PNNL

Sameera Horawalavithana is a data scientist in Pacific Northwest National Laboratory’s (PNNL) Physical and Computational Science Directorate. He is a researcher and practitioner of large-scale artificial intelligence (AI) foundation models across multiple data modalities, such as language, graph, sensor, etc. His expertise on scaling AI for science and security problems has resulted in a great success in multiple projects (e.g., EXPERT, STEEL THREAD, MegaAI) where he developed a non-existing capability in the national lab complex to pre-train large-scale foundation models (more than 20B parameters) from scratch. He has authored more than 20 peer reviewed papers, including publications at premier AI conferences and workshops such as NeurIPS, ACL, TheWebConf, and WebSci. He also serves as an Associate Editor for the Institute of Electrical and Electronics Engineers (IEEE) Transactions on Artificial Intelligence journal.

• Artificial Intelligence
• Foundation models
• Natural language processing
• Graph learning
• Multi-hop reasoning
• Privacy and security
• Social computing

• PhD in Computer Science and Engineering, University of South Florida
• BS in Computer Science, University of Colombo

Funding

• EXPERT 2.0: Reasoning about Global Proliferation Signatures with Evidence Tracing and Uncertainty Estimation (co-PI; FY23 $932K)

Editorial Board

• Associated Editor, IEEE Transactions in Artificial Intelligence

Program Committee (Conferences)

• What do we need for successful domain generalization? Domain Generalization, The International Conference on Learning Representations (2023)
• Mathematical and Empirical Understanding of Foundation Models, The International Conference on Learning Representations (2023)
• The International Association for the Advancement of Artificial Intelligence (AAAI) Conference on Web and Social Media (2023)
• Association for Computing Machinery (ACM) Web Science Conference (2022 and 2023)
• Thirty-Seventh AAAI Conference on Artificial Intelligence (2023)
• The International Conference on Computational Linguistics (2022)
• Neural Information Processing Systems Conference (2022)
• IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (2022)
• International Workshop on Social Sensing, The International AAAI Conference on Web and Social Media (2021)

Review Committee (Journals)

• Artificial Intelligence Review, Springer (2022)
• IEEE Transactions on Computational Social Systems (2020)
• IEEE Transactions on Information Forensics and Security (2020)
• Journal of Computational Social Science (2020)
• Transactions on Parallel and Distributed Systems (2018)
• Online Social Networks and Media (2018)

• Best Paper Award (COVID Track), International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (2021)
• Winner, Grand Challenge, COVID-19 AstraZeneca Vaccine Disinformation, The 3rd North American Social Networks Conference (2021)
• Best Computer Science Undergraduate Thesis award (2014)

2022

• Botzer, N.A., Y.S. Horawalavithana, T. Weninger, and S. Volkova. 2022. "Lessons from Developing Multimodal Models with Code and Developer Interactions." In I Can't Believe It's Not Better Workshop: Understanding Deep Learning Through Empirical Falsification.
• Horawalavithana, Y.S., E.M. Ayton, A.A. Usenko, S. Sharma, J. Eshun, R.J. Cosbey, and M.F. Glenski, et al. 2022. "EXPERT: Public Benchmarks for Dynamic Heterogeneous Academic Graphs." Presented by Y.S. Horawalavithana at Graph Learning Benchmarks Workshop, The Web Conference, Virtual, Florida. arXiv preprint arXiv:2204.07203
• Horawalavithana, Y.S., E.M. Ayton, S. Sharma, S.A. Howland, M. Subramanian, S.W. Vasquez, and R.J. Cosbey, et al. 2022. "Foundation Models of Scientific Knowledge for Chemistry: Opportunities, Challenges and Lessons Learned." In Proceedings of BigScience Episode #5 -- Workshop on Challenges & Perspectives in Creating Large Language Models, May 2022, Virtual and Dublin, Ireland, 160–172. doi: 10.18653/v1/2022.bigscience-1.12
• Horawalavithana, S., N. Choudhury, J. Skvoretz, et al. 2022. “Online discussion threads as conversation pools: predicting the growth of discussion threads on reddit.” Comput Math Organ Theory 28, 112–140 (2022). doi: 10.1007/s10588-021-09340-1
• Horawalavithana, S., R. De Silva, N. Weerasekara, N.G. Kin Wai, M. Nabeel, B. Abayaratna, C. Elvitigala, P. Wijesekera, and A. Iamnitchi. 2022. “Vaccination trials on hold: malicious and low credibility content on Twitter during the AstraZeneca COVID-19 vaccine development.” Comput Math Organ Theory. 1-22. doi: 10.1007/s10588-022-09370-3
• Kin Wai, N.G., S. Horawalavithana, and A.bIamnitchi. 2022. “Forecasting topic activity with exogenous and endogenous information signals in Twitter.” In Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Association for Computing Machinery, New York, NY, USA, 95–98. doi: 10.1145/3487351.3488344
• Ng, K.W., S. Horawalavithana, and A. Iamnitchi. 2022. “Social media activity forecasting with exogenous and endogenous signals.” Social Network Analysis and Mining 12, 102 doi: 10.1007/s13278-022-00927-3

