
Ozge Nilay Yalcin- PhD
- Professor (Assistant) at Simon Fraser University
Ozge Nilay Yalcin
- PhD
- Professor (Assistant) at Simon Fraser University
About
28
Publications
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Introduction
Current institution
Publications
Publications (28)
"How does the person in the bounding box feel?" Achieving human-level recognition of the apparent emotion of a person in real world situations remains an unsolved task in computer vision. Facial expressions are not enough: body pose, contextual knowledge, and commonsense reasoning all contribute to how humans perform this emotional theory of mind t...
AI-driven personalized support can help students learn from Open-Ended Learning Environments (OELEs). In this paper, we focus on how to effectively provide repeated hints in OELEs, when students repeat a sub-optimal behavior after receiving a hint on how to recover from the first occurrence of the behavior. We formally compare two repeated hint des...
Research has shown that free-form Game-Design (GD) environments can be very effective in fostering Computational Thinking (CT) skills at a young age. However, some students can still need some guidance during the learning process due to the highly open-ended nature of these environments. Intelligent Pedagogical Agents (IPAs) can be used to provide...
Recent advances in reinforcement learning with social agents have allowed such models to achieve human-level performance on certain interaction tasks. However, most interactive scenarios do not have performance alone as an end-goal; instead, the social impact of these agents when interacting with humans is as important and largely unexplored. In th...
Recent advances in reinforcement learning with social agents have allowed such models to achieve human-level performance on specific interaction tasks. However, most interactive scenarios do not have a version alone as an end goal; instead, the social impact of these agents when interacting with humans is as important and largely unexplored. In thi...
Data is the most powerful decision-making tool at our disposal. However, despite the exponentially growing volumes of data generated in the world, putting it to effective use still presents many challenges. Relevant data seems to be never there when it is needed - it remains siloed, hard to find, hard to access, outdated, and of bad quality. As a r...
Recent advances in reinforcement learning with social agents have allowed us to achieve human-level performance on some interaction tasks. However, most interactive scenarios do not have as end-goal performance alone; instead, the social impact of these agents when interacting with humans is as important and, in most cases, never explored properly....
There is a growing recognition that artists use valuable ways to understand and work with cognitive and perceptual mechanisms to convey desired experiences and narrative in their created artworks (DiPaola et al., 2010; Zeki, 2001). This paper documents our attempt to computationally model the creative process of a portrait painter, who relies on un...
Computational modeling of empathy has recently become an increasingly popular way of studying human relations. It provides a way to increase our understanding of the link between affective and cognitive processes and enhance our interaction with artificial agents. However, the variety of fields contributing to empathy research has resulted in isola...
M-Path is an embodied conversational agent developed to achieve natural interaction using empathic behaviors. This paper is aimed to describe the details of the conversational management system within the M-Path framework that manages dialogue interaction with an emotional awareness. Our conversational system is equipped with a goal-directed narrat...
Empathy is a complex socio-emotional behavior that results from the interaction between affective and cognitive mechanisms. Equipping embodied conversational agents (ECAs) with empathic capacity can benefit from the integration and evaluation of these low and high level capabilities in a hierarchical manner. Following the theoretical background on...
The novel research area of computational empathy is in its infancy and moving towards developing methods and standards. One major problem is the lack of agreement on the evaluation of empathy in artificial interactive systems. Even though the existence of well-established methods from psychology , psychiatry and neuroscience, the translation betwee...
This paper is intended to outline the PhD research that is aimed to model empathy in embodied conversational systems. Our goal is to determine the requirements for implementation of an empathic interactive agent and develop evaluation methods that is aligned with the empathy research from various fields. The thesis is composed of three scientific c...