This will be an interactive seminar led by part time PhD researcher, associate MSc Engineering Management lecturer and business executive, Jo North.
Intrapreneurs are entrepreneurial people who work in established organisations. They can be found in many types of organisation and across a wide range of functions and job titles. Intrapreneurs are important because they identify new opportunities for their organisation and follow through with action to convert opportunity into beneficial organisational results.
In this seminar, Jo will present a new perspective on identifying and measuring individual intrapreneurship within organisations, along with some of the key ingredients to achieving successful intrapreneurial outcomes.
Jo will explain what 'intrapreneurship', or being entrepreneurial inside an existing organisation, means in practice, how each of us has the potential to be more intrapreneurial in different ways, and share some intrapreneurship insights to help you to think differently about your own projects and get the very best from the people you work with.
Jo is Managing Director of The Big Bang Partnership Ltd, a commercial consultancy that helps businesses to innovate and grow. She has a proven track record of high profile leadership; directing high-value, competitive bid work streams, designing and delivering innovation activities and coaching managers and directors.
Jo has been a keynote speaker at numerous events, including Venturefest and York Business Week, and also leads Ideation development training workshops on Goldman Sachs’ 10,000 businesses programme.
Jo is an Associate Lecturer at the University of York, where she delivers corporate training in business creativity and innovation in addition to lecturing on Ideation, Marketing and Strategy and Operations.
We present an overview of some recent research on the grammar-based Genetic Programming approach of Grammatical Evolution, which has been taking place in the UCD Natural Computing Research & Applications Group. We place a special focus on developments in grammars and semantics.
Dr. O'Neill is Director of the UCD Complex & Adaptive Systems Laboratory (CASL), a founding Director of the UCD Natural Computing Research & Applications group, and is a Senior Lecturer in the UCD School of Computer Science & Informatics. He has published in excess of 250 peer-reviewed publications including 4 monographs, 17 edited books, and has over 4000 citations. Michael is Guest Editor of a special issue of Genetic Programming and Evolvable Machines on Semantic Methods in Genetic Programming, and co-organiser of a PPSN 2014 workshop on the same topic. He was Local Chair of the ACM Genetic and Evolutionary Computation Conference (GECCO 2011) which was held in Dublin, 12-16 July 2011 with nearly 700 submissions and 600 delegates from 52 countries. In the past he has served as Chair of the European Conference on Genetic Programming (EuroGP 2007 and EuroGP 2008), Chair of the Genetic Programming Track of the ACM Genetic and Evolutionary Computation Conference 2010, Co-Chair of the Grammars in Evolutionary Computation Special Session at IEEE WCCI 2008 and WCCI 2010,andChair of the Real World Applications Track of the Genetic and Evolutionary Computation Conference (GECCO 2009). He is Co-Founder and Chair of the European Event on Evolutionary and Natural Computation in Finance & Economics (EvoFIN 2007- 2010), which sees its eighth instance (EvoFIN 2014) in Granada, Spain in April 2014. He was also Chair of the Grammatical Evolution Workshops (GEWS 2002-2004), and Chair of the SIGEVO Graduate Student Workshop 2005. Dr. O'Neill is a member of the ACM SIGEVO Executive Board, Associate Editor of the journal Applied Soft Computing, and serves on the Editorial Boards of Genetic Programming & Evolvable Machines and Recent Patents on Computer Science. Dr. O'Neill has co-authored a number of successful funding applications with a total value over 7 Million Euro.
A key aspect of my recent research has involved investigations into how lifetime learning has affected the evolution of different animal species. That is useful in its own right, but it is also important to understand what has led to the evolution of different species if we want to use them as inspiration for building useful artificial systems. The two issues I have been concentrating on are: Neural Architecture (in particular, the advantages and causes of modularity), and Life History (the sequence of changes that take place during an organism’s lifetime: stages of growth, age at first reproduction, frequency of childbirth, litter size, protection of children, menopause, death). These don’t sound particularly related, but they do influence each other, and the same Artificial Life approach has proved effective for studying both. My talk will give an overview of my general approach, and also present some detailed results for a few particularly interesting aspects.
