Arshad Ahmed

I have developed a strong interest in working with medical and AI-driven datasets, especially those involving human behaviour, cognition, and neural patterns. My experience in neural data collection and multimodal annotation-ranging from video and image analysis to audio and text labeling—has helped me understand how high-quality data directly influences the accuracy of healthcare AI systems.

I enjoy the detailed and disciplined nature of annotation work, whether it involves tracking subtle facial cues, mapping eye movements, organising biomedical signals, or ensuring consistent dataset standards.

Over time, I’ve become comfortable using cloud-based annotation tools like AWS GroundTruth and GCP Vertex AI, along with manual, frame-by-frame annotation methods. What motivates me the most is contributing to meaningful AI applications that can support clinical research, improve diagnostics, or enhance patient experience.

I am now looking to grow in roles where I can work closely with medical data, collaborate with research-focused teams, and continue improving the quality and integrity of training datasets for advanced AI models.