Abdulmajid Murad
Om
I am a postdoctoral fellow at NorwAI, NTNU, connected to the DATA work package. My main research interests focus on using deep reinforcement learning, active learning, and GFlowNet to improve data efficiency, adaptation, and generalization of intelligent systems. I aim to help make intelligent systems accessible and add value with fewer resources by reducing dependence on big data.
PUBLICATIONS:
2023:
- Doctoral Thesis: Uncertainty-Aware Autonomous Sensing with Deep Reinforcement Learning. Trondheim, Norway: ntnu 2023 (ISBN 978-82-326-6974-5) 207 s.
NTNU
2021:
-
Murad, A.; Kraemer, F.A.; Bach, K.; Taylor, G.; Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting. Sensors 21(23), November 2021.
-
Klemsdal, E.; Herland, S.; Murad, A.; "Learning Task Agnostic Skills with Data-driven Guidance". ICML 2021 workshop on Unsupervised Reinforcement Learning, July 18--24, 2021, Vienna, Austria.
2020:
- Murad, A.; Kraemer, F.A.; Bach, K.; Taylor, G.; Information-Driven Adaptive Sensing based on Deep Reinforcement Learning. Proceeding of the 10th International Conference on the Internet of Things, October 4--9, 2020, Malmö, Sweden.
2019:
- Murad, A.; Kraemer, F.A.; Bach, K.; Taylor, G.; Autonomous Management of Energy-Harvesting IoT Nodes using Deep Reinforcement Learning. Proceeding of the IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), June 16--20, 2019, Umeå, Sweden.
- Murad, A.; Kraemer, F.A.; Bach, K.; Taylor, G.; IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning. Proceeding of the 9th International Conference on the Internet of Things, October 22--25, 2019, Bilbao, Spain.
2017:
- Murad, A.; Pyun, J.; Deep Recurrent Neural Networks for Human Activity Recognition. Sensors 17(11), November 2017.
Publikasjoner
2021
-
Murad, Abdulmajid ;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2021)
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.
Sensors
Vitenskapelig artikkel
2020
-
Murad, Abdulmajid ;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2020)
Information-Driven Adaptive Sensing Based on Deep Reinforcement Learning.
Association for Computing Machinery (ACM)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
2019
-
Murad, Abdulmajid Abdullah Yahya;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2019)
Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning.
IEEE (Institute of Electrical and Electronics Engineers)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Murad, Abdulmajid Abdullah Yahya;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2019)
IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning.
Association for Computing Machinery (ACM)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Tidsskriftspublikasjoner
-
Murad, Abdulmajid ;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2021)
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.
Sensors
Vitenskapelig artikkel
Del av bok/rapport
-
Murad, Abdulmajid ;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2020)
Information-Driven Adaptive Sensing Based on Deep Reinforcement Learning.
Association for Computing Machinery (ACM)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Murad, Abdulmajid Abdullah Yahya;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2019)
Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning.
IEEE (Institute of Electrical and Electronics Engineers)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
-
Murad, Abdulmajid Abdullah Yahya;
Kraemer, Frank Alexander;
Bach, Kerstin;
Taylor, Gavin.
(2019)
IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning.
Association for Computing Machinery (ACM)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Formidling
2019
-
PosterMurad, Abdulmajid Abdullah Yahya; Kraemer, Frank Alexander; Bach, Kerstin; Taylor, Gavin. (2019) IoT Sensor Gym: Training Autonomous IoT Devices with Deep Reinforcement Learning (Poster). IoT 20019 2019-10-22 - 2019-10-25