John Bullinaria completed a BSc in Physics at Imperial College London, Maths Part III at Cambridge University, and a PhD in Theoretical Physics at Southampton University. He then spent two years as a Research Fellow in Mathematics at Durham University working on Superstring Theory and Quantum Gravity, before leaving academia to travel the world for three years. He returned to get a "proper job" but instead obtained an MSc in Artificial Intelligence from Cranfield University, and spent the following nine years as a Research Fellow carrying out computational modelling in various Psychology departments. He moved to the School of Computer Science at the University of Birmingham in 2001, where he is now a Senior Lecturer. His current research interests are mainly in the fields of Computational Intelligence, Cognitive Science, and Artificial Life.
Artificial evolutionary systems often exhibit very low diversity and bounded complexity. I will give an overview of a number of projects, carried out with research partners and students, that include addressing these shortcomings within their aims: research into critical mutation rates for the maintenance of allelic diversity; mutation rate control for extinction-avoiding novel adaptation; the role of transcription errors in discovering behaviours inaccessible to incremental genetic evolution alone; and selection complexification strategies for incremental evolution. I will then look forward and discuss three approaches to the evolution of intelligent agents, more specifically to tackling the requirement to find an evolutionary path from a random or primordial soup to a sufficient behaviour: scaffolding selection with increasingly complex tasks, searching for novel behaviours, and seeding evolution by artificial selection with the results of (long-term or open-ended) evolution by natural selection. Examples of evolved agents will be shown in simple two-and three-dimensional environments.
Dr Alastair Channon worked in the software industry (at Micro Focus) before carrying out his BA/MA in Mathematics at the University of Cambridge and then focussing on Evolutionary and Adaptive Computation through an MSc at the University of Sussex and a PhD at the University of Southampton. From there he moved directly to a senior lectureship (post-92) at the University of Portsmouth in 1999, a lectureship at the University of Birmingham in 2004 and to the School of Computing and Mathematics at Keele University in 2007, where he is now a senior lecturer. His primary research interest is in the open-ended evolution of neurally controlled animats and he is best known for having created the only closed system other than Earth's biosphere to have passed the enhanced statistical "ALife Test" for open-ended evolution. Alastair's recent publications have included significant results on the relationship of mutation rate to population size, with clear implications for biological extinction events, and to fitness, computed over both abstract and biological fitness landscapes. He is a partner in a BBSRC project on the theory and practice of evolvability: effects and mechanisms of mutation rate plasticity, with partners at Manchester and Middlesex Universities, following the same team's successful completion of an EPSRC project on information dynamics in evolutionary systems.
This talk considers the implications, challenges and successes of an employer led development of a higher apprenticeship offering an alternative route to a degree for young people leaving sixth form and tertiary education. The Mineral Products industry provides a fundamental service to society, it literarily provides the foundations of the physical structures which form the basis of our civilization. It is at the same time both technologically basic and extremely advanced and requires of its employees and particularly its future managers and leaders, people who are well educated, flexible and whom demonstrate a good range of employability and behavioural skills. The Industry faces a demographic time-bomb, whilst it has continued to invest in its people during the recession, it recognises that new blood coming into the industry is insufficient over the medium to longer term to meet its needs as more and more of its senior people retire. Rather than focus on the recruitment of graduates straight from University, the industry felt that it would like to offer young people an alternate route to a degree, offering work experience and competence development whilst simultaneously studying for a degree whose learning programme is closely linked to the work-based learning journey. A pilot programme was developed and introduced in 2011 and a new cohort of around 40 student/apprentices are about to embark on a new phase this autumn. The programme has been very successful, but has not been without its challenges and this talk will focus on some of these and discuss how they have been overcome or are in the process of being addressed through the formative partnership which has developed between the industry and the University.
