Dr Salem Ameen
School of Science, Engineering & Environment
Current positions
Lecturer
Biography
Dr Salem Ameen is a Lecturer in Artificial Intelligence, Robotics and Automation at the University of Salford. His research focuses on efficient and robust artificial intelligence, deep-learning model optimisation, computer vision, robot perception and autonomous systems.
He completed his PhD at the University of Salford in 2017. His doctoral research investigated the optimisation of deep neural networks using multi-armed bandit methods. His subsequent work has included neural-network pruning, model compression, efficient AI deployment, RGB-D computer vision and machine learning for robotics and healthcare applications.
Dr Ameen teaches across Levels 3 to 7 in artificial intelligence, mobile robotics, automation and robotics, mechatronics, interactive visualisation, numerical analysis, computing, probability and mathematics. He also contributes to programme and module delivery, assessment, moderation, student support and academic quality assurance.
He currently supervises one PhD researcher and multiple master’s dissertation and project students in artificial intelligence, machine learning, computer vision, robotics and autonomous systems. He welcomes enquiries from prospective postgraduate researchers whose interests align with these areas
Areas of Research
Efficient Deep Learning and Model Optimisation
Developing efficient and resource-aware deep-learning methods, including neural-network pruning, model compression, quantisation and deployment on resource-limited computing platforms.
Machine Learning and Reinforcement Learning
Investigating machine-learning and sequential decision-making methods, including multi-armed bandits, reinforcement learning and optimisation under uncertainty.
Computer Vision and Robot Perception
Developing robust perception methods for robotics and automation, including RGB-D sensing, scene understanding and perception in challenging environments involving glass, mirrors and reflective or transparent surfaces.
Robotics and Autonomous Systems
Applying artificial intelligence, machine learning and perception methods to mobile robotics, autonomous systems and intelligent automation.
Multimodal and Vision-Language AI
Exploring methods that combine visual, spatial and language information for perception, reasoning and decision support. This is a developing area within the wider research programme.
AI for Healthcare and Automation
Applying machine learning and intelligent decision-making methods to healthcare, diagnostics, automation and engineering systems.
Areas of Supervision
PhD Topics
Deep Learning
Efficient Deep Learning
Transformer Models
Vision Transformers
Multimodal AI
Vision-Language Models
Spatial Reasoning in AI
Common-Sense Reasoning for Intelligent Systems
Embodied AI
World Models and Predictive Representation Learning
Computer Vision
Robot Perception and Sensing
RGB-D Perception in Challenging Environments
Autonomous Systems
Human-Robot Interaction
Machine Learning for Healthcare
AI for Automation and Intelligent Systems
Dr Ameen teaches across foundation, undergraduate and postgraduate levels. His teaching combines theoretical understanding with programming, simulation, practical examples and project-based problem solving.
Level 7
Artificial Intelligence
Mobile Robotics
Interactive Visualisation
Automation and Robotics
Mechatronics
Level 5
Numerical Analysis
Computing Laboratory: Numerical Methods and Simulation
Level 4
Probability
Mathematics and Computing
Level 3
Mathematics 1
Mathematics 2
He also supervises postgraduate dissertations and applied projects in artificial intelligence, machine learning, computer vision, robotics and autonomous systems. His teaching approach supports students in moving from theory to implementation while developing critical thinking, technical communication and independent problem-solving skills.
Qualifications
-
Machine Learning and Artificial Intelligence
2013 - 2017 -
Computer Science and Engineering
2007 - 2009