Anurag Acharya
Anurag Acharya
Biography
Anurag Acharya is a data scientist at Pacific Northwest National Laboratory (PNNL). He is an active researcher in the overlapping fields of artificial intelligence (AI) and natural language processing, with a key focus on evaluating and analyzing large language models (LLMs) in their application for scientific domains and in their correctness and bias. He has a record of using AI to detect misinformation and disinformation surrounding major world events, from the White Helmets operations in Syria to the COVID-19 pandemic. During his work in EXPERT, Acharya led the development of the first ever expert-crafted evaluation benchmark for LLMs for the nuclear nonproliferation domain. His current works include MegaAI, which focuses on using LLMs for molecular chemistry and to detect and classify vulnerabilities in code to protect critical cyber infrastructure, and ACCELERATE, an effort to analyze and predict the degradation of catalysts for sustainable conversion of alternate feedstocks to fuels and chemicals. In addition to these works, Acharya’s research interest is in understanding and mitigating biases in AI systems, and working towards building ethical AI. In addition to Department of Energy agencies, his research works have been funded by the Defense Advanced Research Projects Agency, the Air Force Research Laboratory, and IBM.
Disciplines and Skills
- Artificial Intelligence
- AI Ethics
- Natural Language Processing
- Large Language Models
- Generative AI
- Computational Linguistics
- Computational Social Sciences
Education
- PhD in computer science, Florida International University
- MS in computer science, Florida International University
- BEng in computer engineering, Tribhuvan University, Nepal
- BA in English and political science, Tribhuvan University, Nepal
Affiliations and Professional Service
Professional Membership
- Association for the Advancement of Artificial Intelligence
- Association for Computational Linguistics
- Association for Computing Machinery
Program and Organizing Committee
- Program Committee, Seventh International Workshop on Narrative Extraction from Texts, 2024
- Ethics Reviewer, Conference on Neural Information Processing Systems, 2023
- Session Chair, Ninth Annual Conference on Advances in Cognitive Systems Conference, 2021
- Organizing Committee, Communicating Science Workshop for Graduate Students, 2021
Review Committee (Journals)
- Natural Language Engineering, 2023 – Present
- IEEE Transactions on Artificial Intelligence, 2023 – Present
- Humanities & Social Sciences Communications, 2023 – Present
- International Journal of Data Science and Analytics, 2023 – Present
Awards and Recognitions
- Best Paper Award, Advanced Engineering and ICT-Convergence Proceedings, Transfer Learned Mobilenets with Shrinking Hyperparameters for Classifying Covid-19 Based on X-ray Images, 2021
Publications
- Saldanha E.G., A. Acharya, M. Ocal, J. Eshun, M.F. Glenski, and S. Volkova. 2024. "Detecting and Summarizing Narratives in the Information Environment: A Case Study of Misinformation and Disinformation Campaigns." In Detecting Online Propaganda and Misinformation, edited by Mark Last, Marina Litvak, Miao Lin. PNNL-SA-171527. doi:10.1142/13556
- Yarlott, W.V.H., A. Ochoa, A. Acharya, L. Bobrow, D. Castro-Estrada, D. Gomez, J. Zheng, D. McDonald, C. Miller, and M.A. Finlayson. 2021. “Finding Trolls Under Bridges: Preliminary Work on a Motif Detector.” Advances in Cognitive Systems. Virtual Conference
- Yarlott, W.V.H., A. Ochoa, A. Acharya, L. Bobrow, D. Castro-Estrada, D. Gomez, J. Zheng, D. McDonald, C. Miller, and M.A. Finlayson. 2021. “AI models for detecting motifs in a text collection” Literature & Culture and/as Intelligent Systems. Stuttgart, Germany.
- Acharya, A., K. Talamadupula, and M.A. Finlayson. 2021. “Towards an Atlas of Cultural Commonsense for Machine Reasoning.” Workshop on Common Sense Knowledge Graphs, The Thirty-Fifth AAAI Conference on Artificial Intelligence. Virtual Conference.
- KC, K., A. Acharya, A. Acharya, and S. Shrestha. 2021. “Transfer Learned Mobilenets with shrinking hyperparameters for classifying Covid-19 based on X-ray images.” Advanced Engineering and ICT-Convergence Proceedings. Vol 4, No. 2. Bangkok, Thailand.