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Mohamed Trabelsi

Murray Hill, NJ, USA
Research Scientist

Biography

Mohamed Trabelsi completed his Ph.D. in Computer Science from Lehigh University, PA, USA, in May, 2022. His Ph.D. thesis was about leveraging dataset content in neural models for search and curation in order to develop efficient and effective dataset search engines, and improve the quality of the extracted datasets for downstream tasks. He holds a Master of Science in Computer Science from University of Louisville, KY, USA. He also holds a Bachelor of Science in Computer Science from Tunisia Polytechnic School, Tunisia. His research areas include Machine learning, Information Retrieval, and Natural Language Processing.

Education

2022: Ph.D in Computer Science, Lehigh University, PA, USA.

2018: MS in Computer Science, University of Louisville, KY, USA.

2016: BS in Computer Science, Tunisia Polytechnic School, Tunis, Tunisia.

 

Selected articles and publications

M Trabelsi, Z Chen, S Zhang, BD Davison, J Heflin “StruBERT: Structure-aware BERT for Table Search and Matching”. Proceedings of the Web Conference (WWW’22), April 2022.

M Trabelsi, J Heflin, J Cao “DAME: Domain Adaptation for Matching Entities”. Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 2022.

Z Chen, M Trabelsi, J Heflin, D Yin, BD Davison “MGNETS: Multi-Graph Neural Networks for Table Search”. Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 2021.

M Trabelsi, Z Chen, BD Davison, J Heflin “Neural ranking models for document retrieval”. Information Retrieval Journal, 24(6): 400-444, 2021.

M Trabelsi, J Cao, J Heflin “SeLaB: Semantic Labeling with BERT”. International Joint Conference on Neural Networks (IJCNN), 1-8, 2021.

M Trabelsi, Z Chen, BD Davison, J Heflin “A Hybrid Deep Model for Learning to Rank Data Tables”. IEEE International Conference on Big Data (Big Data), 979-986, 2020.

M Trabelsi, Z Chen, BD Davison, J Heflin “Relational Graph Embeddings for Table Retrieval”. IEEE International Conference on Big Data (Big Data), 3005-3014, 2020.

Z Chen, M Trabelsi, J Heflin, Y Xu, BD Davison “Table Search Using a Deep Contextualized Language Model”. Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 589-598, 2020.

Z Chen, M Trabelsi, BD Davison, J Heflin “Towards Knowledge Acquisition of Metadata on AI Progress”. ISWC (Posters and Demos), 232-237, 2020.

M Trabelsi, BD Davison, J Heflin “Improved table retrieval using multiple context embeddings for attributes”. IEEE International Conference on Big Data (Big Data), 1238-1244, 2019.

M Trabelsi, H Frigui “Robust fuzzy clustering for multiple instance regression”. Pattern Recognition, 90: 424-435, 2019.

M Trabelsi, H Frigui “Fuzzy and possibilistic clustering for multiple instance linear regression”. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-7, 2018.

A Karem, M Trabelsi, M Moalla, H Frigui “Comparison of several single and multiple instance learning methods for detecting buried explosive objects using GPR data”. Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 2018.