Technische Universität Braunschweig
Institut für Informationssysteme
Mühlenpfordtstraße 23, 2.OG
D-38106 Braunschweig
Phone: +49 (531) 391 3103
Email: kinda.maarry@gmail.com
Room: 216
| Winter Semester 2016/2017 | "Data warehousing and Data Mining" Lecture |
| Summer Semester 2016 | Co-supervising the software development project SocialPal. |
| Winter Semester 2015/2016 | "Deductive Databases and Knowledge-Based Systems" Lecture |
| Summer Semester 2015 | "Data warehousing and Data Mining" Lecture |
| Winter Semester 2013/2014 | "Information Retrieval and Web Search Engines" Lecture |
| 2013 - present | Research Assistant at the Institute for Information Systems, University Carolo-Wilhelmina, Braunschweig. |
| 2011 - 2013 | - Earned the Internet Technologies & Information Systems M.Sc., Institute for Information Systems, University Carolo Wilhelmina, Braunschweig. |
| - Awarded the best M.Sc. thesis of the Faculty for Computer Science, Math, and Business Administration 2013. | |
| - Awarded the Niedersaechsische Technische Hochschule scholarship for excellent female ITIS students | |
| 2008 - 2010 | IT Administrator at Human soft, Taalum group, Doha, Qatar. |
| 2004 - 2008 | Earned the Information system and computer science BSc., Faculty of Computer and Information, Cairo University. |
Overview
In the era of Big Data, crowdsourcing has emerged as a flexible solution, which aid with the flood of data and the process of structuring it. By harnessing human intelligence from the crowd, many applications can be then steered, realizing the seamless integergated concept of Human Computation: combining start-of the-art algorithms’ unmatched computational power with the humans’ cognitive abilities and intellectual insights.
Crowdsourcing offers a cheap digital solution by tapping into a geographically dispersed network of people and creating open calls on its platform. Its virtual and highly distributed nature promotes it as a flexible solution. Yet this very nature also open doors to quality risks. In this virtual and anonymous nature, unethical workers and free riders can simply exploit the short term contracts that are offered by merely submitting random answers. This violation compromises the core gain of the crowd-sourcing services. And questions regarding the reliability and usability of the attained data materializes.
Crowd Evolution: Empower and Reap research comprises two directions:
1) Empowering the Crowd: Through realizing the vision of Impact sourcing and creating quality measures, which can reliably distinguish spammers, and honest low-skilled workers.
2) Reaping intelligent insights such as elicited rationals and relationships between attributes within data, etc.