Freelancers using FastAPI in Paris
Freelancers using FastAPI in Paris
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Ismail ait-lahssen
Production-oriented ML system built with a modular architecture separating data processing, feature engineering, inference, API services, persistence, and training pipelines for scalable and maintainable deployment workflows.
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40
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Sathwika Bandaru
Collaborative project, contributed key production components of Med-V²QA, a clinical Visual Question Answering system built on the MUMC architecture for radiology image analysis. My contributions: built the Dual-Gate Guardrail System (Gate 1 rejects non-medical intent, Gate 2 uses a local CLIP classifier to reject non-medical images ensuring clinical safety and system focus); developed the Batch Triage module using zero-shot CLIP to automatically sort and prioritise the most abnormal scans from uploads of up to 20 images; integrated Voice I/O using OpenAI Whisper for speech-to-text transcription and gTTS for audio readout of answers; built the PDF report generation module producing structured clinical reports with patient data, notes, and VQA results; and developed the FastAPI backend handling high-performance async request processing across all services. Built as part of a team my work covered the safety layer, multimodal I/O, clinical reporting, and backend API infrastructure.
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20
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Lionel Owono
Electronic Document Management (EDM) AI Application
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5
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Sathwika Bandaru
Built a Medical NLP system that processes clinical text to extract healthcare entities, redact sensitive information, and structure unstructured medical data using NER pipelines and FastAPI for backend integration.
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