2023 - Research.com Computer Science in Australia Leader Award
2020 - IEEE Fellow For contributions to haptically-enabled robotic systems
His primary scientific interests are in Artificial intelligence, Artificial neural network, Prediction interval, Data mining and Machine learning. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Computer vision and Pattern recognition. Saeid Nahavandi usually deals with Artificial neural network and limits it to topics linked to Control theory and Linear form and Control.
The concepts of his Prediction interval study are interwoven with issues in Simulated annealing, Electric power system, Minification, Uncertainty quantification and Coverage probability. His work in Data mining covers topics such as Cluster analysis which are related to areas like Unsupervised learning. In his study, Feedforward neural network and Control engineering is strongly linked to Fuzzy logic, which falls under the umbrella field of Machine learning.
His main research concerns Artificial intelligence, Computer vision, Control theory, Artificial neural network and Simulation. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His research in Computer vision is mostly focused on Segmentation.
The concepts of his Control theory study are interwoven with issues in Control engineering and Kinematics. His Artificial neural network study which covers Prediction interval that intersects with Coverage probability. He has included themes like Virtual training, Virtual reality, Human–computer interaction and Robot, Teleoperation in his Haptic technology study.
Artificial intelligence, Machine learning, Artificial neural network, Deep learning and Control theory are his primary areas of study. His research integrates issues of Computer vision and Pattern recognition in his study of Artificial intelligence. He is interested in Feature selection, which is a branch of Machine learning.
His studies deal with areas such as Uncertainty quantification, Prediction interval and Transfer of learning as well as Artificial neural network. Saeid Nahavandi combines subjects such as Robot and Mechanism with his study of Control theory. His study focuses on the intersection of Mechanism and fields such as Kinematics with connections in the field of Workspace.
His primary areas of investigation include Artificial intelligence, Machine learning, Deep learning, Control theory and Workspace. Saeid Nahavandi interconnects Computer vision and Pattern recognition in the investigation of issues within Artificial intelligence. His Machine learning research integrates issues from Baseline and CAD.
The various areas that Saeid Nahavandi examines in his Deep learning study include Transfer of learning and Reinforcement learning. His work carried out in the field of Control theory brings together such families of science as Robot, Mechanism and Synchronization. His Workspace research includes elements of Motion, Kinematics, Model predictive control, Simulation and Algorithm.
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Dynamic nanofin heat sinks
Pyshar Yi;Khashayar Khoshmanesh;Adam F. Chrimes;Jos L. Campbell.
Advanced Energy Materials (2014)
Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals
A Khosravi;S Nahavandi;D Creighton;A F Atiya.
IEEE Transactions on Neural Networks (2011)
Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances
A. Khosravi;S. Nahavandi;D. Creighton;A. F. Atiya.
IEEE Transactions on Neural Networks (2011)
Dielectrophoretic platforms for bio-microfluidic systems.
Khashayar Khoshmanesh;Saeid Nahavandi;Sara Baratchi;Arnan Mitchell.
Biosensors and Bioelectronics (2011)
Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications
Thanh Thi Nguyen;Ngoc Duy Nguyen;Saeid Nahavandi.
IEEE Transactions on Systems, Man, and Cybernetics (2020)
Comments on 'Information measure for performance of image fusion'
M. Hossny;S. Nahavandi;D. Creighton.
Electronics Letters (2008)
A Review of Vision-Based Gait Recognition Methods for Human Identification
Jin Wang;Mary She;Saeid Nahavandi;Abbas Kouzani.
digital image computing: techniques and applications (2010)
Construction of Optimal Prediction Intervals for Load Forecasting Problems
Abbas Khosravi;Saeid Nahavandi;Doug Creighton.
IEEE Transactions on Power Systems (2010)
Prediction Intervals for Short-Term Wind Farm Power Generation Forecasts
A. Khosravi;S. Nahavandi;D. Creighton.
IEEE Transactions on Sustainable Energy (2013)
Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication
Shanmugam Lakshmanan;Mani Prakash;Chee Peng Lim;Rajan Rakkiyappan.
IEEE Transactions on Neural Networks (2018)
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