Profile
Sukhpal Singh Gill is a Lecturer (Assistant Professor) in Cloud Computing at School of Electronic Engineering and Computer Science , Queen Mary University of London, UK. Prior to this, Dr. Gill has held positions as a Research Associate at the School of Computing and Communications, Lancaster University, UK and also as a Postdoctoral Research Fellow at CLOUDS Laboratory, The University of Melbourne, Australia. Dr. Gill is serving as an Associate Editor in ETT Wiley and IET Networks Journal. He has co-authored 70+ peer-reviewed papers published in prominent international journals and conferences such as IEEE TCC, IEEE TSC, IEEE TII, Elsevier JSS and IEEE CCGRID. His research interests include Cloud Computing, Fog Computing, Internet of Things and Energy Efficiency. For further information, please visit http://www.ssgill.me
Teaching
Cloud Computing (Postgraduate)
Cloud Computing has transformed how services and applications are delivered. Thanks to the rise of virtualisation technology and new programming paradigms, applications can quickly be delivered to a growing audience, without the need to physically own and configure the infrastructure. The Cloud Computing module will cover the main characteristics of Cloud Computing, including the enabling technologies, main software and service paradigms underpinning it, as well as related aspects, namely security, privacy, ethical concerns
Fundamentals of Web Technology (Undergraduate)
This is a module designed to offer you practical skills as well as understanding of underlying principles of programming the World Wide Web. There will be two hours of lectures per week, and weekly timetabled lab sessions for each student. Major topics you will study include Internet and Web server basics; client-side programming using XHTML; Cascading Style Sheets, and Javascript. You will develop practical skills in server-side programming using PHP and gain an understanding and hands on experience in the practical issues involved when setting up a website.
Semi-structured Data and Advanced Data Modelling (Postgraduate/Undergraduate)
In this module, student will learn to process XML (with XSLT and Java), to model data with XML (XML native, RDF), and to query XML data (XQuery). The module teaches many concepts of data modelling and knowledge representation that are beyond the syntactic issues of XML or RDF. The knowledge students acquire in the course is fundamental to the many data design and data analytics tasks occurring in todays IT and business landscapes. The second part of the module is dedicated to advanced DB concepts including active databases, mobile databases, spatial and temporal databases, triggers, performance tuning, distributed databases, indexing and query optimisation. The third part of the module covers the modern, agile world of data processing: NoSQL. It is about the processing of semi-structured data, transforming data streams into formats (triplets, JSON) to be processed by new DB systems (e.g. MongoDB, CouchDB). Overall, students will learn in this module to solve data and information management tasks as they typically occur in today's IT landscape.
