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Ali Abbasi
Affiliation
DTx—Digital Transformation CoLAB, University of Minho, Guimarães, Portugal
Topic
Incremental Learning,Neural Network,Catastrophic Forgetting,Long Short-term Memory,Optimization Problem,Accuracy Of Model,Angle Estimation,Batch Normalization Layer,Continuous Estimation,Cyber-physical Systems,Deep Neural Network,Federated Learning,Ground Station,Knee Joint Angle,Lifelong Learning,Low Earth Orbit,Optimization Algorithm,Previous Tasks,Root Mean Square Error,Test Scenarios,Threat Model,Training Data,sEMG Signals,Access Control,Accuracy In Scenarios,Accurate Estimation,Adam Optimizer,Additive Noise,Advanced Algorithms,Advanced Optimization,AlexNet,Artificial Neural Network,Attack Surface,Attention Mechanism,Attention-based Long Short-term Memory,Automatic Identification System,Baseline Algorithms,Battery State Of Charge,Biceps Femoris,Bidirectional Long Short-term Memory,Bilevel Optimization,Bilevel Optimization Problem,Bit Error,Bitrate,Brainwashing,Chest X-ray,Classical Optimization,Clean Data,Combined Set,Commercial Solver,
Biography
Ali Abbasi received the B.Sc. degree in electrical engineering from the University of Tehran, in 2020. He is currently pursuing the Ph.D. degree in computer science with the MINT Laboratory, Vanderbilt University, Nashville, TN, USA. His research interests include continual learning and bio-inspired neural networks, exploring their capabilities to effectively memorize, and selectively forget their past experiences.