shell and a number of local SMEs.

Dr. Jonathon Hare opening the symposium

13th May : Symposium on Interdisciplinary Machine Learning

Across many disciplines at the university of Southampton, there is interest in the applications of machine learning to scientific research. The symposium on interdisciplinary machine learning was a morning event designed to bring together researchers and facilitate a discussion about this growing field. Talks covered a range of topics from archeology to biology with a view to understanding the benefits provided by machine learning and their limitations. The event attracted over 200 sign-ups and talks were well received by the audience

Speaker list:

  • Dr Jonathon Hare: Intorduction to the CMI and Machine Learning at Southampton
  • Professor Adam Prügel-Bennett: What can Machine Learning do for you?
  •  Xin Du: Applications Based on Cascade Learning
  • Iris Kramer: Machine Learning for Archeology
  • Greg Parkes: Using Machine Learning in Medicine
  • Dr Patrick Stumpf: Mapping Cell Idenitities from Mouse to Man

27th February 2019 CMI PhD Evening and intro to the MINDS CDT

The CMI PhD evening consisted of a series of talks detailing the PhD process, and specific areas of interest across the different core Machine Intelligence Research Groups within ECS. In particular, we introduced the new Centre for Doctoral Training on Machine Intelligence and Nano-Electronic Devices  (MINDS CDT) and the opportunities to get involved with this exciting training programme. 

 

26th October 2018 - Machine Intelligence Showcase

The Machine Intelligence Showcase was a great success. Head over to the event page to find out who was speaking and to watch the showcase video!

 CMI evening on Machine Learning - 21/06/2018

 When you read about AI in the news, you're more likely than not to actually be reading about a new advancement in Machine Learning. In the past 10 years, machine learning has started to find its way into everyday technology and revolutionise both products and industry.  The CMI evening on machine learning attracted over 150 attendees including members of the public, students, and researchers. Talks from industry and academia were well received by the audience and led to very exciting discussions at the end.

Speakers included

  • Dr Jonathon Hare, ECS - what machine learning can and can't do
  •  Professor Mahesan Niranjan, ECS - the reality of machine learning
  •  Professor Adam Prügel-Bennett, ECS - Title TBC
  •  Dr Honor Powrie, GE Aviation - GE Aviation Commercial Engines - ML Applications
  •  Dr Kate Farrahi, ECS - IoT and Health related applications of ML
  •  Dr Srinandan Dasmahapatra, ECS - Computational Biology
  • Oliver Tearle - AI Corporation - Practical Card Fraud Detection

 

The panel session received many questions about the use of data from the NHS and other questions around the techniques used to manage large datasets.

The evening closed with a very successful networking session. 

CMI Evening on Robots and their use in Warfare - 02/05/2018

We held an evening seminar on Robots and their use in Warfare on the 2nd of May. With over 130 signups, the event was a great success. World experts in the legal aspects of warfare, Prof. Christian Enemark and Dr. Regina Rauxloh gave an overview of the key legal, moral, and ethical considerations. Dr. Andrea Munafo from the National Oceanography Centre, along with Dr. Tarapore and Dr. Ramchurn from ECS, then provided an overview of the capabilities built into the next generation of autonomous systems, whether under-water, ground, or aerial. The evening concluded with a networking session that we hope will bring many more collaborations across the University via the CMI.

 

AI and Ethics Evening - 21/03/2018

CMI organised an evening of talks on Artificial Intelligence and the ethical and societal challenges associated with large scale use of such technology. The evening consisted of a number of talks by leading academics within the Centre for Machine Intelligence as well as guests from leading tech companies. Prof. Chris Reed from Dundee and Dr. Isabel Sargent from Ordnance Survey were guest speakers.

We had over 60 attendees from within the University, industry, and the general public. The panel led to a number of questions raised around the use of argumentation machines to discuss ethical questions, the use of AI in defence and how we can work with policy makers to develop regulation for autonomous systems.

 

Prof. Steven Meers

CMI Phd Evening - 07/03/2018

The event was a great success with over 60 signups and  a number of talks detailing topics in AI, Machine Learning, and Autonomous Systems as well as funding opportunities. 

The  networking part generated great interactions between students, academics and existing PhD students. 
 

01/02/2018 -  AI and Blockchain: Opportunities and Challenges

This first open event organised by the CMI attracted over 100 attendees from across ECS, the Faculty of Engineering and Physical Sciences, as well as industry and the general public. The event was sponsored by Oxford Innovation and was an exciting mix of both academic presentations and hands-on use-case discussions from industry. 

 

Paul Lewin, head of ECS, opening the the first CMI event.