Research articles in which I served as the lead author. For a comprehensive list, please refer to my Google Scholar profile.

Journal articles

Lamsal, R., Read, M. R., Karunasekera, S., & Imran, M. (2025). CReMa: Crisis Response through Computational Identification and Matching of Cross-Lingual Requests and Offers Shared on Social Media. IEEE Transactions on Computational Social Systems, 12(1), 306-319. [Published version]

Lamsal, R., Read, M. R., & Karunasekera, S. (2024). CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media texts. Knowledge-Based Systems, 296, 111916. [Published version]

Lamsal, R., Read, M. R., & Karunasekera, S. (2023). BillionCOV: An enriched billion-scale collection of COVID-19 tweets for efficient hydration. Data in Brief, 48, 109229. [Published version]

Lamsal, R., Harwood, A., & Read, M. R. (2022). Twitter conversations predict the daily confirmed COVID-19 cases. Applied Soft Computing, 109603. [Published version]
Dataset: https://github.com/rabindralamsal/MegaGeoCOV

Lamsal, R., Harwood, A., & Read, M. R. (2022). Socially Enhanced Situation Awareness from Microblogs using Artificial Intelligence: A Survey. ACM Computing Surveys. [Published version]

Lamsal, R. (2021). Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence, 51(5), 2790-2804.
Datasets: http://dx.doi.org/10.21227/781w-ef42 and http://dx.doi.org/10.21227/fpsb-jz61

Lamsal, R., & Katiyar, S. (2020). cs-means: Determining optimal number of clusters based on a level-of-similarity. SN Applied Sciences, 2(11), 1-9.

Lamsal, R., & Kumar, T. V. (2021). Twitter-Based Disaster Response Using Recurrent Nets. International Journal of Sociotechnology and Knowledge Development, 13(3), 133-150.

Conference articles

Lamsal, R., Read, M. R., & Karunasekera, S. (2024). Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts . In ISCRAM 2024.

Lamsal, R., Read, M. R., & Karunasekera, S. (2023). A Twitter narrative of the COVID-19 pandemic in Australia. In ISCRAM 2023.

Lamsal, R., Harwood, A., & Read, M. R. (2022). Where did you tweet from? Inferring the origin locations of tweets based on contextual information. In In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3935-3944).

Lamsal, R., Harwood, A., & Read, M. R. (2022). Addressing the location A/B problem on Twitter: the next generation location inference research. In Proceedings of the 6th ACM SIGSPATIAL LocalRec (pp. 1-4).

Book Chapters

Lamsal, R., & Kumar, T. V. (2020). Artificial Intelligence and Early Warning Systems. In AI and Robotics in Disaster Studies (pp. 13-32). Palgrave Macmillan, Singapore.

Lamsal, R., & Kumar, T. V. (2020). Artificial Intelligence Based Early Warning System for Coastal Disasters. In Development in Coastal Zones and Disaster Management (pp. 305-320). Palgrave Macmillan, Singapore.

Lamsal, R., & Vijay Kumar, T. V. (2019). Artificial Intelligence based Disaster Response Systems. Fourth World Congress on Disaster Management. January 29-February 1, 2019, IIT Bombay, India. [Book: Page 81--88]

Just preprints

Lamsal, R., & Choudhary, A. (2018). Predicting Outcome of Indian Premier League (IPL) Matches Using Machine Learning. arXiv preprint arXiv:1809.09813.

Public Datasets

Lamsal, R. (2021). Coronavirus (COVID-19) Tweets Dataset. IEEE Dataport.

Lamsal, R. (2021). Coronavirus (COVID-19) Geo-tagged Tweets Dataset. IEEE Dataport.

Lamsal, R. (2020). A Large Scale Nepali Text Corpus. IEEE Dataport.

Lamsal, R. (2019). 300-Dimensional Word Embeddings for Nepali Language. IEEE Dataport.