Avishek Anand

Associate Prof. at the TU Delft


3.West.660, Building 28

TU Delft,

Delft, The Netherlands

Avishek Anand is an Associate Professor in the Web Information Systems (WIS) at the Software Technology department at Delft University of Technology (TU Delft). His research aims to develop intelligent and transparent machine learning approaches to help humans find relevant information. Specifically, he is interested in Explainable Information Retrieval. He holds a PhD in computer science from the Max Planck Insitute for Informatics, Saarbrücken. Previously, he was an Assistant professor in Information Retrieval in Lebniz University Hannover. His research is supported by Amazon research awards, Schufa Gmbh, BMBF, and EU Horizon 2020. He is also a member of the L3S Research Center and was a visiting scholar in Amazon Search. He also leads the Research, Engineering, and Infrastructure Team (REIT) at the Department of Software Technology.


Jul 20, 2024 Paper accepted at ICML 2024, titled “Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions”. 🎉
May 06, 2024 Paper accepted at the TKDE Journal, titled “DINE: Dimensional Interpretability of Node Embeddings”. Arxiv 🎉
Mar 24, 2024 🎤 Invited talk on “Explainable Information Retrieval” as part of Data Science Talk Series, Bloomberg, London.
Dec 24, 2023 🏆 Best Paper Award at IEEE International Conference on Data Mining (ICDM) for our paper titled “A Deep Reinforcement Learning Approach to Configuration Sampling Problem”.
Nov 08, 2023 📢 Organized the Dutch-Belgian IR Conference or DIR 2023! Fun talks with some great minds in IR 🌐 🔍

selected publications

  1. Efficient Neural Ranking Using Forward Indexes and Lightweight Encoders
    Jurek Leonhardt, Henrik Müller, Koustav Rudra , and 3 more authors
    ACM Transactions of Information Systems (TOIS), 2024
  2. Data Augmentation for Sample Efficient and Robust Document Ranking
    Abhijit Anand, Jurek Leonhardt, Jaspreet Singh , and 2 more authors
    ACM Transactions of Information Systems (TOIS), 2024
  3. Temporal Blind Spots in Large Language Models
    Jonas Wallat, Adam Jatowt, and Avishek Anand
    In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 , 2024
  4. Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
    Thorben Funke, Megha Khosla, Mandeep Rathee , and 1 more author
    IEEE Trans. Knowl. Data Eng., 2023
  5. Extractive Explanations for Interpretable Text Ranking
    Jurek Leonhardt, Koustav Rudra, and Avishek Anand
    ACM Transactions of Information Systems (TOIS), 2023
  6. A Deep Reinforcement Learning Approach to Configuration Sampling Problem
    Amir Abolfazli, Jakob Spiegelberg, Gregory Palmer , and 1 more author
    In IEEE International Conference on Data Mining, ICDM 2023, Shanghai, China, December 1-4, 2023 , 2023
  7. Explainable Information Retrieval
    Avishek Anand, Procheta Sen, Sourav Saha , and 2 more authors
    In , 2023
  8. DINE: Dimensional Interpretability of Node Embeddings
    Simone Piaggesi, Megha Khosla, André Panisson , and 1 more author
    Transactions of Knowledge and Data Engineering (TKDE), 2024
  9. Understanding, Categorizing and Predicting Semantic Image-Text Relations
    Christian Otto, Matthias Springstein, Avishek Anand , and 1 more author
    In Proceedings of the 2019 on International Conference on Multimedia Retrieval, ICMR 2019, Ottawa, ON, Canada, June 10-13, 2019 , 2019