TU Berlin

Fachgebiet Big Data ManagementMohammad Mahdavi

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Mohammad Mahdavi

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Mohammad Mahdavi is a PhD candidate and research assistant at Big Data Management group. He received his MSc degree in Artificial Intelligence from University of Tehran. His main interests are data integration, machine learning and information retrieval.

Currently, he is working on the recommending data cleaning workflows. The aim of this is to recommend the best workflow of data cleaning based on the previous data cleaning efforts.  

 

Contact Information
CV:
CV.pdf
E-Mail:
m.mahdavi∂mailbox.tu-berlin.de
Google Scholar:
scholar.google.com/citations
GitHub:
github.com/m-mahdavi
LinkedIn:
linkedin.com/in/mohammad-mahdavi-lahijani
Selected Contributions
Project
Venue
Presentation
Repository
TBA
TBA
TBA
TBA
Raha
SIGMOD 2019
PaperPoster, Video
GitHub
CLRL
EDBT 2019
PaperPoster
GitHub
REDS
SSDBM 2019
PaperPoster
GitHub
Abstraction Layer
GitHub
Selected Publications
Mohammad Mahdavi, Ziawash Abedjan, Raul Castro Fernandez, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, and Nan Tang (2019). Raha: A Configuration-Free Error Detection System. SIGMOD.
Öykü Özlem Çakal, Mohammad Mahdavi and Ziawasch Abedjan (2019). CLRL: Feature Engineering for Cross-Language Record Linkage. EDBT.
Mohammad Mahdavi and Ziawash Abedyan (2019). REDS: Estimating the Performance of Error Detection Strategies Based on Dirtiness Profiles. SSDBM.

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