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Mohammad Mahdavi

Lupe [1]

Mohammad Mahdavi was 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 research interests are data science, machine learning, and natural language processing.

He defended his PhD thesis, entitled "Semi-Supervised Data Cleaning", with the "Summa Cum Laude" honer on November 6, 2020. 


Contact Information
Google Scholar:
scholar.google.com/citations [2]
github.com/m-mahdavi [3]
linkedin.com/in/mohammad-mahdavi-lahijani [4]
Selected Contributions
Demo (Raha + Baran)
CIDR 2021
Paper [5], Video [6]
Baran [7]
PVLDB 2020
Paper [8], Video [9]
GitHub [10]
Raha [11]
Paper [12],  Poster [13], Video [14]
GitHub [15]
CLRL [16]
EDBT 2019
Paper [17],  Poster [18]
GitHub [19]
REDS [20]
SSDBM 2019
Paper [21],  Poster [22]
GitHub [23]
Abstraction Layer [24]
GitHub [25]
Selected Publications
Mohammad Mahdavi and Ziawasch Abedjan (2021). Semi-Supervised Data Cleaning with Raha and Baran. CIDR.
Mohammad Mahdavi and Ziawash Abedjan (2020). Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning. PVLDB.
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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