Welcome 😃
My name is Wadhah, and I am pursuing my PhD at the L3S Research Center in Germany. As a scientific researcher, I enjoy using my skills to contribute to the exciting technological advances happening every day in the field of artificial intelligence. I graduated from Bielefeld University in 2022 with a Master’s degree in Intelligent Systems.
My research interests include artificial intelligence, tactile sensing for robots, machine learning, reinforcement learning, robotics, and computer vision.
If you are interested in discussing these topics, feel free to contact me 😊.
Publications
Transferring Tactile Data Across Sensors
Wadhah Zai El Amri, Malte Kuhlmann, and Nicolás Navarro-Guerrero (2024). "Transferring Tactile Data Across Sensors." in 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA@40), Rotterdam, The Netherlands, Sept. 2024, pp. 1540–1542.
Optimizing BioTac Simulation for Realistic Tactile Perception
Wadhah Zai El Amri, Nicolás Navarro-Guerrero (2024). "Optimizing BioTac Simulation for Realistic Tactile Perception." 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, pp. 1-8, doi: 10.1109/IJCNN60899.2024.10650656..
A Review of the Role of Causality in Developing Trustworthy AI Systems
Niloy Ganguly, Dren Fazlija, Maryam Badar, Marco Fisichella, Sandipan Sikdar, Johanna Schrader, Jonas Wallat, Koustav Rudra, Manolis Koubarakis, Gourab K. Patro, Wadhah Zai El Amri, and Wolfgang Nejdl (2023). "A Review of the Role of Causality in Developing Trustworthy AI Systems." arXiv:2302.06975.
Hierarchical Decentralized Deep Reinforcement Learning Architecture for a Simulated Four-Legged Agent
Wadhah Zai El Amri, Luca Hermes, Malte Schilling (2022). "Hierarchical Decentralized Deep Reinforcement Learning Architecture for a Simulated Four-Legged Agent." In: Nicosia, G., et al. Machine Learning, Optimization, and Data Science. LOD 2022. Lecture Notes in Computer Science, vol 13811. Springer, Cham. https://doi.org/10.1007/978-3-031-25891-6_20.
Transfer Learning with Jukebox for Music Source Separation
Wadhah Zai El Amri, Oliver Tautz, Helge Ritter, Andrew Melnik (2022). "Transfer Learning with Jukebox for Music Source Separation." Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 647).
Open Set Task Augmentation Facilitates Generalization of Deep Neural Networks Trained on Small Data Sets
Wadhah Zai El Amri, Felix Reinhart, Wolfram Schenck (2022). "Open Set Task Augmentation Facilitates Generalization of Deep Neural Networks Trained on Small Data Sets." Neural Computing and Applications, 34, 6067–6083.