An educationalist and teacher by training, I served as a head teacher in my early career and then as a local authority school inspector, moving into the then Employment Department as a Vocational Education Advisor. During the past ten years I have served as Senior Manager of a National Training Organisation (NTO) and more recently as an advisor on ICT and electronic skills issues within the former UK Department of Trade and Industry (now Business Innovation and Skills). Currently I am an academic at the University of Derby, the academic lead within the Strategic Partnerships Unit where I specialise in Work-Based Learning, Employer Engagement and the development of Higher Apprenticeships. My research interests cover a variety of areas, but my main focus is assessment and learning in vocational education and training; the impact of Higher Apprenticeships on employability, pastoral care and well-being of students and a side interest in Maths Anxiety.
The presentation will give an overview of the technology that has the potential to allow terrorists and criminals to damage or disable critical infrastructure such as banks, airports, water, electricity and gas utilities. Work in the STRUCTURES FP7 project to detect, identify and locate the source electromagnetic attacks will then be presented.
In this talk, I will introduce a novel Joint Source and Channel Code (JSCC), which we refer to as the Unary Error Correction (UEC) code. Unlike existing JSCCs, our UEC facilitates the practical encoding of source symbol values that are selected from an infinite alphabet. Conventionally, these symbols would be conveyed using Separate Source and Channel Codes (SSCCs), but these are associated with a number of problems. In particular, Exp-Golomb codes and their family suffer from capacity loss, owing to the residual redundancy that typically remains in their encoded bits. Meanwhile, adaptive arithmetic codes suffer from extreme sensitivity to bit errors, owing to the loss of adaptive synchronisation that results between the encoder and decoder. By contrast, the proposed UEC code can eliminate nearly all capacity loss, without requiring any adaptive synchronisation between encoder and decoder. Furthermore, the UEC code has the same moderate complexity as state-of-the-art SSCCs, facilitating its employment in practical low-complexity applications. Even when encoding symbols from finite alphabets, the UEC complexity is typically significantly lower than that of other JSCCs, such as Variable Length Error Correction (VLEC) codes.
Vesa Välimäki is Full Professor of audio signal processing at Aalto University, Espoo, Finland. He received the Master of Science in Technology and the Doctor of Science in Technology degrees, both in electrical engineering, from the Helsinki University of Technology (TKK), Espoo, Finland, in 1992 and 1995, respectively.
In 1996, he was a Postdoctoral Research Fellow at the University of Westminster, London, UK. He was Professor of signal processing at the Pori unit of the Tampere University of Technology, Pori, Finland, in 2001-2002. In 2002, he was appointed Professor at TKK, which became part of Aalto University in 2010. In 2008-2009, he was a Visiting Scholar at Stanford University. He is the author of over 80 journal papers, 3 book chapters, and over 180 conference papers, and is responsible for four patents. His main research contributions are in the areas of physical modeling of musical instruments, digital filtering of audio signals, and virtual analog modeling. He has collaborated in research projects with several companies, for example Genelec, Nokia, and VLSI Solution.
Prof. Välimäki is a Senior Member of the IEEE and a Life Member of the Acoustical Society of Finland. He has been an Associate Editor of five journals and has organized four special issues for scientific journals. He was the Papers Chair of the AES 22nd International Conference on Virtual, Synthetic, and Entertainment Audio in 2002 and was the Chairman of the International Conference on Digital Audio Effects, DAFx-08, in 2008.
This talk focuses on signal processing techniques for modeling analog audio systems used in music technology. Many analog music systems produce a distinctive and desirable sound, but the original devices may be expensive or hard to access and maintain. Examples include classic synthesizer modules and vintage guitar amplifiers. It is therefore of interest to give such systems a new life as software simulations, which will be accessible to many. Virtual analog modeling approaches can be divided into three categories: 1. reduction of artifacts in digital signal processing, 2. introducing analog ‘feel’ to digital signal processing, and 3. emulation of specific analog equipment. An example of the first category includes the replacement of discrete unit delays with smoothly varying interpolated delays, and the reduction of aliasing occurring in oscillators and nonlinearities. Analog ‘feel’ comes from the simulation of typical characteristics or limitations of analog systems, such as limited bandwidth, distortion, parameter drift, and added noise. Emulation is the most demanding task, because it refers to the detailed imitation of the response of a particular device, whose behavior is often nonlinear. Emulation can be based on physical modeling of an analog circuit, or on the black-box method, which models the system based on observing its input and output relations. An overview of recent research in the area of virtual analog modeling will be presented. Topics include antialiasing oscillator algorithms, virtual analog synthesizer filters, modeling of guitar pickups, spring reverberation units, ring modulators, carbon microphones, and audio antiquing. Virtual analog research can also open new opportunities beyond software versions of old technology. This talk will mention some examples of such possibilities.
