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Centre for Machine Intelligence

Who We Are | Centre for Machine Intelligence

We are a world-leading group of researchers, thinkers, and entrepreneurs.

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The Centre for Machine Intelligence was initiated by the department of Electronics and Computer Science and is a centre of expertise for Artificial Intelligence, Machine Learning, and Autonomous Systems. We work with industry, policy makers, and the general public to address both national and global challenges.

Centre for Machine Intelligence Board

Haiming Liu (Director)

Dr Haiming Liu is an Associate Professor at the WAIS research Group of ECS. Haiming specialises in understanding users’ preferences and behaviours during their information access processes.

Corina Cirstea

Corina Cirstea is a lecturer and holds a DPhil in Computation from the University of Oxford (2000). She was the holder of a Junior Research Fellowship in Computer Science at St. John's College Oxford prior to joining Southampton.

Kate Farrahi

Kate is an assistant professor focused on machine learning, particularly deep learning applied to health-related applications. She is interested in developing techniques to address novel sensor-driven healthcare problems.

Jonathon Hare

Jonathon's research interests lie in the area of multimedia data mining, analysis and retrieval, with a particular focus on large-scale multimodal approaches. This research area is at the convergence of machine learning and computer vision.

Luis-Daniel Ibáñez

Luis-Daniel is a Lecturer. He has interests in Data Science support systems including Dataset Discovery, pricing and valuation. He also has interests in interfaces for learning Data Science.

Shoaib Jameel

Shoaib Jameel’s research interests are in natural language processing and information retrieval applied to the education domain. His research goal is to develop computational methods that will automatically create geographically personalised content.

Sasan Mahmoodi

He is currently an associate professor with research interests in biometrics, medical image analysis, computer vision, and machine learning. Dr. Mahmoodi has been the primary investigator of Gait Analysis Project funded by DSTL.

Stuart Middleton

Stuart Middleton is an Associate Professor at the AIC research group of ECS. His research interest lies in the Natural Language Processing (NLP) areas of information extraction and human-in-the-loop NLP.

Thanassis Tiropanis

Thanassis is professor at the Web and Internet Science Group. His expertise is in decentralised data architectures, distributed linked data infrastructures, semantic technologies.

Mohammad Soorati

Mohammad's research centers on bringing multi-robot systems to trustworthy real-world applications. His group is trying to address the challenges of trustworthy human-swarm teaming and design tools and methodologies for human-centered robotics.

Steering Committee

The members of the committee include respected academics and representatives from Industry. Under their guidance, the CMI aims to broaden its impact and reach out to communities employing machine intelligence in their research and practice. Our current members are:

  • Themis Prodromakis 
  • Stephen Prior
  • Steve Beeby
  • Tim Norman
  • Michalis Zervas
  • Koushik Maharatna

 

Related Staff Member

Steffen Staab 

Professor for Web and Computer Science

My Research: How can computers know something about the world? In my research I am interested in how computers can have explicit or implicit knowledge. Explicit knowledge can be organized in huge knowledge graphs. They may capture data bases, but typically go beyond in expressivity and range. I research how to manage knowledge graphs and how to exploit them by querying or machine learning. Implicit knowledge may be derived from data and in particular from text. There, I am interested how to uncover implicit knowledge using text and data mining, information extraction and text clustering.

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Related Staff Member

Dr. Danesh Tarapore 

Lecturer

My research: Dr. Tarapore’s research is interdisciplinary in nature, focused on understanding biological systems, and developing bio-inspired approaches to the design of fault-tolerant and resilient robots. Through the development and application of theoretical models, agent-based models, multi-scale stochastic simulations, and the physical instantiation of biological models in robots, he has addressed a diverse range of important problems in task allocation and division of labour in large-scale multiagent systems, immunological maintenance of self-tolerance in the adaptive immune system, and fault-detection and fault-tolerance for both single-robot systems, and large-scale robot swarms. Through addressing such diverse problems, Danesh has gained expertise in a wide range of fields besides robotics, including: bio-inspired learning algorithms, swarm intelligence, robot behaviour representation, and evolutionary robotics.

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Related Staff Member

Prof. Mike Wald 

Professor of Computer Science

Professor Mike Wald leads research into accessible technologies in the Web and Internet Science Group, ECS, University of Southampton. He has had many years of experience working with disabled users in research, development, support and provision of knowledge in the areas of disability, assistive technology and digital accessibility. He was a founder member of the International Liberated Learning Consortium that included leading universities and organisations investigating how speech recognition captioning and transcription could be enhanced. Over 20,000 people in more than 150 countries have enrolled on his online inclusion and digital accessibility courses.

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Related Staff Member

Dr. Sebastian Stein 

Associate Professor

Dr Sebastian Stein’s research focusses on resource allocation problems in multi-agent systems, where he is applying techniques from mechanism design, incentive engineering and decision-making under uncertainty. He is passionate about applying his work to addressing important societal challenges and he has worked on electric vehicle (EV) charging, intelligent transportation systems, crowdsourcing , participatory sensing for pollution monitoring and cloud systems.

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Related Staff Member

Prof. Kirk Martinez 

Professor of Computer Science

My research creates solutions to environmental sensing problems. Previous research includes novel sensor networks in glaciers using new networks and decision making algorithms. Current research is into semi-autonomous UAVs aiding in the deployment and recovery of sensor network nodes on glaciers in Iceland.

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