Dr. Roie Melamed is a senior research staff member at IBM Research where he is working in the areas of indoor and outdoor location services, mobile backend services, and cloud. He holds a Ph.D., M.A. and B.A. (cum laude) degrees from the Technion – Israel Institute of Technology. He led research teams that developed technologies for numerous IBM products and offerings including Mobile Cloud Services (Bluemix), WebSphere Application Server, WebSphere eXtreme Scale and Tivoli Virtual Deployment Engine, and led successful proofs of concept with customers. He has won five major IBM awards, gave talks in tens of academic and IBM conferences, co-authored over a dozen publications and has more than 10 US patents being filed.
Indoor Localization: Challenges and Opportunities
Accurate indoor positioning can transform the retail, travel and transportation, and sports industries. For example, think of getting a mobile coupon for a shirt when you are standing near to it in a clothing store and turn-by-turn indoor navigation to the food booth with the shortest queue in airports and stadiums. While the Indoor Location market includes many new business opportunities (estimated around $4.5B by 2019), this emerging area suffers from shortcomings such as limited accuracy, complex maintenance of indoor sensing platforms and lack of data quality assessment tools.
This talk will review existing indoor positioning technologies and will discuss their aforementioned limitations. We will present new directions for mitigating these limitations, and we will focus on novel data smoothing algorithms for cleansing noisy indoor data. These algorithms open market opportunities supporting new indoor use cases such detection of common customer paths, targeted/wanderer customers and queues length. Finally, we will discuss future trends in indoor localization and how these technologies will be able to pin point you to a small grocery product in a large supermarket.
Monica S. Lam
Stanford University , USA
Dr. Monica Lam has been a Professor of Computer Science at Stanford University since 1988. She is the Faculty Director of the Stanford MobiSocial Computing Laboratory. She has worked in the areas of architecture, compiler optimization, software analysis to improve security, mobile and social computing. She received a PhD in Computer Science from Carnegie Mellon University in 1987. Lam is an ACM Fellow, received an NSF Young Investigator award in 1992, and has won a range of best paper awards from the ACM. She is a co-author of the “dragon book”, the most popular textbook in compilers. She is also the founding CEO of Omlet, a Stanford spinoff working to create an open social platform.
A Distributed Open Social Platform for Mobile Devices
Sharing is broken today. To share today, we have to get our friends to join some social network, share according to the rules of that network, while giving up ownership of our data. Why can’t we just share anything we want with any group of friends, directly from our phones to theirs, without worrying about creepy ads? The Omlet Social OS makes such kind of sharing possible. Technically, Omlet is a distributed semantic file system built on top of a real-time group messaging system Omlet where users can choose where to store their data. All mobile apps can be made social and inter-operate with each other, within the same open network, by just making APIs calls on the phone. This distributed architecture addresses privacy and scalability concerns and makes possible new paradigms such as a distribute internet of things.
University College London, London (UK)
Mark Harman is professor of Software Engineering in the Department of Computer Science at University College London, where he directs the CREST centre and is Head of Software Systems Engineering. He is widely known for work on source code analysis and testing and co-founded the field of Search Based Software Engineering (SBSE). SBSE research has rapidly grown over the past five years and now includes over 1600 authors, from nearly 300 institutions spread over more than 40 countries. A recent tutorial paper on SBSE can be found here: http://www.cs.ucl.ac.uk/staff/mharman/laser.pdf
Mobile App and App Store Analysis, Testing and Optimisation
This talk will present results on analysis and testing of mobile apps and app stores, reviewing the work of the UCL App Analysis Group (UCLAppA) on App Store Mining and Analysis. The talk will also cover the work of the UCL CREST centre on Genetic Improvement, applicable to app improvement and optimisation for properties such as performance and energy consumption. This keynote is based on joint work with colleagues at UCL, including Afnan Alsubaihin, Bobby Bruce, Anthony Finkelstein, Yue Jia, Bill Langdon, Ke Mao, Alexandru Marginean, Justyna Petke, William Martin, Federica Sarro and Yuanyuan Zhang at UCL. UCLAppA website: http://www0.cs.ucl.ac.uk/staff/F.Sarro/projects/UCLappA/UCLappA.html