Roderich Gross received a Diploma degree in computer science in 2001 from Dortmund University of Technology (Germany) and an M.Sc. in applied science and a Ph.D. degree in engineering sciences in 2003 and 2007 from the Universite Libre de Bruxelles (Belgium). From 2005-2007, he was a JSPS research fellow at the Tokyo Institute of Technology (Japan), a research associate with the School of Biological Sciences, University of Bristol (UK), and a Marie Curie Research Fellow at Unilever R&D Port Sunlight (UK). From 2008-2009 he was a Marie Curie Intra-European Fellow at the EPFL (Switzerland). From 2010-2013, he was a Lecturer in the ACSE department of the University of Sheffield (UK) and since 2014 he has been a Senior Lecturer in the same department, where he leads the Natural Robotics Lab (http://naturalrobotics.group.shef.ac.uk/). Dr Gross is an Associate Editor of the journal Swarm Intelligence, and of the robotics conferences IROS and ICRA.
Swarm intelligence refers to the phenomenon of a system of spatially distributed individuals that coordinate their actions in a decentralised and self-organised manner, so as to exhibit complex collective behaviour. This talk will present recent advances in controlling groups of robots. It is shown that some tasks can be solved by swarms of robots of severely limited abilities . We also present a method that is able to identify models of the individuals of a swarm through observation or interaction [2,3]. This method does not require any pre-defined metrics to gauge the resemble of models to the observed individuals.
 Self-organized aggregation without computation, International Journal of Robotics Research, http://dx.doi.org/10.1177/0278364914525244
 A Coevolutionary Approach to Learn Animal Behavior Through Controlled Interaction, GECCO 2013, http://dx.doi.org/10.1145/2463372.2465801
 Coevolutionary Learning of Swarm Behaviors Without Metrics, GECCO 2014 (in press)
Dr Moore is a Research Associate in Speech and Audio Processing at Imperial College London where he is working on signal analysis for law enforcement applications and dereverberation for VoIP and robot audition. He obtained the MEng degree in Electronic Engineering with Music Technology Systems from the University of York in 2005. Here he remained to work on room acoustic modelling using time domain methods as a Research Assistant before commencing his PhD under the supervision of Tony Tew.
Dr Moore's PhD studies were in the field of binaural hearing and the long-standing problem of in-head localisation of auditory images, which is commonly experienced during headphone listening. The project, funded by France Telecom R&D, developed and validated a crosstalk cancellation system suitable for delivering high quality individualised binaural stimuli to listeners without the need for headphones.
Before returning to academia in 2012, Dr Moore spent three years as a Hardware Design Engineer at Pure developing digital radio and network audio systems for the consumer electronics market.
Identification and verification of the location in which a recording was made are important yet understudied topics in audio forensics. The recently introduced concept of ‘roomprints’ provides some first steps towards tackling these tasks. We define a roomprint as a quantifiable description of an acoustic environment which can be measured under controlled conditions and estimated from a monophonic recording made in that space. In this talk the various types of information which could be included in a roomprint will be reviewed based on their expected reliability and the feasibility of extracting them from a recording. Recent results from this ongoing research will be presented which show the efficacy of frequency-dependent reverberation time as an identifying feature.
