Developed ETL pipelines to automate data ingestion and transformation from Oracle servers.Utilized Spark SQL for data processing and automated asset reporting across the Geneva electrical grid.Created a unified database using a multi-tiered architecture to centralize and optimize data processing for grid management.

Co-head of start-up relations at the largest student recruitment fair in Europe, attracting over 22,000 visitors. Responsibilities include outreach and support for more than 130 start-ups, with a focus on fostering innovative initiatives and developing a collaborative dynamic between these young companies and emerging talent.

Developed an innovative socio-technical predictive model, soon to be published, that uses structural learning to build a Bayesian Network. This model uniquely combines social behavior and technical factors to forecast solar panel adoption among the Swiss population, offering a groundbreaking approach to understanding and encouraging renewable energy uptake.Part of the SWEET EDGE initiative, backed by the Swiss Federal Office of Energy (SFOE), the project analyzes regional motivations (Alps, cities, midlands) for solar adoption. It generates strategic scenarios supporting Switzerland’s Energy Strategy 2050, providing policymakers with data-driven insights to drive impactful, sustainable policies.

Student Assistant for Master course : Energy Conversion and Renewable Energy

Member of the Consulting Society Team, involved in organizing events to promote consulting on campus. Contributed to setting up roundtable discussions and meetings between students and consultants, as well as organizing a national business case competition in collaboration with start-ups.

Experienced private tutor specializing in math and physics. Work with students from various academic backgrounds, including Informatics, Mechanics, Biology, Physics, Economics, Literature, and Architecture.

Creation of an informatic tool that facilitates the choice of a storage system composed of a battery and an oxygen tank given criterion such as cost, weight, volume, efficiency, and performance. The goal of the storage system is to help a medical device (concentrator), developed by the lab, to provide oxygen to patients that need oxygen. It ensures the concentrator works in regions with unreliable electrical grids, with a particular focus on low-middle income countries (LMICs). The biggest challenge was that optimization on this type of hybrid storage has never been studied before, therefore a lot of literature study and creativity was necessary. Additionally, comprehensive modeling of various components, including patient requirements, concentrator behavior, storage system operation, and grid outages, was necessary for this project. Statistical analysis was employed to model the duration and occurrence of grid outages, while scenarios were created to simulate patient oxygen needs accurately.