Ali Montazer

Ali Montazer

Ali Montazeralghaem (Montazer)

I am currently a Ph.D. candidate in the Computer Science Department at the University of Massachusetts Amherst, where I have the privilege of working under the guidance of Professor James Allan. I received my Master’s degree from the Computer Science Department at the University of Tehran, mentored by Professor Azadeh Shakery. I completed two internships at Microsoft Research, one internship at Google Research.

My research interests are centered around Information Retrieval, Data Mining, Natural Language Processing, Recommender Systems, and Reinforcement Learning. These areas fascinate me because they stand at the crossroads of technology and human interaction, shaping the way we access and utilize vast amounts of information.

Selected Papers

  • Extracting Relevant Information from Users Utterances in Conversational Search and Recommendation - Published in The 28th ACM KDD22 Conference on Knowledge Discovery and Data Mining, 2022. Read More
  • Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies - Published in arxiv, 2023. Read More
  • Algorithmic Vibe in Information Retrieval - Published in WWW 23 Proceedings of the ACM Web Conference, 2023. Read More
  • Learning Relevant Questions for Conversational Product Search using Deep Reinforcement Learning - Published in The Fifteenth ACM International Conference on Web Search and Data Mining, 2022. Read More
  • Large-scale Interactive Conversational Recommendation System using Actor-Critic Framework - Published in The Fifteenth ACM Conference on Recommender Systems, 2021. Read More
  • A Reinforcement Learning Framework for Relevance Feedback - Published in The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020. Read More
  • Relevance Ranking Based on Query-Aware Context Analysis - Published in The 42th European Conference on Information Retrieval, 2020. Read More
  • Theoretical Analysis of Interdependent Constraints in Pseudo-Relevance Feedback - Published in The 41th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2018. Read More