Demonstrated professional experience as a senior data scientist, researcher, AI engineer. Proven experience working on various projects and concepts including large datasets, text analysis, natural language processing, healthcare analysis, knowledge representation and graph databases.
Over the course of my PhD, I worked on large graph databases, knowledge graphs, and machine learning, and then conducted most of my postdoctoral works on data science (machine learning, deep learning, NLP, image processing, data engineering…). These research skills were coupled with a concrete real-world application for Artificial Intelligence.
I frequently use tools/packages such as:
– Python (Scikit-learn, Pandas, Keras, Tensorflow).
– StanfordCore NLP, NLTK, spaCy.
– SQL, Neo4j, MongoDB.
To design/apply:
– Supervised, unsupervised, and advanced machine learning models.
– Healthcare analysis
– Text analysis,
– Image Recognition.
– Efficient Knowledge Query Answering with Graph Databases.
Areas of interest: #aiops, #machine_learning, #healthcare_analysis #artificial_intelligence