John S. Thompson currently holds a personal chair in Signal Processing and Communications at the School of Engineering in the University of Edinburgh. His research interests currently include signal processing, energy efficient communications systems, and multihop wireless communications. He was deputy academic coordinator for the recent Mobile Virtual Centre of Excellence Green Radio project, which involved collaboration between five UK universities and a dozen international companies. During 2012-2014 he is serving as member-at-large for the Board of Governors of the IEEE Communications Society (Comsoc). He is also a distinguished lecturer for Comsoc in 2014-2015. He was technical programme co-chair for the IEEE Vehicular Technology Conference Spring in Dresden in 2013.
The Recent Green Radio Research Programme in the UK was a major collaboration between academic and industrial researchers. The main aim of the project was to try to reduce the carbon footprint of mobile wireless networks. Recent work has shown that mobile base stations account for a significant portion of the energy consumed in such networks. Therefore the programme focussed on designing more efficient base station designs as well as new concepts to reduce energy in networks as a whole. This talk will give an overview of the research and some of the key findings as well as describing future directions, specifically relating to a new project in the area of smart grid technology.
Professor Alexandre (Alex) Yakovlev was an EPSRC Dream Fellow of EPSRC in 2011-12 to investigate different aspects of energy-modulated computing. He received D.Sc. from Newcastle University in 2006, and M.Sc. and Ph.D. from St. Petersburg Electrical Engineering Institute in 1979 and 1982 respectively, where he worked in the area of asynchronous and concurrent systems since 1980, and in the period between 1982 and 1990 held positions of assistant and associate professor at the Computing Science department. Since 1991 he has been at the Newcastle University, where he is a professor and leads the microSystems research group at the School of Electrical and Electronic Engineering. His main interests and publications are in the field of modelling and design of asynchronous, concurrent, real-time, real-power systems and autonomous systems for survival.
For more information: http://async.org.uk ; http://www.ncl.ac.uk/eee/staff/profile/alex.yakovlev
The traditional approach to designing power-aware computing systems is based on optimizing the energy consumption of a system for a given set of operating conditions, such as power supply, temperature range etc., and for requirements on performance, such as throughput and reliability.
For systems that are significantly power-constrained, such as autonomous or implanted electronic devices, energy usage is an essential factor in the system’s requirements, and not just an optimization criterion. In this type of systems, the behavioural profile of the system is determined by both power delivery and information flow, often intertwined. In the extreme case, even the information can enter the system in the form of energy. For example, consider a system of sensors monitoring the energetic field (mechanical, thermal or photovoltaic) of some area. Here, the energy of each point in the field is both the driver of the sensor’s activity and the source of data. Design of such systems must be holistic in the sense that both information and energy paths have to be considered in close interaction. Making only part (in time or in space) of the system’s functionality energy-efficient, for example, when its computational load is guaranteed a well-regulated power source, while the energetic cost of voltage regulation is ignored, would be wrong. At present, there is no sound theory and methodology of designing systems that are energy-modulated or what we may call here “real-power systems”. Systems are not sufficiently power-proportional, i.e. their functionality, e.g. computation activity, is not proportional to energy consumption. One of the stumbling blocks is in the domain of timing, which is usually determined by a clock generator, whose operation is not directly related to the energy source.
Self-timed or asynchronous systems design offers ways to building systems that are both robust and efficient for the above-mentioned regimes of work. This talk will look at a number of systematic techniques for designing systems with more predictable energy consumption from the transistor level upwards. It will also illustrate this potential of self-timed circuits with a number of examples, including speed-independent SRAM, reference-free voltage sensor, self-timed microprocessor, and voltage regulation for sporadic and intermittent power supply.
Recently, sound source separation technologies were used to make stereo upmixes from the original mono recordings for a number of songs by the Beach Boys. These were released on a number of album reissues in 2012. For these songs, true stereo mixes could not otherwise be created as some or all of the multitrack tapes were missing, or there were significant parts which were added live during mixdown. To overcome this, sound source separation technologies were used to extract sources from the original mono masters, and the extracted sources used to create stereo versions of the original recordings. This talk will provide an overview of the technologies used, including factorisation based techniques, and median filtering based techniques for both vocal and percussion separation, as well as user assisted separation in cases where parts of the multitracks were available. It will also highlight some of the issues encountered when deploying sound source separation technologies for upmixing in the real world.
