Lara Hassan

Masters in Computer Science Conducted research on data centers in desert environments, focusing on energy efficiency and optimization strategies for extreme climate conditions. Worked on Arabic NLP research during my first year, contributing to dialect identification and regional AI advancements. Master’s thesis: AI in Healthcare, with a focus on dermatology applications.

Leading the engineering team to build and maintain secure data storage systems. Managing projects from start to finish and mentoring the team for continuous improvement. Managing projects from inception to completion, ensuring timely delivery and high-quality outcomes. Mentoring the team to foster continuous improvement and professional growth.

Data engineer working on creating end-to-end pipelines to clean and process Real-Estate Data as well as providing a complete data intake service.

Researched and Investigated state-of-the-art Retrieval Augmented Generation algorithms. Deployed an end-to-end pipeline to query private Enterprise data. Applied iterative prompt engineering to achieve downstream task adaptation in legal scenarios via in-context learning.

- Worked on enhancing the functionality of Embedded Views Dashboard of Microsoft Clarity as part of the Growth team by adding a new feature and updating documentation accordingly. - Experimented the applicability and prototyped a tool that simulates Microsoft Clarity locally.

• Participated in SemEval Shared Task 3: Understanding Intent, News Genre, Framing, and Persuasion Techniques Detection • Fine-tuned and benchmarked models for News Genre Categorization and achieved very good results • Deployed and integrated models into a working website on-the-fly, granting the public the possibility to try the three tasks in SemEval 3 in real time • Visualized results for over 2 million articles from 183 countries and 10+ languages with different sorts of aggregation techniques to get the most insight out of countries news behavior

• Worked on the design, implementation and deployment of a Residency Reporting Module (RRM) aiming to design a new generation web-based pathology reporting system to enhance the educational experience of pathology residents. The system is grounded on the concept that digital pathology workflows are not constrained by physical limitations imposed by glass slides. • Proposed a novel experience that would allow residents to work on cases in parallel increasing the volume of cases per resident and introducing scalable case-based feedback. • Worked on the design and implementation of a web-based novel biopsy generator aiming for more rapid diagnoses of malignant skin neoplasms and reduction of invasive skin biopsies. • Worked on the development of a tool to automate the measurement of glomerular basement membrane thickness.

• Worked on the Amazon fr. account and was dedicated to providing exceptional service and support to customers, ensuring their satisfaction and building lasting relationships.