See How Your Research Aligns
Create a free account to analyze your research alignment,
identify potential research gaps, and generate personalized
application documents for this professor.
Create Free Account
Banafsheh Rekabdar
Reinforcement Learning
Variational Autoencoders (VAEs)
Diffusion Models
Robust Machine Learning
Multimodal Machine Learning
About
I’m an Assistant Professor in the Department of Computer Science at Portland State University and Director of the Artificial Intelligence Lab.
My research focuses on reinforcement learning and generative AI (e.g., VAEs, diffuison models), with an emphasis on robust and multimodal machine learning. I develop learning methods for decision-making, perception, and real-world deployment.
Research Performance Summary
2012-2026
Active Research Span
First Recorded Paper
Artificial neural network ensemble approach for creating a negotiation model with ethical artificial agents
Year:
2012
Citations:
11
Venue:
International Conference on Artificial Intelligence and Soft Computing
Latest Recorded Paper
Spike Timing Dependent Plasticity Organizes Type Ia Muscle Afferents in a Synthetic Nervous System
Year:
2026
Citations:
0
Venue:
Conference on Biomimetic and Biohybrid Systems
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Rekabdar
Nicolescu
Mousas
Research Impact by Period
Papers
10
Citations
6
Avg. Citations / Paper
0.6
H-Index
1
Papers
47
Citations
450
Avg. Citations / Paper
9.6
H-Index
13
Papers
29
Citations
501
Avg. Citations / Paper
17.3
H-Index
12
Papers
3
Citations
32
Avg. Citations / Paper
10.7
H-Index
3
Contact and Professional Links
Detected Research Keywords
Spatio Temporal Patterns
Spiking Neural Networks
Question Answering Knowledge
Answering Knowledge Base
Learning Spatio Temporal
Knowledge Base Language
Base Language Model
Language Model Embeddings
Classification Drainage Crossings
Resolution Digital Elevation