2021

• Horawalavithana, S., R. De Silva, M. Nabeel, C. Elvitigala, P. Wijesekara, and A. Iamnitchi. 2021. “Malicious and low credibility urls on twitter during the astrazeneca covid-19 vaccine development.” In Social, Cultural, and Behavioral Modeling: 14th International Conference, Virtual Event, July 6–9, 2021, Proceedings 14 (pp. 3-12). arXiv preprint arXiv:2102.12223
• Horawalavithana, S., K.W. Ng, and A. Iamnitchi. 2021. “Drivers of Polarized Discussions on Twitter during Venezuela Political Crisis.” In 13th ACM Web Science Conference 2021 Association for Computing Machinery, New York, NY, USA, 205–214. doi: 10.1145/3447535.3462496
• Kin Wai, N.G., S. Horawalavithana, and A. Iamnitchi. 2021. “Multi-platform information operations: Twitter, facebook and youtube against the white helmets.” In Proceedings of the 14th International AAAI Conference on Web and Social Media, Atlanta, USA.

2020

• Horawalavithana, S., K.W. Ng, and A. Iamnitchi. 2020. “Twitter is the megaphone of cross-platform messaging on the white helmets.” In Social, Cultural, and Behavioral Modeling: 13th International Conference, Washington, DC, USA, October 18–21, 2020, Proceedings 13 (pp. 235-244). doi: 10.1007/978-3-030-61255-9_23

2019

• Alhazmi, E., N. Choudhury, S. Horawalavithana, and A. Iamnitchi. 2019. “Temporal Mobility Networks in Online Gaming.” Frontiers in Big Data, 2, 21. doi: 10.3389/fdata.2019.00021
• Horawalavithana, S., J. Arroyo Flores, J. Skvoretz, et al. 2019. “The risk of node re-identification in labeled social graphs.” Applied Network Science 4, 33 (2019). doi:10.1007/s41109-019-0148-x
• Horawalavithana, S., J.G.A. Flores, J. Skvoretz, and A. Iamnitchi. 2019. "Behind the Mask: Understanding the Structural Forces That Make Social Graphs Vulnerable to Deanonymization," in IEEE Transactions on Computational Social Systems, vol. 6, no. 6, pp. 1343-1356. doi: 10.1109/TCSS.2019.2951330
• Horawalavithana, S., A. Bhattacharjee, R. Liu, N. Choudhury, L.O. Hall, and A. Iamnitchi. 2019. “Mentions of Security Vulnerabilities on Reddit, Twitter and GitHub.” In IEEE/WIC/ACM International Conference on Web Intelligence (WI '19). Association for Computing Machinery, New York, NY, USA, 200–207. doi: 10.1145/3350546.3352519
• Horawalavithana, S., C. Gandy, J.A. Flores, J. Skvoretz, and A. Iamnitchi. 2019. “Diversity, homophily and the risk of node re-identification in labeled social graphs.” Complex Networks and Their Applications VII. COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol. 813. Springer, Cham. doi: 10.1007/978-3-030-05414-4_32
• Liu, R., F. Mubang, L. O. Hall, S. Horawalavithana, A. Iamnitchi, and J. Skvoretz. 2019. "Predicting Longitudinal User Activity at Fine Time Granularity in Online Collaborative Platforms." 2019 IEEE International Conference on Systems, Man and Cybernetics, Bari, Italy, pp. 2535-2542, doi: 10.1109/SMC.2019.8914586