معرفی
Ziawasch Abedjan is a full professor of computer science and chair of the Data Integration and Data Preparation (D2IP Lab) Group at Technische Universität Berlin, part of the Berlin Institute for the Foundations of Learning and Data (BIFOLD). He holds a PhD from the Hasso Plattner Institute (2014) and was previously a junior professor at TU Berlin (2016–2020), with postdoctoral work at MIT (2014–2016). His research focuses on scalable methods for processing large heterogeneous datasets, emphasizing automated data preparation, extraction, and cleaning for data science workflows.
Education:
- PhD in Computer Science, Hasso Plattner Institute (2014)
- MSc in Computer Science, Hasso Plattner Institute (2010)
- BSc in Computer Science, Hasso Plattner Institute (2008)
Research Interests: Dr. Abedjan’s work bridges database systems and machine learning, addressing challenges in data integration, automated data cleaning, and scalable data science tools. His team develops systems like Blend for unified data discovery and MATE for multi-attribute table extraction. Recent projects include exploring the environmental impact of AutoML and advancing catalog enrichment techniques.
Awards & Recognition:
- First Prize, GI Data Science Challenge (BTW 2023)
- SIGMOD Reproducibility Award (2019)
- Best Dissertation Award (2013/2014)
Teaching & Service: Teaches foundational courses in data structures and databases. Serves on committees for major conferences (SIGMOD, VLDB) and chairs roles such as Reproducibility Chair for BTW (2023/2025). Active in editorial roles for journals including ACM JDIQ and IEEE Data Engineering Bulletin.
Labs & Teams: Leads the D2IP Lab, collaborating with universities and industry. Current projects include TDC2 NFDI4DS. Offers thesis topics in data science lifecycle optimization and ML system design.
