My research revolves around Efficient AI Methods, AI for Science, AI Alignment, Large Language Models, and Software Systems.
Research
AI for Science
- Generation-Augmented Retrieval for Product Recommendations
David Oniani, Nathan Liu, Jin Shang, Alex Patry, Suju Rajan
AMLC 2025 (2025) - A Scoping Review of Artificial Intelligence for Precision Nutrition
Xizhi Wu, David Oniani, Zejia Shao, Paul Arciero, Sonish Sivarajkumar, Jordan Hilsman, Alex E Mohr, Stephanie Ibe, Minal Moharir, Li-Jia Li, Ramesh Jain, Jun Chen, Yanshan Wang
Advances in Nutrition (2025) - Generative LLMs for Query-Product Relevance: Findings and Observations
David Oniani, Amjad Jbara
AMLC Workshop on Gen AI, Personalization Algorithms and Recommender Systems (2024) - Clinical Information Retrieval: A scoping review
Sonish Sivarajkumar, Haneef Ahamed Mohammad, David Oniani, Kirk Roberts, William Hersh, Hongfang Liu, Daqing He, Shyam Visweswaran, Yanshan Wang
Journal of Healthcare Informatics Research (2024) - Natural Language Processing for Digital Health in the Era of Large Language Models
Abeed Sarker, Rui Zhang, Yanshan Wang, Yunyu Xiao, Sudeshna Das, Dalton Schutte, David Oniani, Qianqian Xie, Hua Xu
Yearbook of Medical Informatics (2024) - Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications
David Oniani, Jordan Hilsman, Chengxi Zang, Junmei Wang, Lianjin Cai, Jan Zawała, Yanshan Wang
Scientific Reports (2024) - Generative AI enhanced with NCCN clinical practice guidelines for clinical decision support: A case study on bone cancer
Yanshan Wang, Xizhi Wu, Luke Carlson, David Oniani
ASCO 2024 (2024) - Extraction of Sleep Information from Clinical Notes of Alzheimer's Disease Patients Using Natural Language Processing
Sonish Sivarajkumar, Thomas Yu CHow Tam, Haneef Ahamed Mohammad, Samual Viggiano, David Oniani, Shyam Visweswaran, Yanshan Wang
JAMIA (2024) - Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models
David Oniani, Sreekanth Sreekumar, Renuk DeAlmeida, Dinuk DeAlmeida, Vivian Hui, Young Ji Lee, Yiye Zhang, Leming Zhou, Yanshan Wang
AMIA Informatics Summit (2023) - Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features
David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen
arXiv (2021) - Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping
David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen
arXiv (2021) - Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review
Anusha Bompelli, Yanshan Wang, Ruyuan Wan, Esha Singh, Yuqi Zhou, Lin Xu, David Oniani, Bhavani Singh Agnikula Kshatriya, Joyce (Joy) E. Balls-Berry, Rui Zhang
Health Data Science (2021) - Constructing Co-occurrence Network Embeddings to Assist Association Extraction for COVID-19 and Other Coronavirus Infectious Diseases
David Oniani, Guoqian Jiang, Hongfang Liu, Feichen Shen
JAMIA (2020)
AI Alignment & Evaluation
- Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Mahyar Abbasian, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Ram Sriram, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh Jain, Amir M. Rahmani
npj Digital Medicine (2024) - Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines
David Oniani, Xizhi Wu, Shyam Visweswaran, Sumit Kapoor, Shravan Kooragayalu, Katelyn Polanska, Yanshan Wang
Human-Centred XAI: Enhancing AI Acceptability for Healthcare (IEEE ICHI Workshop) (2024) - Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare
David Oniani, Jordan Hilsman, Yifan Peng, Ronald K. Poropatich, Jeremy C. Pamplin, Gary L. Legault, Yanshan Wang
npj Digital Medicine (2023) - A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19
David Oniani, Yanshan Wang
ACM-BCB (2020)
Efficient AI Methods
- In-Context Learning Functions with Varying Number of Minima
David Oniani, Yanshan Wang
arXiv (2023) - Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks: Algorithm Development and Validation Study
David Oniani, Premkumar Chandrasekar, Sonish Sivarajkumar, Yanshan Wang
JMIR AI (2023) - Large Language Models Vote: Prompting for Rare Disease Identification
David Oniani, Jordan Hilsman, Hang Dong, Fengyi Gao, Shiven Verma, Yanshan Wang
arXiv (2023)
Software Systems & Infrastructure
- The ENACT network is acting on housing instability and the unhoused using the open health natural language processing toolkit
Daniel R. Harris, Sunyang Fu, Andrew Wen, Alexandria Corbeau, Darren Henderson, Jordan Hilsman, David Oniani, Yanshan Wang
JCTS (2024) - ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research
David Oniani, Bambang Parmanto, Andi Saptono, Allyn Bove, Janet Freburger, Shyam Visweswaran, Jonathan Silverstein, Michael Becich, Anthony Delitto, Elizabeth Skidmore, Yanshan Wang
International Journal of Medical Informatics (2023)
Teaching Computer Science
- Setting Up Python Development Environment for Use in a Small Classroom
Roman Yasinovskyy, Karina Hoff, David Oniani
Midwest Instruction and Computing Symposium (2020)
Foundations & Mathematics
- Cosine Similarity and Its Applications in the Domains of Artificial Intelligence
David Oniani
(2020) - The Topology of Robotic Configuration and Motion Planning
David Oniani
(2019) - Type Inference Rules For Container Types in CCL
David Oniani
(2019) - Textual and Statistical Analysis of Russian IRA Facebook Advertisements
David Oniani
(2019)