Dr Derry FitzGerald is a senior Post-Doctoral Researcher in the NIMBUS Centre at Cork Institute of Technology. He was a Stokes Lecturer in Sound Source Separation algorithms at the Audio Research Group in DIT from 2008-2013. Previous to this he worked as a post-doctoral researcher in the Dept. of Electronic Engineering at Cork Institute of Technology, having previously completed a Ph.D. and an M.A. at Dublin Institute of Technology. He has also worked as a Chemical Engineer in the pharmaceutical industry for some years.
In the field of music and audio, he has also worked as a sound engineer and has written scores for theatre. He has recently utilised his sound source separation technologies to create the first ever officially released stereo mixes of several songs for the Beach Boys, including Good Vibrations, Help me Rhonda and I get around.
His research interests are in the areas of sound source separation, upmixing from mono to stereo, tensor factorizations, automatic music transcription and music information retrieval systems.
Dr. Poonam Yadav is a research associate at London e-science Center and Social Computing Group, Computing Department at Imperial College London. Previously, she worked as a visiting researcher at US Army Research Labs, Adelphi, Maryland and a supplement researcher with IBM Watson Research Centre on ITA (International Technology Alliance) project. She received her PhD from Distributed System and Network Group, Computing Department, Imperial College London in 2011. She is a recipient of the prestigious UK-India Education and Research Initiative (UKIERI) fellowship and Imperial Volunteer Award. Her research interests include Wireless and Distributed Networks, Cloud Computing, Software Define Networking, Internet of Things (IoT), Machine to Machine (M2M) Networking, Complex and Dynamical Systems.
In recent years, the networks of low-power devices have gained popularity. Deployments of such technologies range from smart cars and cities to precision agriculture. Typically these devices are wireless and battery powered, and where deployed as the Machine to Machine (M2M) networks, Wireless Sensor Networks (WSNs) or Internet of Things (IOT), they form a system larger than the sum of their parts. The self-coordination among these devices is a challenging task in the absence of a central control. This talk presents a bio-inspired coordination scheme, which is fully de-centralised and tolerant of disturbances caused by faulty nodes, wireless link failures, contention and interference for these self-organising networks.
The control and prediction of complex chemical systems is a very hard problem due to the nature of the interactions, transformations and processes occurring. From self-assembly to catalysis and self-organisation, complex chemical systems are often heterogeneous mixtures that at the most extreme exhibiting system level functions for instance that could be observed in a living cell. In this talk I will outline an approach to understand and explore complex chemical systems using an automated reactor platform to control chemical unit operations according to a well-defined program. By investigating the system not just at the molecular level, but by characterising the spatio-temporal dynamics, the aim is to understand how to control system level emergence of complex chemical behaviour and even view the system-level behaviour as a programmable entity capable of information processing. In particular I will discuss our ideas for embodying evolutionary algorithms into wet chemical formats attempting to explore ways of developing artificial living systems beyond biology leading to so-called ‘inorganic biology’.
Lee Cronin FRSE. Professional Career: 2013-Regius Professor of Chemistry. Alexander von Humboldt research fellow (Uni. of Bielefeld); 1997-1999: Research fellow (Uni. of Edinburgh); 1997: Ph.D. Bio-Inorganic Chemistry, Uni. of York; 1994 BSc. Chemistry, First Class, Uni. of York. Prizes include 2013 BP/RSE Hutton Prize, 2012 RSC Corday Morgan, 2011 RSC Bob Hay Lectureship, a Wolfson-Royal Society Merit Award in 2009, Election to the Royal Society of Edinburgh in 2009. The focus of Cronin’s work is understanding and controlling self-assembly and self-organisation in Chemistry to develop functional molecular and nano-molecular chemical systems; linking architectural design with function and recently engineering system-level functions (e.g. coupled catalytic self-assembly, emergence of inorganic materials and fabrication of inorganic cells that allow complex cooperative behaviours). Much of this work is converging on exploring the assembly and engineering of emergent chemical systems aiming towards ‘inorganic biology’. This work has been presented in over 250 papers and 220 lectures worldwide. It is also worth pointing out that the expertise in the Cronin group is unique bringing together inorganic chemists, chemical engineers, complex system modelling, evolutionary theory, robotics and AI.
