Arash Abedi
Computer Engineer · AI Researcher
PhD Researcher in Artificial Intelligence for Sustainable Future at the University of Bergamo. My background combines data engineering, cloud technologies, machine learning, and artificial intelligence.
Computer Engineer · AI Researcher
PhD Researcher in Artificial Intelligence for Sustainable Future at the University of Bergamo. My background combines data engineering, cloud technologies, machine learning, and artificial intelligence.
I am a Computer Engineer with a strong focus on data science and artificial intelligence. My academic and professional experience has allowed me to develop expertise in data analytics, machine learning, and big data technologies.
I am currently pursuing research in artificial intelligence, with interests at the intersection of AI, data, and sustainability.
Artificial intelligence and machine learning methods for data-driven applications and decision-making.
Exploring the intersection between AI, data, and sustainability, with a focus on impactful applications.
Supervised and unsupervised learning, anomaly detection, and data-driven modeling.
Scalable data pipelines, data architectures, and infrastructure for large-scale data processing.
Cloud infrastructure, distributed systems, and scalable architectures for data-intensive workloads.
Machine learning approaches for identifying anomalous patterns in real-world data.
PhD Researcher
Doctoral research focused on artificial intelligence
and its potential applications in the context of
sustainable development and data-driven systems.
Graduate studies focused on data science, data engineering, machine learning, and computer engineering.
PhD in Artificial Intelligence for Sustainable Future, focusing on the intersection of artificial intelligence, data, and sustainability.
Worked as a Cloud Data Engineer in the insurance sector, focusing on cloud infrastructure, data architecture, and scalable data solutions. Contributed to the development and management of cloud environments using modern cloud and Infrastructure as Code technologies.
Designed and orchestrated end-to-end ETL/ELT pipelines on Google Cloud Platform, supporting data integration, transformation, and loading processes.
Developed machine learning pipelines for anomaly detection and predictive modeling using unsupervised learning techniques including PCA, Isolation Forest, and LOF.
Performed advanced data analysis and SQL optimization across BigQuery, Microsoft SQL Server, and Oracle SQL.
Developed and optimized desktop applications using PyQt to simplify interactions with relational database management systems.
No scientific publications are currently listed. Research outputs will be added as they become available.
GitHub