Databases and Information Systems


Sneha Singhania

Sneha Singhania

Max-Planck-Institut für Informatik
D5: Databases and Information Systems
 office: Campus E1 4, Room 424
Saarland Informatics Campus
66123 Saarbrücken
 website: Google Scholar | LinkedIn | GitHub


I'm a PhD student at the Max Planck Institute for Informatics, advised by Dr. Simon Razniewski and Prof. Gerhard Weikum. I'm passionate about research in natural language processing for Information Extraction and Knowledge Bases.

Before joining MPII, I worked as an AI Researcher and Engineer at Accenture Labs. I graduated with a Bachelor of Technology and a Master of Technology (dual degree) from the International Institute of Information Technology, Bangalore (IIITB) in 2018.


  1. Evaluating Language Models for Knowledge Base Completion
    Blerta Veseli, Sneha Singhania, Simon Razniewski, Gerhard Weikum
    Extended Semantic Web Conference (ESWC) 2023.
  2. LM-KBC: Knowledge Base Construction from Pretrained Language Models
    Sneha Singhania, Tuan-Phong Nguyen, and Simon Razniewski
    Semantic Web Challenge at International Semantic Web Conference (ISWC) 2022.
    [website] [proceedings] [code]
  3. Predicting Document Coverage for Relation Extraction
    Sneha Singhania, Simon Razniewski, and Gerhard Weikum
    Transactions of the Association for Computational Linguistics (TACL) 2022. (oral presentation at ACL 2022)
    [paper] [code]
  4. Decision Support System for Playlist Management and Curation
    Abhisek Mukhopadhyay, Sneha Singhania, Shubhashis Sengupta, and Andrew Fano
    International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Data Science Meets Optimization 2019. (oral)
  5. Deep Learning methods for (i) Extracting Numeric Semantics, and (ii) Entity Relation Classification
    Sneha Singhania
    Master's Thesis 2018.
  6. Predicting GPS TEC maps using Deep Spatio-temporal Residual Networks
    Sneha Singhania, Bharat Kunduri, Maimaitirebike Maimaiti, Joseph B. H. Baker, and J. Michael Ruohoniemi
    American Geophysical Union (AGU) Workshop on ML in Space Weather 2018. (oral)
    [link] [code]
  7. 3HAN: A Deep Neural Network for Fake News Detection
    Sneha Singhania, Nigel Fernandez, and Shrisha Rao
    International Conference On Neural Information Processing (ICONIP) 2017. (oral)
    [paper] [code]

Work Experience

  • AI Reseacher and Engineer
    Sep 2018 - Jan 2020
    Accenture Labs, Bangalore
  • Research Intern
    May 2018 - Aug 2018
    Google Summer of Code (GSoC)
    Open source organization: Space@VT, University of Virginia Tech
  • Project Assistant
    Aug 2017 - Dec 2017
    VideoKen, Bangalore
  • Research Intern
    Jun 2017 - Jul 2017
    VideoKen, Bangalore

Scholarships and Awards

  • 2020, 2021: Heidelberg Laureate Forum (HLF) Young Researcher
  • 2019: Star Innovator Award (zone: India) for top performance at Accenture Labs
  • 2019: Selected for CMMRS, LxMLS, Deep|Bayes, and MLSS summer schools
  • 2018: Selected for presentation at ACM's IRISS as one of India's top student papers
  • 2018: Winner of AI challenge in Cognitive Fashion, IBM Research India
  • 2017: Travel grant by Microsoft Research India and AICTE-INAE
  • 2013: INSPIRE fellowship by Government of India


  • Artificial Intelligence based Music Playlist Reordering and Song Performance Assessment. Abhisek Mukhopadhyay, Shubhashis Sengupta, Andrew Fano, and Sneha Singhania. U.S. Patent 11,106,728. 31 Aug. 2021.
  • Artificial Intelligence Based Music Playlist Curation. Abhisek Mukhopadhyay, Shubhashis Sengupta, Andrew Fano, and Sneha Singhania. U.S. Patent No. 11,061,961. 13 Jul. 2021.

Professional Activities

Student Mentoring

Blerta Veseli, Master's Thesis


Hobbies include running, hiking, painting and endurance cycling