Brief Bio

I am a PhD student at the eXascale Infolab working on Semantic Web and Machine Learning. My research focuses on Knowledge Graph embeddings. I hold a Bachelor of Science in Computer Science from the University of Torino (Italy) and a Master of Science in Computer Engineering from the University of Pavia (Italy). During my university career I have been participating in many exchange programs such as Erasmus at Technical University of Lodz (Poland) and exchange study program at Tongji University in Shanghai (China). Additionally, I have written my master thesis at HLRS in Stuttgart (Germany) in collaboration with the Performance Evaluation Group of the University of Pavia (Italy). Afterwards, I have done the Erasmus traineeship at HLRS in Stuttgart (Germany) where I have developed a platform to benchmark different architectures for High Performance Computing.

Bibliography

1. Vibhav Agarwal, Akansha Bhardwaj, Paolo Rosso, and Philippe Cudré-Mauroux. “ConvTab: A Context-Preserving, Convolutional Model for Ad-Hoc Table Retrieval.” In 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021. IEEE, 2021. Bibtex PDF

   ConvTab: A Context-Preserving, Convolutional Model for Ad-Hoc Table Retrieval

   Vibhav Agarwal, Akansha Bhardwaj, Paolo Rosso, and Philippe Cudré-Mauroux. “ConvTab: A Context-Preserving, Convolutional Model for Ad-Hoc Table Retrieval.” In 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021. IEEE, 2021.

   @inproceedings{agarwal2021bigdata,
     author = {Agarwal, Vibhav and Bhardwaj, Akansha and Rosso, Paolo and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {ConvTab: {A} Context-Preserving, Convolutional Model for Ad-Hoc Table
                    Retrieval},
     booktitle = {2021 {IEEE} International Conference on Big Data (Big Data), Orlando,
                    FL, USA, December 15-18, 2021},
     year = {2021},
     organization = {IEEE},
     url = {https://exascale.info/assets/pdf/agarwal2021bigdata.pdf}
   }
   

   ×
2. Prathyusha Nerella, Akansha Bhardwaj, Paolo Rosso, and Philippe Cudré-Mauroux. “GraphEDM: A Graph-Based Approach to Disambiguate Entities in Microposts.” In 2021 7th Swiss Conference on Data Science (SDS). IEEE, 2021. Bibtex PDF

   GraphEDM: A Graph-Based Approach to Disambiguate Entities in Microposts

   Prathyusha Nerella, Akansha Bhardwaj, Paolo Rosso, and Philippe Cudré-Mauroux. “GraphEDM: A Graph-Based Approach to Disambiguate Entities in Microposts.” In 2021 7th Swiss Conference on Data Science (SDS). IEEE, 2021.

   @inproceedings{nerella2021graphedm,
     author = {Nerella, Prathyusha and Bhardwaj, Akansha and Rosso, Paolo and Cudr{\'e}-Mauroux, Philippe},
     title = {GraphEDM: A Graph-Based Approach to Disambiguate Entities in Microposts},
     booktitle = {2021 7th Swiss Conference on Data Science (SDS)},
     year = {2021},
     organization = {IEEE},
     url = {https://exascale.info/assets/pdf/nerella2021sds.pdf}
   }
   

   ×
3. Paolo Rosso, Dingqi Yang, Natalia Ostapuk, and Philippe Cudré-Mauroux. “RETA: A Schema-Aware, End-to-End Solution for Instance Completion in Knowledge Graphs.” In Proceedings of The Web Conference (WWW 2021). Ljubljana, Slovenia, 2021. Bibtex PDF Code

   RETA: A Schema-Aware, End-to-End Solution for Instance Completion in Knowledge Graphs

   Paolo Rosso, Dingqi Yang, Natalia Ostapuk, and Philippe Cudré-Mauroux. “RETA: A Schema-Aware, End-to-End Solution for Instance Completion in Knowledge Graphs.” In Proceedings of The Web Conference (WWW 2021). Ljubljana, Slovenia, 2021.

   @inproceedings{rosso2021www,
     title = {RETA: A Schema-Aware, End-to-End Solution for Instance Completion in Knowledge Graphs},
     author = {Rosso, Paolo and Yang, Dingqi and Ostapuk, Natalia and Cudr{\'e}-Mauroux, Philippe},
     booktitle = {Proceedings of The Web Conference (WWW 2021)},
     year = {2021},
     address = {Ljubljana, Slovenia},
     code = {https://github.com/eXascaleInfolab/RETA_code},
     url = {https://exascale.info/assets/pdf/rosso2021www.pdf}
   }
   

   ×
4. Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, and Philippe Cudré-Mauroux. “Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!.” In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020). Yokohama, Japan, 2020. Bibtex PDF Code

   Location Prediction over Sparse User Mobility Traces using RNNs: Flashback in Hidden States!

   Dingqi Yang, Benjamin Fankhauser, Paolo Rosso, and Philippe Cudré-Mauroux. “Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!.” In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020). Yokohama, Japan, 2020.

