Virgil Pavlu

Associate Teaching Professor

Virgil Pavlu
  • Information retrieval
  • Machine learning
  • Algorithms
  • PhD in Computer Science, Northeastern University
  • BS in Mathematics with minor in Computer Science, University of Bucharest — Romania

Virgil Pavlu is an associate teaching professor at the Khoury College of Computer Sciences at Northeastern University. He earned his doctorate in computer science from Northeastern and his bachelor’s in mathematics from the University of Bucharest, Romania. Pavlu’s research interests include information retrieval, including diversity, learning to rank, metasearch, score distribution models, and relevance feedback. At Northeastern, he teaches machine learning, information retrieval, and algorithms.

Pavlu’s current research centers around machine learning algorithms for certain data types, particularly applications to text data. On long text, this includes the extraction and selection of n-grams features, and on short text, this includes the discovery, indexing and matching of nuggets for tasks like relevance and novelty. One of his projects addresses the representability of text documents in high-dimensional spaces, the study of similarity and distance notions, and the active learning application to crowdsourcing methodologies for obtaining such representation.

Since 2007, Pavlu has been involved with the SIGIR conference either as a reviewer or an organizer. He was a coordinator of several TREC and NTCIR tracks.

Pavlu grew up in Bucharest, Romania.

  • A Complex KBQA System using Multiple Reasoning Paths

    Citation: Kechen Qin, Yu Wang , Cheng Li, Kalpa Gunaratna, Hongxia Jin, Virgil Pavlu, Javed A. Aslam. (2020). A Complex KBQA System using Multiple Reasoning Paths CoRR, abs/2005.10970. https://arxiv.org/abs/2005.10970

  • Learning to Calibrate and Rerank Multi-label Predictions

    Citation: Cheng Li, Virgil Pavlu, Javed A. Aslam, Bingyu Wang, Kechen Qin. (2019). Learning to Calibrate and Rerank Multi-label Predictions ECML/PKDD (3), 220-236. https://doi.org/10.1007/978-3-030-46133-1_14

  • Adapting RNN Sequence Prediction Model to Multi-label Set Prediction

    Citation: Conference Proceedings Adapting RNN Sequence Prediction Model to Multi-label Set Prediction. Qin, Kechen; Li, Cheng; Pavlu, Virgil; Aslam, Javed. Proceedings of the 2019 NAACL-HLT, Volume 1 (Long and Short Papers), 2019 8 jun I Association for Computational Linguistics, Minneapolis, Minnesota

  • A Study of Realtime Summarization Metrics

    Citation: Matthew Ekstrand-Abueg, Richard McCreadie, Virgil Pavlu, and Fernando Diaz. 2016. A Study of Realtime Summarization Metrics. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM '16). Association for Computing Machinery, New York, NY, USA, 2125–2130. DOI: 10.1145/2983323.2983653

  • Optimizing nDCG Gains by Minimizing Effect of Label Inconsistency

    Citation: P. Metrikov, V. Pavlu, J. A. Aslam, "Optimizing nDCG Gains by Minimizing Effect of Label Inconsistency", Advances in Information Retrieval: 35th European Conference on IR Research (ECIR), Moscow, Russia (2013). Best Poster Paper Award

  • A Modification of LambdaMART to Handle Noisy Crowdsourced Assessments

    Citation: Pavel Metrikov, Jie Wu, Jesse Anderton, Virgil Pavlu, and Javed A. Aslam. 2013. A Modification of LambdaMART to Handle Noisy Crowdsourced Assessments. In Proceedings of the 2013 Conference on the Theory of Information Retrieval (ICTIR '13). Association for Computing Machinery, New York, NY, USA, 133–134. https://doi.org/10.1145/2499178.2499198

  • Impact of Assessor Disagreement on Ranking Performance

    Citation: P. Metrikov, V. Pavlu, J. A. Aslam, "Effect of Assessor Disagreement on Ranking Performance", Proceedings of the 35th international ACM SIGIR conference on Research and Development in Information Retrieval, Portland, USA (2012)