Research Seminars 2015-16 Academic Year

Speaker Institution Date, Location Ack
Prof Sanjay K. Jha University of New South Wales 07/09/2016, N118 WT
Dr Mykola Pechenizkiy Eindhoven University of Technology 27/04/2016, N242 MG
Dr Alice Toniolo & Dr Marianthi Leon Aberdeen, Robert Gordon University 27/04/2016, N242 ML
Dr Dawn Carmichael Abertay 30/03/2016, N117 DCD
Chris Campbell Robert Gordon University 15/03/2016, N117 DCD
Prof Quintin Cutts Glasgow 24/02/2016, N117 DCD
Dr. Marilyn Lennon Strathclyde 17/02/2016, N117 DCD
Dr. Martin Halvey Strathclyde 27/01/2016, N117 DCD
Dr. Christophe B. Michel Stirling 09/12/2015, N117 DCD
Dr. Paul Anderson Edinburgh 25/11/2015, N118 DCD
Dr. Fiona McNeill Heriot-Watt 18/11/2015, N117 DCD
Dr. Leo Chen Glasgow Caledonian 11/11/2015, N118 DCD
Dr. Louis Aslett Oxford 04/11/2015, N117 DCD
Peter Prjevara Kongsberg 23/10/2015, N117 DCD
Dr. Bo Han AT&T Research Labs 08/10/2015, ABS 441C WT

Other Forthcoming Speakers – Dates to be Confirmed
Assoc Prof Horacio Gonzalez-Velez, National College of Ireland
Amy Nicholson, Andrew Fryer, Microsoft – Data Science
Prof George Coghill, Aberdeen
Prof Jose Alcaraz-Calero, University West of Scotland, 2016

General Info
Seminars usually held on Wednesdays beginning at 13:05, Sir Ian Wood Building, Garthdee Road, Robert Gordon University, Aberdeen. If you have suggestions for possible speakers then please do contact the Seminar host/organiser.

Lecture room locations can as also change from time to time, hence note the location listed below and in the corresponding post about the Seminar.


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Towards Socially Intelligent Robots – Karen Spärck Jones lecture LiveCast@RGU 25 May 2017

To honour the pioneering work of Karen Spärck Jones, the British Computer Society (BCS) holds a distinguished lecture in her name each year, celebrating a prominent female computing researcher.

The 2017 lecture will be given by Dr. Maja Matarić (University of Southern California) who is Professor and Chan Soon-Shiong Chair of Computer Science, Neuroscience & Pediatrics; Founding Director at the USC’s Robotics and Autonomous Systems Center, and Director of the USC’s Robotics Research Lab.

The lecture will take place on 25 May 2017, 18:00 – 19:30 BST in Room N303

Sir Ian Wood Building
Robert Gordon University
Garthdee Road
AB10 7GJ

We would appreciate it if you could register your interest to attend here:


How can human-robot interaction be improved by making robots more socially intelligent? This is the key question at the heart of socially assistive robotics (SAR): a new field of intelligent robotics that focuses on developing machines capable of assisting users through social rather than physical interaction, in order to encourage people to have the drive and motivation to do their own work, for improved health and wellness. Our research brings together engineering, health sciences, neuroscience, social, developmental, and cognitive sciences to create robots that can serve as coaches, motivators, and companions. This requires personalising human-robot interaction through appropriate speech, gesture, and body language; the embodiment is the most important even without physical work. Our successes include coaching stroke patients to perform rehabilitation activities, helping children with autism to learn social skills, encouraging teens at risk for type-2 diabetes to exercise, motivating first graders to make healthy food choices, and helping elderly patients with Alzheimer’s disease to stay engaged. The lecture will describe those projects and the associated research into embodiment, modelling and steering of social dynamics, and long-term user adaptation for SAR, illustrated with many videos.

About the Lecturer:

Dr. Maja Matarić is inspired by the vast potential for affordable human-centered technologies, especially socially assistive robotics, as means of improving human quality of life. Founder and director of the Interaction Lab at the University of Southern California, her research is aimed at endowing robots with the ability to help people, especially those with special needs. She is passionate about conveying the importance and promise of interdisciplinary engineering research and careers in STEM to all who should know more, including K-12 students and teachers, women and other underrepresented groups in engineering, the media, and policymakers.

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Wed 26th April 2017 – Dr. Richard Dybowski


Wed 26th April 2017 – Dr Richard Dybowski

Dr Richard Dybowski – Disease Dynamics Unit, University of Cambridge


Two recent developments in neural computation: NTMs and GANs

The presentation will focus on two recent developments from the neural computing community. The first is the concept of the Neural Turing Machine (NTM), which is a fully differentiable system with the potential to learn algorithmic solutions to problems, and which has outperformed LSTM-based recurrent networks. The second is the Generative Adversarial Network (GAN), in which the parameters of a probabilistic generative model are estimated via a minimax game involving a discriminating deep neural network.

