معرفی
Nadia M. Ady serves as a Postdoctoral Researcher in the Department of Computer Science at Aalto University, specializing in artificial intelligence with a focus on computational creativity and intrinsic motivation. Her research explores how to imbue machines with traits of creativity and curiosity through intrinsically motivated learning algorithms, particularly within reinforcement learning frameworks.
Her primary research interests span artificial intelligence, machine learning, and cognitive science, with specific emphasis on formalizing psychological concepts like curiosity and competence from Self-Determination Theory for AI applications. She investigates the landscape of intrinsically motivated learning algorithms, diversity progress in goal selection, and the implementation of specific curiosity mechanisms in machine learning systems. Her work bridges theoretical cognitive models with practical AI implementations, often addressing how human variables influence creative AI development.
Ady's publication record (2022-2025) reveals a strong interdisciplinary trajectory connecting cognitive science, reinforcement learning, and human-computer interaction. Key themes include the formal specification of competence needs in AI, discriminability-motivated goal selection, and applications of intrinsic motivation to virtual reality environments like dance visualization. Her research consistently addresses the challenge of translating human cognitive traits into computational frameworks while maintaining scientific rigor in modeling psychological constructs.
She actively collaborates within Professor Christian Guckelsberger's research group, working alongside researchers including Erik Lintunen, Sebastian Deterding, Markus Laattala, and Perttu Hämäläinen. This collaborative environment spans multiple disciplines, facilitating publications in premier venues such as the Cognitive Science Society, CHI Conference on Human Factors in Computing Systems, and the International Conference on Computational Creativity. Her current projects focus on formalizing curiosity mechanisms and exploring their applications in creative domains and human-AI interaction scenarios.
