The MSc poster presentations and project demonstrations took place this afternoon. We wish all of our MSc students good luck as they finish their dissertations and move closer to graduation!
Mirco Musolesi leaves the School today to start his new post in Birmingham. Thank you for the cakes from a local Royal supplier. Good luck and we will hopefully see you in St Andrews in the future.
The summer school “Advanced techniques in computer algebra systems development” is organised by the Centre of Interdisciplinary Research in Computational Algebra and supported by the Scottish Informatics and Computer Science Alliance (SICSA) and the EU FP6 project “SCIEnce – Symbolic Computation Infrastructure for Europe” Further details>>>
Mobile computing and sensing technologies present exciting opportunities for healthcare. Wireless sensors worn by patients can automatically deliver medical
sensor data to care providers, family members, or other caregivers, providing new opportunities to diagnose, monitor, and manage a wide range of medical
conditions. Using the mobile phones that patients already carry to provide connectivity between sensors and providers can help to keep costs low and
deployments simple. However, there are many security and privacy challenges involved in developing a system that will protect the patient’s privacy and the
integrity of the data collected. In this talk I describe the advent of these “mHealth” systems, survey the security and privacy issues, and describe research
underway at Dartmouth to address these challenges.
David Kotz is the Champion International Professor, in the Department of Computer Science, and Associate Dean of the Faculty for the Sciences, at Dartmouth
College in Hanover NH. During the 2008-09 academic year he was a Visiting Professor at the Indian Institute of Science, in Bangalore India, and a Fulbright
Research Scholar to India. At Dartmouth, he was the Executive Director of the Institute for Security Technology Studies from 2004-07. His research interests
include security and privacy, pervasive computing for healthcare, and wireless networks. He has published over 100 refereed journal and conference papers. He
is an IEEE Fellow, a Senior Member of the ACM, a member of the USENIX Association, and a member of Phi Beta Kappa.
After receiving his A.B. in Computer Science and Physics from Dartmouth in 1986, he completed his Ph.D in Computer Science from Duke University in 1991 and
returned to Dartmouth to join the faculty. For more information see http://www.cs.dartmouth.edu/~dfk/.
Research by Tom Kelsey and colleagues from Glasgow and Edinburgh into normative models of hormone levels has been featured in the Daily Telegraph, the Scotsman, and the Express. Read the original paper here.
St Andrews PhD student Lars Kotthoff has won the Best Student Paper award at the Fourth Annual Symposium on Combinatorial Search. His paper, co-authored by Ian Gent and Ian Miguel, has the title “A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems” and compares the performance of different Machine Learning techniques on several Algorithm Selection problems from the literature.
More information, including the paper, can be found on Lars’ website here.
Research by Ian Gent and Lars Kotthoff into the suitability of virtualised hardware for computational experiments is featured in a recent article of the HPC in the cloud site. The article contains a description of the research and an interview with Lars Kotthoff.
Read more at HPC in the cloud.
Speaker: Peterri Nurmi, Helsinki Institute for Information Technology HIIT
Abstract:
Contemporary mobile phones readily support different positioning techniques. In addition to integrated GPS receivers, GSM and WiFi can be used for position estimation, and other sensors such as accelerometers and digital compasses can be used to support positioning, e.g., through dead reckoning or the detection of stationary periods. Selecting which sensor technologies to use for positioning is, however, a non-trivial task as available sensor technologies vary considerably in terms of their energy demand and the accuracy of location estimates. To improve the energy-efficiency of mobile devices and to provide as accurate position estimates as possible, novel on-device positioning technologies together with techniques that select optimal sensor modalities based on positioning accuracy requirements are required. In this talk we first introduce novel GSM and WiFi fingerprinting algorithms that run directly on mobile devices with minimal energy consumption [1]. We also introduce our recent work on minimizing the power consumption of continuous location and trajectory tracking on mobile devices [2].
[1] P. Nurmi, S. Bhattacharya, J. Kukkonen: “A grid-based algorithm for on-device GSM positioning.” Proc. 12th ACM International Conference on Ubiquitous Computing (Ubicomp, Copenhagen, Denmark, September 2010). ACM Press, 2010, 227-236.
[2] M. B. Kjaergaard, S. Bhattacharya, H. Blunck, P. Nurmi, “Energy-efficient Trajectory Tracking for Mobile Devices”, Proc. 9th International Conference on Mobile Systems, Applications and Services (MobiSys, June-July, 2011).
About Petteri:
Dr. Petteri Nurmi is a Senior Researcher at the Helsinki Institute for Information Technology HIIT. He received a PhD in Computer Science from the University of Helsinki in 2009. He is currently co-leading the Adaptive Computing research group at HIIT together with Doc. Patrik Floréen. His research focuses on ubiquitous computing, user modeling and interaction with a view of making the life of ordinary people easier through easy-to-use mobile services. He regularly serves as Program Committee Member and reviewer for numerous leading conferences and journals. More information about his research can be found from the webpage of the research group: http://www.hiit.fi/adapc/
Speaker: Mirco Musolesi, Computer Science, University of St Andrews
Abstract:
Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, that can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of such technologies in these devices that are part of our everyday experience. Moreover, data extracted from the sensors can also be used to model people behaviour and movement patterns providing a very rich set of multi-dimensional data, which can be extremely useful for social science, marketing and epidemiological studies.
In this talk I will present some of my recent work in this area including the design and implementation of the CenceMe platform, a system that supports the inference of activities and other presence information of individuals using off-the-shelf sensor-enabled phones and of EmotionSense, a system for supporting social psychology research. Finally, I will discuss the issues related to the design of energy-efficient social sensing systems.
About Mirco:
Dr. Mirco Musolesi is a SICSA Lecturer at the School of Computer Science at the University of St. Andrews. He received a PhD in Computer Science from University College London in 2007 and a Master in Electronic Engineering from the University of Bologna in 2002. From October 2005 to August 2007 he was a Research Fellow at the Department of Computer Science, University College London. Then, from September 2007 to August 2008 he was an ISTS Postdoctoral Research Fellow at Dartmouth College, NH, USA, and from September 2008 to October 2009 a Postdoctoral Research Associate at the Computer Laboratory, University of Cambridge. His research interests lie in the broad area of mobile systems and networking with a current focus on intelligent mobile systems, online social networks, application of complex network theory to networked systems design, mobility modelling and sensing systems based on mobile phones. More information about his research profile can be found at the following URL: http://www.cs.st-andrews.ac.uk/~mirco
Calculator that returns chances of a live birth for a planned IVF cycle.
IVF-Predict Support.
IVFpredict was developed by Professor Scott Nelson and Professor Debbie Lawlor and published in PLOS Medicine.
In conjunction with Dr Tom Kelsey they have transformed this complex formula into a simple online and smartphone based calculator.