   @inproceedings{yang2020location,
     title = {Location Prediction over Sparse User Mobility Traces using RNNs: Flashback in Hidden States!},
     author = {Yang, Dingqi and Fankhauser, Benjamin and Rosso, Paolo and Cudr{\'e}-Mauroux, Philippe},
     booktitle = {Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020)},
     year = {2020},
     address = {Yokohama, Japan},
     code = {https://github.com/eXascaleInfolab/Flashback_code/},
     url = {https://exascale.info/assets/pdf/yang2020IJCAI.pdf}
   }
   

   ×
5. Yasamin Eslahi, Akansha Bhardwaj, Paolo Rosso, Kurt Stockinger, and Philippe Cudré-Mauroux. “Annotating Web Tables through Knowledge Bases: A Context-Based Approach.” In 2020 7th Swiss Conference on Data Science (SDS). IEEE, 2020. Bibtex PDF

   Annotating Web Tables through Knowledge Bases: A Context-Based Approach

   Yasamin Eslahi, Akansha Bhardwaj, Paolo Rosso, Kurt Stockinger, and Philippe Cudré-Mauroux. “Annotating Web Tables through Knowledge Bases: A Context-Based Approach.” In 2020 7th Swiss Conference on Data Science (SDS). IEEE, 2020.

   @inproceedings{eslahi2020annotating,
     author = {Eslahi, Yasamin and Bhardwaj, Akansha and Rosso, Paolo and Stockinger, Kurt and Cudr{\'e}-Mauroux, Philippe},
     title = {Annotating Web Tables through Knowledge Bases: A Context-Based Approach},
     booktitle = {2020 7th Swiss Conference on Data Science (SDS)},
     year = {2020},
     organization = {IEEE},
     url = {https://exascale.info/assets/pdf/eslahi2020sds.pdf}
   }
   

   ×
6. Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction.” In Proceedings of The Web Conference (WWW 2020). Taipei, Taiwan, 2020. Bibtex PDF Code

   Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction

   Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction.” In Proceedings of The Web Conference (WWW 2020). Taipei, Taiwan, 2020.

   @inproceedings{rosso2020www,
     title = {Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction},
     author = {Rosso, Paolo and Yang, Dingqi and Cudr{\'e}-Mauroux, Philippe},
     booktitle = {Proceedings of The Web Conference (WWW 2020)},
     year = {2020},
     address = {Taipei, Taiwan},
     code = {https://github.com/eXascaleInfolab/HINGE_code},
     url = {https://exascale.info/assets/pdf/rosso2020www.pdf}
   }
   

   ×
7. Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Revisiting Text and Knowledge Graph Joint Embeddings: The Amount of Shared Information Matters!.” In BigData, 2019. Bibtex PDF Code

   Revisiting Text and Knowledge Graph Joint Embeddings: The Amount of Shared Information Matters!

   Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Revisiting Text and Knowledge Graph Joint Embeddings: The Amount of Shared Information Matters!.” In BigData, 2019.

   @inproceedings{rosso2019bigdata,
     author = {Rosso, Paolo and Yang, Dingqi and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {Revisiting Text and Knowledge Graph Joint Embeddings: The Amount of Shared Information Matters!},
     booktitle = {BigData},
     year = {2019},
     code = {https://github.com/eXascaleInfolab/JOINER_code},
     url = {https://exascale.info/assets/pdf/rosso2019bigdata.pdf}
   }
   

   ×
8. Dingqi Yang, Paolo Rosso, Bin Li, and Philippe Cudre-Mauroux. “NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching.” In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), 2019. Bibtex PDF

   NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching

   Dingqi Yang, Paolo Rosso, Bin Li, and Philippe Cudre-Mauroux. “NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching.” In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), 2019.

   @inproceedings{yang2019nodesketch,
     title = {NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching},
     author = {Yang, Dingqi and Rosso, Paolo and Li, Bin and Cudre-Mauroux, Philippe},
     booktitle = {Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)},
     year = {2019},
     url = {https://exascale.info/assets/pdf/yang2019nodesketch.pdf}
   }
   

   ×
9. Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Knowledge Graph Embeddings.” In Encyclopedia of Big Data Technologies., 2019. Bibtex PDF

   Knowledge Graph Embeddings

   Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Knowledge Graph Embeddings.” In Encyclopedia of Big Data Technologies., 2019.

   @incollection{rosso2018bigdata,
     author = {Rosso, Paolo and Yang, Dingqi and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {Knowledge Graph Embeddings},
     booktitle = {Encyclopedia of Big Data Technologies.},
     year = {2019},
     doi = {10.1007/978-3-319-63962-8\_284-1},
     timestamp = {Thu, 14 Feb 2019 16:03:55 +0100},
     url = {https://exascale.info/assets/pdf/rosso2018bigdata.pdf}
   }
   

   ×