Ayesha Fazal Lashkarwala

Developed and delivered a Python programming curriculum to 100+ enrolled students.

- Curated and prepared a domain-specific dataset from Hugging Face for efficient experimentation. - Developed a visual logging tool to streamline monitoring and analysis of Large Language Model outputs. - Researched and evaluated inference servers to identify the most suitable solution for deployment.

• Integrated SignalR into a legacy .NET Framework system with WebForms, optimizing real-time communication. • Utilized Azure Data Studio for detailed analysis, dissecting individual components of a complex stored procedure to identify areas for improvement. • Reduced execution time by 89% by optimizing a complex stored procedure within the legacy system. • Performed in-depth data analysis to standardize and harmonize system metrics, enhancing data consistency and reliability.

• Completed comprehensive engineering training, covering gRPC, N-tier Architecture, Clean Architecture, Cloud Storage and other topics in .Net Core. • Developed a Reasonable and Customary Fee Tool in .Net Core (backend) and Angular (frontend) for one of the existing products. • Proposed design (UI) changes within a product to improve User Experience of the product. • Completed comprehensive DevOps training, covering Azure DevOps CI/CD pipeline and Jenkins

Data Science (CS 334) Teaching Assistant • Assisted Dr. Mobin Javed in this course. • Encouraged students to learn by organizing tutorials in Python and conducting office hours weekly. • Aided the instructor by regularly preparing assignments and checking quizzes and assignments as well as leading a semester long project for 80+ students.

• Analyzed data using Mix panel and SQL queries to find useful insights. • Found discrepancies in the available data and informed higher authorities.

• Assisted Dr. Imdad Khan in this course. • Guided students to engage in learning by organizing help sessions and office hours. • Facilitated the instructor by regularly checking quizzes, preparing, and checking assignments for 200+ enrolled students.

CGPA: 3.47 (1.7 German Grade) Relevant Courses: Artificial Intelligence, Computer Vision, Human Centered Interaction, Topics in Human Centered Design and Interaction, Cognition and Computers, Principles and Techniques of Data Science, Machine Learning, Software Engineering