Dr. Tiganj's research interests combine artificial intelligence, cognitive science and computational neuroscience with the objective of building artificial agents that can learn in an unsupervised manner from temporal and spatial regularities in the real world. Domains of application include reinforcement learning, spatial navigation, natural language processing and computer vision.
- Cognitive Science
- Computational Neuroscience
- Using structured neural representation for learning cognitive programs.
- Building time-aware machine intelligence through timeline-augmented neural networks.
- Using machine learning methods to identify temporally modulated neural populations.
- Studying how time and space are represented in the human brain through behavioral experiments.
- artificial intelligence, cognitive science and computational neuroscience