Laraib amna Khan

Built a forecasting system predicting heater energy consumption using NeuralProphet and Time Series Transformer models to capture seasonal patterns. Migrating a C# file-conversion system to Python (.kml to .inp) for ML pipeline integration, supporting leakage detection in water distribution networks. - Designed and trained ML models in Python. - Integrated AI/ML solutions into production systems. - Migrated and modernized legacy code for ML compatibility. - Optimized models for efficient deployment.

Enhancing Leakage Detection in Water Distribution Networks via Edge Weight Optimization Using Neural Operators • Studied leak detection in water networks with sparse sensors and complex flows. • Highlighted limits of Hazen–Williams and Darcy–Weisbach for nonlinear dynamics. • Used Navier–Stokes equations for realistic fluid modeling. • Trained a PINO for flow-based edge weights. • Integrated PINO into Liquor HGNN, replacing static models. • Enabled adaptive edge estimation.

- Conducted exercise classes for the Master in Cyber Security program - Assisted students in understanding and completing technical tasks - Maintained course exercises and provided ongoing support - Proctored sessions to ensure academic quality and integrity

As a React JS Developer on the HCI team at Julius Maximilian University of Würzburg, I contribute to the “Measurement Engine” project by: - Integrating APIs to capture and display physiological sensor data (heart rate, pulse). - Building intuitive, responsive interfaces that turn complex sensor data into clear visualizations. - Managing frontend data flow to ensure accurate, meaningful, and actionable insights.

Deal with clients, developed modules for frontend, backend and mobile apps, API integration, optimise angular JS and react JS code with modern approches or industry best practices. The responsibilities further includes code refactoring, testing with jasmine, karma and protractor and maintain the application structure. I got introduced to build systems such as gulp, babel, and webpack. I also got to work with no sql (mongodb with mongoose) databases and nodejs+express backend applications with web sockets.

grade: 1.8

Grade: 3.5 CGPA