I am an applied mathematician, statistician and computer scientist based in the Disease Dynamics Unit, University of Cambridge. Following a degree in chemistry, I specialised in NMR spectroscopy. I undertook a PhD in statistical and computational chemistry at Leeds University (i.e., the computational diagnosis of endocrine metabolites) and was then appointed as a Research Fellow at St Thomas’ Hospital/King’s College London, where I undertook statistical research into a variety of medical areas, including microbiology, intensive care, and ophthalmology. I also taught artificial intelligence (AI) as a University Lecturer in computer science at the University of East London. After a number of years away from academia caring for others, I returned in earnest.

Venue and Time

Lecture Room N117, 14:00 – 15:00.

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, AB10 7GJ 

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Wed 22 Feb 2017 – Prof David Benyon

Professor David Benyon, Napier University, Edinburgh

Designing Blended Spaces


A blended space is a space where a physical space is deliberately integrated in a close-knit way with a digital space. Because the digital space has been designed and integrated with a physical space a novel user experience is created. New properties emerge from the particular combination of physical and digital that may give rise to a new sense of presence. 

Blending Theory was originally developed as a theory of linguistics and language understanding. Prof Benyon introduced the concepts to interaction design with his book Designing with Blends in 2006 and followed this with Spaces of interaction, Places for Experience (2014, Morgan and Claypool). In this talk, he will explore the ideas and where they have been applied.


Professor David Benyon has been working in the area of human-computer interaction (HCI) and interaction design for over 25 years. He has written widely on the subject with over 150 refereed publications covering HCI, interaction design and intelligent user interfaces. He published one of the first textbooks on HCI in 1994 and recently completed the 4th edition of the textbook Designing User Experience: a comprehensive guide to HCI, UX and interaction design (Pearson, 2013). In 2007 Prof Benyon introduced ideas of conceptual blending to HCI with his book Designing with Blends (MIT Press, with Manuel Imaz). He published his monograph Spaces of Interaction, Places for Experience with Morgan and Claypool in September 2014.

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, Lecture Room N117, 13:00 – 14:00.

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Wed 7th Sept 2016 – Prof Sanjay K. Jha

Professor Sanjay K. Jha – University of New South Wales

A Changing Landscape: Securing The Internet Of Things (IoT)

First part of this talk will discuss how the community is converging towards the IoT vision having worked in wireless sensor networking and Machine-2-Machine (M2M) communication. This will follow a general discussion of security challenges in IoT. Finally I will discuss some results from an ongoing projects on security of bodywork devices and IoT. Wireless bodyworn sensing devices are becoming popular for fitness, sports training and personalized healthcare applications. Securing the data generated by these devices is essential if they are to be integrated into the current health infrastructure and employed in medical applications. In this talk, I will discuss a mechanism to secure data provenance and location proof for these devices by exploiting symmetric spatio-temporal characteristics of the wireless link between two communicating parties. Our solution enables both parties to generate closely matching `link’ fingerprints, which uniquely associate a data session with a wireless link such that a third party, at a later date, can verify the links the data was communicated on. These fingerprints are very hard for an eavesdropper to forge, lightweight compared to traditional provenance mechanisms, and allow for interesting security properties such as accountability and non-repudiation. I will present our solution with experiments using bodyworn devices in scenarios approximating actual device deployment. I will also touch upon other research on secure reprogramming of IoT devices over wireless networks.

Professor Sanjay K. Jha is Director of the Cybersecurity and Privacy Laboratory (Cyspri) at UNSW. He also heads the Network Systems and Security Group (NetSys) at the School of Computer Science and Engineering at the University of New South Wales. His research activities cover a wide range of topics in networking including Network and Systems Security, Wireless Sensor Networks, Adhoc/Community wireless networks, Resilience and Multicasting in IP Networks. Sanjay has published over 200 articles in high quality journals and conferences and graduated more than 20 Phd students. He is the principal author of the book Engineering Internet QoS and a co-editor of the book Wireless Sensor Networks: A Systems Perspective. He is an editor of the IEEE Trans. of Secure and Dependable Computing (TDSC) and served as an associate editor of the IEEE Transactions on Mobile Computing (TMC) and the ACM Computer Communication Review (CCR).

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, Lecture Room N118, 11:00 – 12:00.

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Wed 27th April 2016 – Dr Mykola Pechenizkiy

Dr Mykola Pechenizkiy – Eindhoven University of Technology

Predictive Analytics that Works!?

Application-driven research in predictive analytics contributes to the massive automation of the data-driven decision making and decision support. As data mining researchers and data scientists we often have a (false) believe that our techniques are immediately applicable for solving real problems, and have no bad intents; and thus we can keep our focus on developing novel techniques pushing for higher and higher accuracy of predictive models. Some of us study how to make them more robust or adaptive to changes in known and hidden contexts, others – how to facilitate privacy-preserving or privacy-aware analytics. In the first part of my talk, I will overview some of such practical issues that matter in real applications and relate them to the current state of the art in predictive analytics research.
However, recent reports as e.g. 2014 Whitehouse Review of Big Data argue that “big data technologies can cause societal harms beyond damages to privacy”, that data-driven decisions could have discriminatory effects even in the absence of discriminatory intent, that there are threats of opaque decision-making and call for a thorough studying of these threats and of methods to address them. In the second part of my talk I will revisit these concerns in the context of the personalized medicine research with the goal to highlight why the general public, domain experts or policy makers may consider predictive analytics as a thread. I will present my subjective view on what questions need to be included into the data science research agendas for gaining a deeper understanding what it means for predictive analytics to be ethics-aware and accountable and how we can achieve this.

