Amjad Mohamed Haider

Kempten University of Applied Sciences

Papers

1

Total Citations

2

H-Index

1

About

Dr. Amjad Mohamed Haider is a leading researcher at the intersection of machine learning, embedded systems, and control theory, with a primary focus on enabling sophisticated neural network controllers (NNCs) for resource-constrained mobile platforms. His most notable contribution is the development of **COM-PACT (COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models)**. This pioneering framework directly addresses the critical challenge of deploying deep neural networks on devices with severe hardware limitations, such as mobile robots, wearables, and IoT systems. By introducing a component-aware pruning strategy within latent space models, Dr. Haider’s work achieves significant computational acceleration without sacrificing control performance, bridging the gap between high-accuracy AI and real-world, low-power deployment. His research is pivotal for the next generation of autonomous systems, where efficiency is paramount. With his highly cited work already shaping the field, Dr. Haider is recognized for his practical, systems-oriented approach to AI, making him a key figure in the advancement of intelligent, on-device control.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
COM-PACT: COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models
2 citations · 2026
📈 Most Prolific Year: 2026 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Kempten University of Applied Sciences

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago