Hassan Uz Zaman

- Event-driven system comprising 30+ microservices, built with extensive use of AWS services including ECS, EKS, Lambda, DynamoDB, RDS, SQS, Kinesis, API Gateway etc. - Rewrote of a legacy monolithic system by designing from scratch a modern event-driven microservice architecture for product tagging. - Owned every part of the engineering lifecycle, from architecture design to on-call rotations and CI/CD pipelines. - Evaluated job applications and conducted technical interviews.

- Topic: "Time Series Prediction of Vehicle Emissions Using Recurrent Neural Networks" - Modeling real-world time-series data from cars using machine learning.

At Digitalization, Powertrain Development: - Machine learning, time-series analysis (Python, scikit-learn, TensorFlow, etc) - Web/Software development (Python, Flask, etc) - Visualizations and dashboards (matplotlib, Plotly, etc) - Data engineering (Spark, AWS, Python)

At the Chair of Economic History: - Data collection, visualization and analysis. - Web app development and deployment with Python (Django) and Heroku.

Data collection and engineering at the Chair of Financial Management and Capital Markets

Hyper-spectral image segmentation and document verification at the NUST-TUKL Lab