Mykola Pechenizkiy is Associate Professor in Predictive Analytics at the Department of Computer Science, Eindhoven University of Technology (TU/e), the Netherlands. He received his PhD in Computer Science from the University of Jyvaskyla, Finland in 2005. Since June 2013 he is also Adjunct Professor in Data Mining for Industrial Applications there. His expertise and research interests are in predictive analytics and knowledge discovery from evolving data, and in their application to real-world problems in industry, commerce, medicine and education. He develops generic frameworks and effective approaches for designing adaptive, context-aware predictive analytics systems. He has actively collaborated on this with industry. He has co-authored over 100 peer-reviewed publications and co-organized several workshops, conferences, special issues, and tutorials in these areas. He served as the chair of the steering committee of Computer-Based Medical Systems (CBMS) conference series in 2012-2016. As a panelist and an invited speaker he has been advocating for the ethics-aware predictive (learning) analytics research at several recent events, including the FATML@ICML 2015 and NSF IRB Privacy and Big Data workshops and the EDM 2015 conference.

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, Conference Room N242, 14:00 – 15:00.

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Wed 27th April 2016 – Dr Alice Toniolo & Dr Marianthi Leon

Dr Alice Toniolo – University of Aberdeen & Dr Marianthi Leon – Robert Gordon University

Argumentation schemes for supporting collaborative reasoning and deliberation dialogue; an application for analysing collaboration for the built environment

The ability to process large amounts of data and forecast possible trends is fundamental in intelligence analysis, as well as in other analytic contexts such as web-commerce, social media, or criminal investigation. Current solutions for high-end analytics focus primarily on data aggregation and visualisation. The first part of this talk focusses on how to support users in the process of making sense of the information extracted, or received from different sources in the context of intelligence analysis. An agent-based tool called CISpaces (Collaborative Intelligence Spaces) is presented to help analysts in acquiring, evaluating and interpreting information in collaboration with others. Agents assist analysts in reasoning with different types of evidence exploiting argumentation schemes to structure and share analyses, crowd-sourcing to collect information and provenance to establish the credibility of hypotheses.

The second part of the presentation is focused on efficient monitoring of decision steps by employing a computational model of argumentation applicable to Architecture Engineering and Construction industry collaborative design processes. The presented approach provides a method to rigorously trace the resolution of conflicts by extracting these to acceptable arguments that led to a decision, and may eventually assist multidisciplinary teams of engineers and designers in analysing complex collaborative decisions within a pre-Building Information Modelling context.

Dr Alice Toniolo is a Research Fellow in the Agent, Reasoning and Knowledge group in the Computing Science Department at the University of Aberdeen, UK. Her research is associated with the Collaborative Intelligence Analysis project within the International Technology Alliance in Network and Information Sciences. She is investigating how argumentation schemes can facilitate the intelligence analysis process in elaborating information for identifying plausible explanation for a situation. She was awarded her PhD in Computing Science by the University of Aberdeen, jointly funded by dot.rural RCUK Digital Economy Research, the U.S. Army Research Laboratory, and the International Technology Alliance. Alice has investigated how argumentation models of deliberative dialogue based upon argumentation schemes can enhance agent collaborative planning. Prior to her PhD, she obtained her MSc and BSc in Computer Engineering from the University of Padova, Italy.

Dr Marianthi Leon is a Lecturer and a Research Fellow in Aberdeen Business School and Scott Sutherland School accordingly, at RGU, UK. Her research is focused on managing multidisciplinary collaborations and on 3D scanning and built environment visualisations for supporting stakeholders’ cooperation. Marianthi was awarded her PhD from Scott Sutherland School of Architecture and the Built Environment, which was funded by IDEAS Research Institute. Her PhD investigated and analysed multidisciplinary teams’ collaboration, especially with the application of computer mediation and Tangible User Interfaces specifically. She developed a Protocol/framework for supporting concept and project initiation stages, which she has been applying and optimising it through an ongoing research (PhD and onwards). Prior to her PhD, Marianthi obtained her MSc in Adaptive Architecture and Computation from UCL and she is a Chartered Architect, from Aristotle University of Thessaloniki, Greece.

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, Conference Room N242, 12:30 – 14:00.

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Wed 30th Mar 2016 – Dr Dawn Carmichael

Dr Dawn Carmichael – Glasgow Caledonian University

Smart Metrics

A discussion of a methodology for arriving at value added quality metrics with examples from social media and games.

Dawn Carmichael has a PhD in Software Metrics, is a Lecturer in HCI at Glasgow Caledonian University, has led two funded research projects, and was a Teaching & Learning Committee Chair for over ten years.

School of Computing Science & Digital Media, Robert Gordon University, Sir Ian Wood Building, Garthdee, Aberdeen, Conference Room N117, 13:00 – 14:00.

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