People / Students / Class of 2026
After completing an apprenticeship as an IT Specialist in 2021, Johannes graduated from Cooperative State University Heidenheim in 2024 with a Bachelor of Science in Computer Science - Information Technology. He completed a rigorous curriculum that combined mathematics and electrical engineering with core computer science. Over the course of his studies, he developed a versatile skill set ranging from low-level programming, algorithms, and databases to large-scale application development and machine learning. During his apprenticeship and studies, Johannes had the opportunity to work at BSH, a Bosch subsidiary, where he applied theoretical concepts to real-world projects. There, he initiated his professional career by developing full-stack web applications using .NET and Angular to monitor manufacturing processes and enhance productivity. He later transitioned to the newly established Data Analytics department, where he discovered his passion for working with big data. By designing and implementing a scalable data pipeline on AWS using services such as S3, Lambda, Airflow, ECR, ECS, Aurora, Redshift, and Timestream, Johannes developed core Python-based components that enabled the processing of terabytes of sensor data generated by globally distributed factories. This data was transformed and stored in a unified format across a multi-tiered database architecture, laying the foundation for advanced analytics and real-time monitoring to optimize manufacturing processes. Furthermore, he was key in developing a web-based application using FastAPI and Angular that allowed factory operators to interact with that data and gain actionable insights.
In another project, Johannes prototyped a traceability system leveraging AWS Neptune, a graph database service, to represent detailed information about manufactured appliances within a knowledge graph. Addressing the complexity of developing services for handling convoluted data requests, Johannes researched transpiling GraphQL queries into the Gremlin query language. His work resulted in a tool capable of generating services with a personalized, type-safe query language through GraphQL, based on visually defined data models via a NextJS web interface, enabling intuitive access to highly interconnected data. Recognizing the significance of his project, professors invited Johannes to contribute to the academic curriculum by sharing his knowledge in a university lecture. In his Bachelor's thesis at BSH, Johannes focused on optimizing relational databases for semi-structured time series data by statistically analyzing various optimization and compression techniques, comparing AWS Aurora and Timescale. The resulting database configuration achieved a 95.6% reduction in storage space, a 69-fold increase in query speed, a 13-fold improvement in insertion speed, and a 73.34% reduction in costs. Beyond his studies, Johannes applies his skills to create meaningful projects, ranging from developing mobile apps with Flutter, React Native, and Kotlin, used by hundreds of users, to building a platform for sharing lecture notes and summaries that benefits students across various programs during exam preparation. After graduation, Johannes accepted a full-time position with BSH’s Data Analytics team, where he focused on implementing real-time data streaming solutions using Amazon MSK to handle high-throughput sensor data. Through Northwestern’s MLDS program, Johannes aims to build upon his strong foundation in data engineering by deepening his expertise in machine learning and advanced analytics to design intelligent, scalable, and impactful data-driven systems.
