Software Engineer specialized in J2EE backend development. Team leader in an Agile startup environment delivering various services around Licensing, Monetization and e-Commerce.
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Leader of a 15 engineers team distributed across three countries (Switzerland, Singapore and Romania). Architect for an E-Commerce platform (see Digital Commerce) delivering catalog management and payments capabilities.
E-Commerce service to sell digital goods and manage their lifecycle.
Digital Commerce is a service allowing application developers to sell any type of goods and manage their lifecycle in a flexible, scalable and secure way. Besides providing a catalog management system and checkout capabilities, it offers the possibility to manage the inventory of (consumable) goods on a per consumer basis. Being exposed as a RESTful API, it can be used by any connected application.
After 7 months of development Digital Commerce is eventually feature-complete and validated with a real-life use case demonstrator but is currently not being operated in production. For more details you can refer to the documentation.
Self-service portal for cross-platform licensing.
Lotaris in-appCommerce is a self-service portal helping developers to monetize their (Mobile) applications. It is essentially a B2C adaptation of LiME. It was initially developed as an alternative licensing / payment platform for the Windows 8 ecosystem and later evolved to a more general store-independant licensing service (also for Android).
The service consists of a number of client SDKs (for Android, Windows 8, Windows Phone 8 and Windows Desktop) and a collection of Web tools allowing app developers to register, configure a licensing model for their app (with perpetual, time-limited and subscription licenses), access the integration guides and track their sales. The client SDKs expose an API to control access to premium features and trigger payment processes based on the licensing model configured on the Web tool.
B2B service to license Mobile Applications.
LiME is a service providing flexible licensing and in-app payment capabilities for Mobile applications. It was built and operated as a managed service to help major Software companies monetize their Mobile applications through various distribution channels (retail, OEM, mobile operators, app-stores), using various payment methods (credit card, premium SMS, mobile operator billing, retail scratch cards) and following various licensing models (fremium, perpetual licenses, fixed-length licenses, subscriptions).
The service, built for Android and iOS, uses a server-driven native UI payment experience. It means that from the consumer point of view, the UI is platform specific (using the platform native UI controls, not a Web view) but the screens are driven from the backend, which allows to dynamically change the payment process based on server configurations.
At the time of writing this (11/14), companies like Symantec and Capcom are still relying on LiME to monetize some of their Mobile applications.
Data-Mining techniques applied to content-based video retrieval systems.
In order to achieve true content-based information retrieval on video we should analyse and index video with high-level semantic concepts in addition to using user-generated tags and structured metadata like title, date, etc. However the range of such high-level semantic concepts, detected either manually or automatically, is usually limited compared to the richness of information content in video and the potential vocabulary of available concepts for indexing. Even though there is work to improve the performance of individual concept classifiers, we should strive to make the best use of whatever partial sets of semantic concept occurrences are available to us. We describe in this paper our method for using association rule mining to automatically enrich the representation of video content through a set of semantic concepts based on concept co-occurrence patterns. We describe our experiments on the TRECVid 2005 video corpus annotated with the 449 concepts of the LSCOM ontology. The evaluation of our results shows the usefulness of our approach.
N. Fatemi, F. Poulin, L. Raileanu, A. Smeaton, “Using association rule mining to enrich semantic concepts for video retrieval”, International Conference on Knowledge Discovery and Information Retrieval: KDIR’09, Funchal, Madeira, October 2009.