Roee Shraga
(He/him/his)
Postdoctoral Research Associate
Research interests
- Database systems
- Machine learning
- Deep learning
- Information retrieval
- Natural language processing
- Data science
Education
- PhD in Data Science, Technion – Israel Institute of Technology
- BS in Industrial Engineering and Management (Information Management), Technion – Israel Institute of Technology
Biography
Roee Shraga is a postdoctoral research associate at the Khoury College of Computer Sciences at Northeastern University. His research aims to use artificial intelligence to understand data lakes.
Before joining Khoury College in 2021, Shraga interned in artificial intelligence at IBM Research as he obtained his doctorate from the Technion – Israel Institute of Technology. He also played semi-pro basketball.
Shraga works within the Data Lab, hosted by Renée Miller; he also works with Wolfgang Gatterbauer and Mirek Riedewald. Shraga has published more than a dozen papers in leading journals and conferences dealing with data integration, human-in-the-loop, machine learning, process mining, and information retrieval. He has received several doctoral fellowships, including the Leonard and Diane Sherman Interdisciplinary Fellowship, the Daniel Excellence Scholarship, and the Miriam and Aaron Gutwirth Memorial Fellowship.
Recent publications
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Gen-T: Table Reclamation in Data Lakes
Citation: Grace Fan, Roee Shraga, Renée J. Miller. (2024). Gen-T: Table Reclamation in Data Lakes ICDE, 3532-3545. https://doi.org/10.1109/ICDE60146.2024.00272 -
Learning to Characterize Matching Experts
Citation: Shraga, Roee, Ofra Amir, and Avigdor Gal. "Learning to Characterize Matching Experts." 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. -
Web table retrieval using multimodal deep learning
Citation: Shraga, Roee, et al. "Web table retrieval using multimodal deep learning." Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2020. -
Incognitomatch: Cognitive-aware matching via crowdsourcing
Citation: Shraga, Roee, et al. "Incognitomatch: Cognitive-aware matching via crowdsourcing." Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. 2020 -
Adnev: Cross-domain schema matching using deep similarity matrix adjustment and evaluation
Citation: Shraga, Roee, Avigdor Gal, and Haggai Roitman. "Adnev: Cross-domain schema matching using deep similarity matrix adjustment and evaluation." Proceedings of the VLDB Endowment 13.9 (2020): 1401-1415. -
Learning to rerank schema matches
Citation: Gal, Avigdor, Haggai Roitman, and Roee Shraga. "Learning to rerank schema matches." IEEE Transactions on Knowledge and Data Engineering (2019).