Brief Bio

I am a PhD student at the eXascale Infolab working on a project involving machine learning and crowdsourcing to build the next-generation of Recommender Systems. I hold a Bachelor’s degree in Computer Science from the University of Torino (Italy) and a Master’s degree 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. Afterwards, I have done the Erasmus traineeship at HLRS in Stuttgart (Germany) in which I have developed a platform used to benchmark different architectures for High Performance Computing.

Bibliography

  1. 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
  2. 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
  3. 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
  4. Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. “Knowledge Graph Embeddings.” In Encyclopedia of Big Data Technologies., 2019. Bibtex PDF