Internship Projects

Internship Title

Analyzing the Social Behaviours of Computer Vision Algorithms

Description of Internship There are increasing expectations that algorithms should behave in a manner that is socially just. We consider the case of computer vision APIs and their interpretations of people images. Such services have become indispensable in our information ecosystem, facilitating new modes of visual communication and sharing. But while they offer developers a convenient means to add functionality to their creations, most are opaque and proprietary. Many have criticized the way they perform and judge people’s photos and their overall algorithmic fairness to the ground truth. These services are often making judgments on a person’s physical appearance. How do these judgments change when controlling or modify parts of the facial characteristics on a person's photo? What are the most crucial parts for the algorithms that can influence their decisions? Consequently, how is their objective and/or subjective behavior being affected?
Required Skills Basic knowledge in image processing or computer vision or deep learning, Python
Level of required Skills Basic
Internship Objectives The aim of the project is to develop tools for manipulating the physical facial characteristics in a persons’ photo and use the groups’ prior research tools to study the behavior of computer vision services  such as Google Vision, Amazon Rekognition, IBM Watson, Microsoft FACE, Clarifai and Imagga. The project will involve work in data collection and analysis.
Expected Deliverables TBD
Internship Title

Discovering the spread of (mis)information about COVID-19

Description of Internship The pandemic of COVID-19, informally known as “#CoronaVirus”, made its way to Cyprus in early March 2020. With a close-knit culture exacerbated by the self-quarantines, the population turned online to find crucial information, often from their friends’ posts on social media. However, it is clear that some of the information people encounter are not from the authorities on COVID-19 or infections; instead, there is a lot of misinformation, accelerated by the global panic. We aim to discover where Cypriots turn to, in order to receive information in the moment of a crisis, especially when they are confined to their homes. Through this process, we may also find which information sources they find trustworthy
Required Skills Knowledge in psychology, sociology, or other social sciences; Basic knowledge in statistics and probability; Reading and writing skills in English; Greek and/or Turkish an advantage
Level of required Skills Good.
Internship Objectives The project will gather information from people all around Cyprus about their online habits/behaviors, their information sources, and beliefs. Our aim is to reach a representative sample around Cyprus, design a survey or other data collection method and analyze the results to find information to reliably gauge how and where people find information in a global health crisis
Expected Deliverables Data on the average digital literacy of Cypriots; Literature review on information access and sharing habits in health crises; Suggestions for the government and NGOs for information dissemination
Internship Title

Exploring the impact of a pandemic on algorithmic transparency

Description of Internship The World Health Organization (WHO) has categorized COVID-19 as a pandemic. This is the first time in the modern era that a coronavirus has affected everyday life in such a drastic way. Physical interactions are reduced to minimal while human interactions over social media applications have spiked. In a world that is interconnected more than ever over the Internet an enormous amount of new data is created by the hour. A significant amount of the produced data is fed back into machine learning algorithms created to facilitate our interaction with an application or provide us a more personalized experience over the Web. How these new data created in the moment of a pandemic affect machine learning algorithms? What are the possible measures to be taken?
Required Skills Machine learning, Programming skills (Python or R), English
Level of required Skills Basic to intermediate
Internship Objectives The project will identify the possible sources of data affected or impaired as a result of a pandemic outbreak. It will explore the implications of using these data in machine learning algorithms used broadly over the Web (i.e., recommendation systems). As a final step methods and techniques will be proposed for risk mitigation.
Expected Deliverables Review of literature, Collection/analysis of data and/or Demo system

The applicants may address any technical or research related inquiries to the Research Office at

Subscribe to our Newsletter

* indicates required