I'm a PhD student at the Max Planck Institute for Informatics, advised by Simon Razniewski and Gerhard Weikum. I'm passionate about research in natural language processing for Information Extraction and Knowledge Bases. I pursued research internships at Apple (Cupertino) and Microsoft Research (Redmond).

Before joining MPI-INF, I worked as an AI Researcher and Engineer at Accenture Labs (Bangalore). I graduated with Bachelor and Master of Technology (dual degree) from IIIT-Bangalore.

1. NEON: News Entity-Interaction Extraction for Enhanced Question Answering
   Sneha Singhania, Silviu Cucerzan, Allen Herring, and Sujay Kumar Jauhar
   Under Submission
   [paper]
2. Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents
   Sneha Singhania, Simon Razniewski, and Gerhard Weikum
   Under Submission
   [paper]
3. Large Language Models and Knowledge Graphs: Opportunities and Challenges
   Jeff Z. Pan, Simon Razniewski, Jan-Christoph Kalo, Sneha Singhania, Jiaoyan Chen, Stefan Dietze, Hajira Jabeen, Janna Omeliyanenko, Wen Zhang, Matteo Lissandrini, Russa Biswas, Gerard de Melo, Angela Bonifati, Edlira Vakaj, Mauro Dragoni, Damien Graux
   Transactions on Graph Data and Knowledge (TGDK) 2023.
   [paper]
4. Extracting Multi-valued Relations from Language Models
   Sneha Singhania, Simon Razniewski, and Gerhard Weikum
   Repl4NLP workshop at the Association for Computational Linguistics (ACL) 2023. (poster)
   [paper] [dataset]
5. Evaluating Language Models for Knowledge Base Completion
   Blerta Veseli, Sneha Singhania, Simon Razniewski, and Gerhard Weikum
   Extended Semantic Web Conference (ESWC) 2023. (oral)
   [paper] [code]
6. 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]
7. 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]
8. Decision Support System for Playlist Management and Curation
   Abhisek Mukhopadhyay, Sneha Singhania, Shubhashis Sengupta, and Andrew Fano
   DSO workshop at the International Joint Conference on Artificial Intelligence (IJCAI) 2019. (oral)
   [link]
9. Deep Learning methods for (i) Extracting Numeric Semantics, and (ii) Entity Relation Classification
   Sneha Singhania
   Master's Thesis 2018.
   [thesis]
10. 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]
11. 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]

• Research Intern
  June 2024 - Sept 2024
  Microsoft Research, Redmond, USA
• Research Intern
  Feb 2023 - Jun 2023
  Apple, Cupertino, USA
• AI Reseacher and Engineer
  Sep 2018 - Jan 2020
  Accenture Labs, Bangalore, India
• 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, India
• Research Intern
  Jun 2017 - Jul 2017
  VideoKen, Bangalore, India

• 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.

• PC member/Reviewer: ICML'24, ARR'24, WWW'24, ECIR'24, EMNLP'23, ACL'23, ACML'23, ESWC'23, ISWC'22, CIKM (2020-23) and Sadhana (2018-2022)
• Teaching Assistant: Automated Knowledge Base Construction, Summer term 2022
• Volunteer: ICML (2021), ACL (2021), NAACL (2021)