Abdelahad CHRAIBI

* LexisNexis (Paris, France) My client is an international group with activities in professional publishing and the providing a wide range of information services, particularly in the legal, business, and academic fields. Achievements : I contributed to a challenging project in genAI focusing on the development of conversational agents using Large Language Models (LLMs). Through this initiative, I took on the following responsibilities: Collaborated with cross-functional teams to enhance AI models' conversational abilities and align with business objectives. Coordinated end-to-end pipeline operations for chatbot development, integrating data retrieval, preprocessing, embeddings, re-rankers, and LLM creation to ensure seamless workflow. Overcame complex data quality challenges, including retrievals, summarizers, embeddings, to optimize efficiency and maintain high accuracy standards for chatbot performance. Skills: Generative AI, ML, LLM, Langchain, Llama_index, Python, NLP, SQL, Prompt Engineering, Vector Databases, AWS, MLFlow, AzureDevOps * Orbit29 (London, UK) The major client mission is to move the dial and ensure health and wellbeing products are designed for engagement, scalability and impact. Achievements : I led a groundbreaking project in generative AI, focusing on the development of conversational agents using Large Language Models (LLMs) to improve health and wellbeing products. Through this initiative, I took on the following responsibilities: Orchestrated end-to-end pipeline operations for chatbot development, ensuring smooth workflow from data retrieval to model creation. Innovated prompt engineering to enhance AI models' conversational abilities, resulting in more engaging interactions with users. Overcame complex data processing challenges to optimize efficiency and accuracy in chatbot development. Skills: Generative AI, ML, LLM, Langchain, Llama_index, Python, NLP, SQL, Prompt Engineering, Chatbot, Vector Databases * Enedis (Lyon, France) I joined the primary manager of the public electricity distribution network in France, responsible for managing over 95% of the low and medium voltage network. My role was pivotal in optimizing power allocation during crises to serve the public interest. Achievements: Spearheaded a landmark initiative to optimize power allocation during crises, delivering the following key milestones: Led a crucial project focusing on power limitation during crises, ensuring network resilience and stability under pressure. Developed advanced predictive models for reconstruction of historical load curves for customer consumption and forecasting future consumption, enabling proactive management and efficient resource allocation. Implemented rigorous statistical validation to guarantee project reliability and maintain the highest standards of accuracy. Managed and analyzed massive datasets, prioritizing data quality for meaningful insights and accurate decision-making. Contributed significantly to crisis management efficiency by automating decision-making processes and streamlining communication channels. Skills: AI, ML, Time Series, Forecasting, Predective Analytics, Statistics, Python, Bitbucket, Jira, Confluence

Alicante is a company working in the innovation and healthcare fields to propose practical uses and solutions for patients and healthcare professionals using cutting-edge technologies to help them create value from the data they produce. In Alicante I have the mission of managing and developping AI and statistics projects, focused on medical data according to a CRISP-DM approach. I worked on several projects involving : •Automatic CIM-10 coding of hospital stays via NLP, ML, DL methods •Detection of pathologies, prevention and screening of long-term diseases •Prediction of length of stay and complications related to hospitalization •Synthesis, structuring and formatting of raw text using NLP methods •Anonymization, information extraction and automatic labeling on raw text •Pharmacovigilance and anomaly detection in drug prescriptions •Time series for prediction and monitoring of COVID-19 indicators •Medication monitoring from unstructured emails •Patient profiling and care pathway monitoring •Reinforcement Learning for classification under imbalanced data •End-to-End projects implementation

LAMIH is a multidisciplinary laboratory and a recognized research player in the fields of transport and mobility: non-polluting vehicles, intelligent transport, driving assistance, eco-driving, lightening of structures, transport logistics, mobility for all and intelligent mobility. In LAMIH I worked on conception and development of industrial models for decision support in different contexts related to the supply chain: •Optimization of Electric Vehicles Charging Stations Location Problem •Optimization/Simulation of Vehicle Routing Problem with inventory management •Optimizing the Planning of Surgical Operations in a stochastic environment •Scheduling of Preventive Maintenance •Optimization/Simulation of the Facility Layout Problem Assignments: • Research & Development Keywords: Operations Research; Combinatorial optimization; Vehicle routing problem; Design of assembly lines; Transportation ; Planning ; Hybridization; Metaheuristics • Supervision of Internships Keywords: Web development; Development of Mobile Applications; Java programming; C/C++ programming; RMI distributed programming; Layout of spaces; Operational research ; Combinatorial optimization; Simulation ; Emergency Department; Vehicle routing problem with inventory management (Inventory Routing Problem)

Designed and delivered engaging curriculum on programming languages, UML and project/inventory management resulting in successful student learning outcomes. Mentored and facilitated students to complete their projects successfully. Served as a valuable member of the evaluation board, assessing final projects and contributing to an objective assessment process. Skills : UML; Database; Operational research ; Project management; Simulation ; Quality Control ; Web development ; Quality audit; Layout of spaces; Combinatorial optimization; Metaheuristics; Mathematical programming