PNNL

Sameera Horawalavithana is a senior 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, and vision. His expertise on advancing AI for science, permitting and security problems has resulted in success in multiple DOE funded ($30M+) projects (e.g., PermitAI, Theseus, EXPERT, STEEL THREAD). The research that he led has highlighted in America's AI Action Plan (2025) and the White House Permitting Innovation Center. He has authored more than 40 peer reviewed papers, including publications at premier AI conferences and workshops. He also serves as an Associate Editor for the Institute of Electrical and Electronics Engineers (IEEE) Transactions on Artificial Intelligence journal, and an Area Chair for Empirical Methods in Natural Language Processing (EMNLP).

• AI for science, permitting, and security
• Natural language processing
• Large multimodal models

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

Funding

• Expanding PermitAI Data and Application Solutions to Federal and State Level Environmental Permitting for Geothermal and Critical Minerals Projects in Alaska and Nevada - DOE Office of Critical Minerals and Energy Innovation (CMEI) (PI; FY 25 – FY27)
• Theseus: A Computational Science Foundation Model - DOE, Office of Advanced Scientific Computing Research (PNNL PI, FY 25-FY27)
• PermitAI: Democratizing AI for Improving Permitting Outcomes and Efficiency - DOE, Office of Policy (PI; FY23-FY26)
• 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
• Associated Editor, Nature PalComms, Humanities and Social Sciences Communications
• Area Chair for Empirical Methods in Natural Language Processing (EMNLP)

Program Committee (Conferences)

• Neural Information Processing Systems (NeurIPs)
• The International Conference on Learning Representations (ICLR)
• Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI)
• The International Conference on Computational Linguistics (ACL)
• The Conference on Empirical Methods in Natural Language Processing (EMNLP)
• Conference on Language Modeling (COLM)
• ACM Conference on AI and Agentic Systems (CAIS)

• National recognition for the research work in America’s AI Action Plan (2025) and the White House Permitting Innovation Center
• Best Paper Award (COVID Track), International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (2021)
• Best Computer Science Undergraduate Thesis award (2014)

2026

• Horawalavithana, S., L. Phillips, I. Stewart, S. Munikoti, and K. Pazdernik. 2026. "Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models." arXiv preprint arXiv:2604.10985.
• Lilienthal, D., M. Mukherjee, and S. Horawalavithana. 2026. "Reward Design for Physical Reasoning in Vision-Language Models." arXiv preprint arXiv:2604.13993.
• Munikoti, S., I. Stewart, S. Horawalavithana, H. Kvinge, T. Emerson, S. Thompson, and K. Pazdernik. 2026. "Generalist Multimodal AI: A Review of Architectures, Challenges and Opportunities." Neurocomputing, 132933. 

2025

• Chaturvedi, S., A. Acharya, R. Meyur, K. Hayashi, S. Munikoti, and S. Horawalavithana. 2025. "Evaluating the Robustness of Dense Retrievers in Interdisciplinary Domains." In KDD Workshop on Evaluation and Trustworthiness of Agentic and Generative AI Models.
• Raab, R., M. Parker, D. Nally, S. Montgomery, A. Bernat, S. Munikoti, and S. Horawalavithana. 2025. "Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processing." arXiv preprint arXiv:2507.08109.
• Wagle, S., S. Munikoti, R. Meyur, J. Whiting, H. Farr, A. Acharya, S. Horawalavithana, M. Halappanavar, J. Strube, and L. Fierce. 2025. "Leveraging Multimodal AI for Efficient Data Discovery in Wind Energy Research." In Practice and Experience in Advanced Research Computing 2025: The Power of Collaboration, 1–3.

2024

• Horawalavithana, S., E. Ayton, A. Usenko, R. Cosbey, and S. Volkova. 2024. "Anticipating Technical Expertise and Capability Evolution in Research Communities Using Dynamic Graph Transformers." IEEE Transactions on Computational Social Systems 11(5):6982–7001.
• Horawalavithana, S., S. Munikoti, I. Stewart, H. Kvinge, and K. Pazdernik. 2024. "SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions." In Proceedings of the 1st Workshop on NLP for Science (NLP4Science), The 2024 Conference on Empirical Methods in Natural Language Processing, 58–72.
• Meyur, R., H. Phan, K. Hayashi, I. Stewart, S. Sharma, S. Chaturvedi, M. Parker, D. Nally, S. Montgomery, and K. Pazdernik. 2024. "Benchmarking LLMs for Environmental Review and Permitting." In Proceedings of the Workshop on Large Language Models for Scientific and Societal Advances (SciSoc LLM) at the 2025 ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
• Munikoti, S., A. Acharya, S. Wagle, and S. Horawalavithana. 2024. "Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning." In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), 84–89.
• Stewart, I., S. Horawalavithana, B. Kennedy, S. Munikoti, and K. Pazdernik. 2024. "Surprisingly Fragile: Assessing and Addressing Prompt Instability in Multimodal Foundation Models." arXiv preprint arXiv:2408.14595.

2023

• Acharya, A., S. Munikoti, A. Hellinger, S. Smith, S. Wagle, and S. Horawalavithana. 2023. "NuclearQA: A Human-Made Benchmark for Language Models for the Nuclear Domain." arXiv preprint arXiv:2310.10920.
• Horawalavithana, S., R. De Silva, N. Weerasekara, N.K. Wai, M. Nabeel, B. Abayaratna, C. Elvitigala, P. Wijesekera, and A. Iamnitchi. 2023. "Vaccination Trials on Hold: Malicious and Low Credibility Content on Twitter during the AstraZeneca COVID-19 Vaccine Development." Computational and Mathematical Organization Theory 29(3):448–469.
• Iamnitchi, A., L.O. Hall, S. Horawalavithana, F. Mubang, K.W. Ng, and J. Skvoretz. 2023. "Modeling Information Diffusion in Social Media: Data-Driven Observations." Frontiers in Big Data 6:1135191.
• Munikoti, S., A. Acharya, S. Wagle, and S. Horawalavithana. 2023. "Atlantic: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science." In AI to Accelerate Science and Engineering, The Thirty-Eighth Annual AAAI Conference on Artificial Intelligence.
• Wagle, S., S. Munikoti, A. Acharya, S. Smith, and S. Horawalavithana. 2023. "Empirical Evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science." In Scientific Document Understanding, The Thirty-Eighth Annual AAAI Conference on Artificial Intelligence.

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