- 🤖 Passionate about uncovering insights and solving problems through data and AI
- 🏅 Enthusiastic about sports, from fitness to team activities
My technical stack
During my academic journey and internships, I had the opportunity to explore and work with a variety of technologies. Here’s a detailed overview of my technical expertise.
Create data cleaning pipelines and ensuring high quality data by analysis.
Strong understanding of machine learning concepts. Able to reason about data and models and diagnose where machine learning goes wrong.
Practical experience in building deep learning models. Able to deal with common neural network problems.
Experience with various data engineering tools, including Apache Kafka for real-time data streaming and messaging, Apache Flink for stateful stream processing, and Spark Streaming for scalable and distributed stream processing
Creating backends with node.js, Spring Boot & Flask
Frameworks such as Remix and React Router to create webapps.
ASP.net to build webapps
Experience with frameworks Vue, Angular and React
Styling webpages using Tailwind
Creating software on Windows using Java, C# and Python
Experience with Google Cloud to setup projects and pipelines using bigquery, cloud functions
Automatically deploy architectures using Terraform
Storage virtualization and cloud object storages such as S3
Visualisation with Grafana
Setting up automated projects using Jenkins
Setup of Kubernetes and containers
Monitoring using Prometheus
Code quality tools such as SonarQube
Understand theoretical concepts
Experience in building a microservice architecture with Quarkus
Theoretical and practical experience in computer vision
Multimedia applications
Theoretical understanding of Blockchain technologies, but not practical experience
