Oversees all strategic planning, operational execution, and stakeholder engagement activities to ensure the success and sustainability of WORB's initiatives. Fosters relationships with international stakeholders, including companies, organizations, and institutions.

Student elect representative focused on optimizing the functioning of the academic department. Actively participated in teacher and student evaluation processes to ensure the maintenance of high-quality educational standards.

Student elect representative dedicated to restructuring outdated administrative policies, optimizing processes, and fostering collaboration. Meticulously analyzed existing systems, conducted financial studies, and advocated for institutional and research purposes.

Evaluate the viability of state-of-the-art projects, as well as providing them with a continuous mentoring support.

A seasoned contributor to particle physics data analysis, closely engaging with the CERN Data Preservation and Open Access (DPOA) team, optimizing workflows and metadata. Leveraged convolutional neural networks (CNNs), provided extensive endpoint support for CMS Open Data Workshops from 2022 to 2024. Experienced workshop instructor, skilled in cloud computing, Kubernetes, and experimental physics. Led the CMS Open Data Hackathon 2024.

Assessed and configured clusters for workshop participants, enabling them to leverage containerized data analysis on a public cloud provider, which facilitated their capabilities for particle physics analyses.

Conducted performance evaluations of modern batch scheduling systems, with a specific focus on Kubernetes-native scheduler, assessing its compatibility within a reproducible data analyses cloud platform.

1) Engaging closely with the CERN Data Preservation and Open Access (DPOA) team, streamlining workflow definitions and optimizing metadata.2) Utilized convolutional neural networks (CNNs) to classify a diverse range of particle processes using images generated from momentum data, particle position, and jet position data transformations.

Employed Kubernetes to analyze network traffic data fluctuations and anomalies within a national network, harnessing data series and machine learning techniques for comprehensive monitoring and detection.

Assessed and configured clusters for workshop participants, enabling them to leverage containerized data analysis on a public cloud provider, which facilitated their capabilities for particle physics analyses. Designed a Kubernetes architecture on GKE, implementing HTTP file server services, Argo CD, Argo Workflows, and RBAC

Gained extensive knowledge in music production, including signal processing, studio recordings, live recordings, and various aspects of audio engineering.