Taha Alfaqheri

I can help with practical AI and Machine Learning projects covering problem definition, data preparation, model selection, model evaluation and deployment planning. My experience includes: machine learning, deep learning, computer vision, GeoAI, remote sensing, Generative AI and foundation models. For a consultation session, I can review your proposed approach, discuss technical options and help identify realistic next steps.

Yes. We can review the business or technical problem, available data, expected outputs, constraints and potential risks. I can help assess whether AI/ML is appropriate, what modelling approaches could be considered, what data may be required and what a realistic Proof of Concept (PoC) or development roadmap could look like.

I can advise on GeoAI and Earth Observation (EO) applications using satellite, drone geospatial remote-sensing data, calibration field data. This can include image classification, semantic segmentation, change detection, environmental monitoring, other spatial ML applications. I can also discuss suitable EO data sources, processing pipelines, model approaches and validation considerations.

Yes. I can discuss practical Generative AI use cases, including target user analysis, RAG systems, prompt engineering, fine-tuning, AI assistants, foundation models, SLMs, LLMs, multimodal models and agent-based workflows. I can also help review architecture choices, data requirements, evaluation approaches, the common implementation risks.

Yes. A session can be used as a technical review or second opinion. We can look at the modelling approach, data pipeline, evaluation metrics, model limitations, deployment architecture or performance issues. Within the session I can help identify potential improvements and areas that may need further investigation.

Yes. I can help teams discuss technical and operational AI risks such as model reliability, hallucination, data quality, privacy, security, bias, model monitoring and human oversight. I can also discuss responsible AI and governance approaches from engineering perspective.

A 30m session is best suited to a focused question, technical discussion or second opinion. A 60m session allows more time to review the AI use case, architecture or modelling approach. A longer session can support a deeper technical review, identify risks and trade-offs, develop practical recommendations or next steps.

If possible, provide a short description of the problem you are trying to solve, your current approach, available data and any specific questions or challenges. Architecture diagrams, model results, requirements or other non-confidential technical information can also help us use the session effectively. If you are at an early idea stage, that is also fine, we can start by clarifying the problem and exploring suitable options.