Sandeep Suntwal

Selected work

Publications

Journal articles and book chapters

  1. Suntwal, S., & Brown, S. (2026). Reference Aware Delexicalization (RAD) Framework: Theory Driven Artificial Intelligence Modeling for Domain Generalization. Information Systems Research.
  2. Suntwal, S. (2026). Attribution-Driven Adaptive Prioritization of Tactics (ADAPT): Linking Threat Identifiability to Sector-Specific Control Prioritization. Information and Computer Security.
  3. Suntwal, S., Kocsis, D., Shepherd, M. (2026). Industry Sector Matters: Mapping Industry-Specific Cyber Vulnerabilities Through Rational Choice Theory Analysis. Information and Computer Security, 1–25.
  4. Suntwal, S., Naraine, M. L., Yadav, V., Aicher, T. J., & Brandimarte, L. (2025). Enriching Digital Sport Marketing Communication: Examining Emoji Functions Through Media Richness Theory. Sport Marketing Quarterly, 34(3), 189–204.
  5. *Al Anaissy, C., *Suntwal, S., Surdeanu, M., & Vesic, S. (2024). On the Feasibility of Learning Bipolar Gradual Argumentation Semantics Using Neural Architectures. Lecture Notes in Artificial Intelligence (LNAI). Springer.

Refereed conference proceedings

  1. Prabhu, S., Kocsis, D., & Suntwal, S. (2026). A Meta-Analytic Review of Sanctions in Organizational Cybersecurity. Proceedings of HICSS.
  2. Al Anaissy, C., Suntwal, S., Surdeanu, M., & Vesic, S. (2024). On Learning Bipolar Gradual Argumentation Semantics with Neural Networks. Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART).
  3. Suntwal, S., Brown, S., & Brandimarte, L. (2023). Understanding the Role of Nonverbal Tokens in the Spread of Online Information. Proceedings of HICSS. Best Paper Nominee.
  4. Suntwal, S., & Brown, S. (2023). Text Versus Paratext: Understanding Individuals' Accuracy in Assessing Online Information. Proceedings of HICSS.
  5. Suntwal, S., Brown, S., & Brandimarte, L. (2021). Pictographs, Ideograms, and Emojis (PIE): A Framework for Empirical Research Using Non-verbal Cues. Proceedings of HICSS.
  6. Mithun, M. P., Suntwal, S., & Surdeanu, M. (2021). Students Who Study Together Learn Better: On the Importance of Collective Knowledge Distillation for Domain Transfer in Fact Verification. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP).
  7. Mithun, M. P., Suntwal, S., & Surdeanu, M. (2021). Data and Model Distillation as a Solution for Domain-Transferable Fact Verification. Proceedings of North American Chapter of the Association for Computational Linguistics–Human Language Technologies (NAACL-HLT).
  8. Panenghat, M. P., Suntwal, S., Rafique, F., Sharp, R., & Surdeanu, M. (2020). Towards the necessity for debiasing natural language inference datasets. European Language Resources Association (ELRA).
  9. Suntwal, S., Brown, S., & Patton, M. (2020). How Does Information Spread? An Exploratory Study of True and Fake News. Proceedings of HICSS. Best Paper Nominee.
  10. Suntwal, S., Paul, M., Sharp, R., & Surdeanu, M. (2019). On the importance of delexicalization for fact verification. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP).
  11. Du, P. Y., Zhang, N., Ebrahimi, M., Samtani, S., Lazarine, B., Arnold, N., Dunn, R., Suntwal, S., et al. (2018). Identifying, collecting, and presenting hacker community data: Forums, IRC, carding shops, and DNMs. Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI).

* Equal contribution.

Patents

  1. Paul, M., Surdeanu, M., Suntwal, S., & Sharp, R. (2022). Domain transferrable fact verification systems and methods. U.S. Patent Application Publication No. US 2022/0358384 A1 (Application No. 17/736,683).