As a computer scientist and researcher with an engineering background from Epitech, I specialize in bridging the gap between advanced artificial intelligence research and production-grade software deployment. My experien…
As a computer scientist and researcher with an engineering background from Epitech, I specialize in bridging the gap between advanced artificial intelligence research and production-grade software deployment. My experience ranges from developing interpretable "white box" AI models for medical diagnostics at the Norwegian University of Science and Technology to building and containerizing automated NLP pipelines for cybersecurity at Predicta Lab. I leverage a versatile technical stack including Python, C++, and Docker to transform complex, unstructured data into scalable, high-performance solutions.
PhD at the Norwegian University of Science and Technology in applied artificial intelligence on medical data.
Worked as a programmer on various projects at the beginning or middle stages of development.
Researched and developed interpretable AI models (“white box”) to facilitate diagnosis based on medical datasets.
Engineered data processing and visualization software to streamline analysis for research teams.
Presented complex technical concepts to non-technical audiences at academic conferences.
Used Python (Pandas, Numpy, Scikit-learn, Tinker), C++ (QT), and Cuda.
Research and development of interpretable AI models (“white box”) to facilitate diagnosis based on medical datasets., Engineering data processing and visualization software to streamline analysis for research teams., Presenting complex technical concepts to non-technical audiences at academic conferences.
Predicta Lab provides advanced cybersecurity services focused on protecting clients from digital threats through Open Source Intelligence (OSINT) innovations.
Created, implemented, and tested various data processing programs for text, image, and raw data.
Developed and deployed data analysis pipelines using Natural Language Processing with Python (Numpy, Pandas, Scikit-learn) to process unstructured textual data.
Designed a data clustering algorithm optimized for efficiency using Scikit-learn.
Fine-tuned TensorFlow models for enhanced pattern recognition in image and text data.
Containerized and deployed applications using Docker and FastAPI.
Ensured reliability through comprehensive Pytest suites.
Creation, implementation, and testing of various data processing programs (text, image, raw data)., Development and deployment of data analysis pipelines using Natural Language Processing with Python (Numpy, Pandas, Scikit-learn) to process unstructured textual data., Design of a data clustering algorithm optimized for efficiency using Scikit-learn., Fine-tuned TensorFlow models for enhanced pattern recognition in image and text data., Containerized and deployed applications using Docker and FastAPI, and ensured reliability through comprehensive Pytest suites.
Developed a cross-platform mobile application for managing weather sensor data using Flutter.
Managed and optimized a MongoDB database.
Developed a cross-platform mobile application for managing weather sensor data using Flutter., Managed and optimized a MongoDB database.
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