Can digital computers help us create new analogue computational devices?...
NASCENCE is an recently funded 2.9M euros EU project in Unconventional computation. The aim of the NASCENCE project is to model, understand and exploit the behaviour of evolved configurations of nanosystems (e.g. networks of nanoparticles, carbon nanotubes, liquid crystals) with the long term goal to build information processing devices exploiting these architectures.
The methodology behind this is called evolution-in-materio (EIM). In EIM, computers running evolutionary algorithms are used to define configurations and magnitudes of physical variables (e.g. voltages) which are applied to material systems so that they carry out useful computation.
One of the potential advantages of this is that artificial evolution can potentially exploit physical effects that are either too complex to understand or hitherto unknown.
Here in York, we have recently shown how it is possible to solve instances of Travelling Salesman Problems very efficiently using EIM. This appears to be the first time that configurations of materials have been evolved to solve classically difficult comptational problems.
In this talk, the speaker will give an overview of his current research work in the area of wireless ad-hoc, mesh and sensor networks at Imperial College. By focusing on vehicular networks, the speaker will present new stochastic traffic models for vehicular ad-hoc networks (VANETs) in urban environments and their applications to quantify communication connectivity and identify locations for placing road-side communication nodes to optimize connectivity. Results on distributed optimization for ad-hoc networks with power control will be discussed. The talk will then be concluded with a discussion on future work to extend the traffic models, optimization techniques and cross-layer protocol designs for VANETs.
Kin K. Leung received his B.S. degree from the Chinese University of Hong Kong in 1980, and his M.S. and Ph.D. degrees from University of California, Los Angeles, in 1982 and 1985, respectively.
He joined AT&T Bell Labs in New Jersey in 1986 and worked at its successor companies, AT&T Labs and Bell Labs of Lucent Technologies, until 2004. Since then, he has been the Tanaka Chair Professor in the Electrical and Electronic Engineering (EEE), and Computing Departments at Imperial College. He is the Head of Communications and Signal Processing Group in the EEE Department. His research interests focus on networking, protocols, optimization and modeling of wireless broadband, sensor and ad-hoc networks. He also works on multi-antenna and cross-layer designs for the physical layer of these networks.
He received the Distinguished Member of Technical Staff Award from AT&T Bell Labs in 1994, was a co-recipient of the 1997 Lanchester Prize Honorable Mention Award, and was elected as an IEEE Fellow in 2001. He received the Royal Society Wolfson Research Merits Award from 2004 to 2009, and was elected as member of Academia Europaea in 2012. He serves as a member (2009-11) and the chairman (2012-13) of the IEEE Fellow Evaluation Committee for Communications Society. He has also served an editor and guest editor for a number of IEEE and ACM journals.
Mobile phone systems have advanced dramatically over the last 20 years, but trying to use a phone in a stadium, music festival etc, or after a natural disaster can prove impossible. FP7 ABSOLUTE, a three-year industrially-led project is trying to change all that. It is developing a new communications architecture that can be overlaid on an existing LTE-A (4G) network to provide supplemental capacity and priority access for first responders. This is achieved using a mixture of aerial platform base stations (located on Helikites – a hybrid tethered aerostat/kite) and portable terrestrial base stations. This talk will discuss how a temporary network can be established in terms of roll-out and roll-back. It will also consider how to deal with constraints of limited radio spectrum, energy, and the logistics in such scenarios. Specific attention will be paid to cognitive techniques based on reinforcement learning and transfer learning that are under development at York, which help the system learn to rapidly adapt to changing circumstances. Finally, future directions for research in this area will be outlined.
Please contact Juri Kirby, Research Support Office, for more information.