Research

My research revolves around Efficient AI Methods, AI Alignment, AI for Science, Large Language Models, and Software Systems.

AI Ethics

  1. David Oniani, Jordan Hilsman, Yifan Peng, Ronald K. Poropatich, Jeremy C. Pamplin, Gary L. Legault, Yanshan Wang. Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare. npj Digital Medicine (2023).

AI Evaluation

  1. 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. Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI. npj Digital Medicine (2024).

  2. David Oniani, Sreekanth Sreekumar, Renuk DeAlmeida, Dinuk DeAlmeida, Vivian Hui, Young Ji Lee, Yiye Zhang, Leming Zhou, Yanshan Wang. Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models. AMIA Informatics Summit (2023).

  3. David Oniani, Yanshan Wang. A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19. ACM-BCB (2020).

AI Infrastructure

  1. David Oniani, Bambang Parmanto, Andi Saptono, Allyn Bove, Janet Freburger, Shyam Visweswaran, Jonathan Silverstein, Michael Becich, Anthony Delitto, Elizabeth Skidmore, Yanshan Wang. ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research. International Journal of Medical Informatics (2023).

  2. Daniel R. Harris, Sunyang Fu, Andrew Wen, Alexandria Corbeau, Darren Henderson, Jordan Hilsman, David Oniani, Yanshan Wang. The ENACT network is acting on housing instability and the unhoused using the open health natural language processing toolkit. JCTS (2024).

AI Methods for Graphs

  1. David Oniani, Guoqian Jiang, Hongfang Liu, Feichen Shen. Constructing Co-occurrence Network Embeddings to Assist Association Extraction for COVID-19 and Other Coronavirus Infectious Diseases. JAMIA (2020).

  2. David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen. Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features. arXiv (2021).

  3. David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen. Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping. arXiv (2021).

LLMs

  1. David Oniani, Nathan Liu, Jin Shang, Alex Patry, Suju Rajan. Generation-Augmented Retrieval for Product Recommendations. AMLC 2025 (2025).

  2. David Oniani, Amjad Jbara. Generative LLMs for Query-Product Relevance: Findings and Observations. AMLC Workshop on Gen AI, Personalization Algorithms and Recommender Systems (2024).

  3. David Oniani, Jordan Hilsman, Chengxi Zang, Junmei Wang, Lianjin Cai, Jan Zawała, Yanshan Wang. Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications. Scientific Reports (2024).

  4. David Oniani, Xizhi Wu, Shyam Visweswaran, Sumit Kapoor, Shravan Kooragayalu, Katelyn Polanska, Yanshan Wang. Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines. Human-Centred XAI: Enhancing AI Acceptability for Healthcare (IEEE ICHI Workshop) (2024).

  5. David Oniani, Premkumar Chandrasekar, Sonish Sivarajkumar, Yanshan Wang. Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks: Algorithm Development and Validation Study. JMIR AI (2023).

  6. Yanshan Wang, Xizhi Wu, Luke Carlson, David Oniani. Generative AI enhanced with NCCN clinical practice guidelines for clinical decision support: A case study on bone cancer. ASCO 2024 (2024).

  7. David Oniani, Jordan Hilsman, Hang Dong, Fengyi Gao, Shiven Verma, Yanshan Wang. Large Language Models Vote: Prompting for Rare Disease Identification. arXiv (2023).

  8. David Oniani, Yanshan Wang. In-Context Learning Functions with Varying Number of Minima. arXiv (2023).

Teaching Computer Science

  1. Roman Yasinovskyy, Karina Hoff, David Oniani. Setting Up Python Development Environment for Use in a Small Classroom. Midwest Instruction and Computing Symposium (2020).

Literature Review

  1. 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. A Scoping Review of Artificial Intelligence for Precision Nutrition. Advances in Nutrition (2025).

  2. Sonish Sivarajkumar, Haneef Ahamed Mohammad, David Oniani, Kirk Roberts, William Hersh, Hongfang Liu, Daqing He, Shyam Visweswaran, Yanshan Wang. Clinical Information Retrieval: A scoping review. Journal of Healthcare Informatics Research (2024).

  3. Abeed Sarker, Rui Zhang, Yanshan Wang, Yunyu Xiao, Sudeshna Das, Dalton Schutte, David Oniani, Qianqian Xie, Hua Xu. Natural Language Processing for Digital Health in the Era of Large Language Models. Yearbook of Medical Informatics (2024).

  4. 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. Social and Behavioral Determinants of Health in the Era of Artificial Intelligence with Electronic Health Records: A Scoping Review. Health Data Science (2021).

Algorithmic and Rule-Based Methods

  1. Sonish Sivarajkumar, Thomas Yu CHow Tam, Haneef Ahamed Mohammad, Samual Viggiano, David Oniani, Shyam Visweswaran, Yanshan Wang. Extraction of Sleep Information from Clinical Notes of Alzheimer's Disease Patients Using Natural Language Processing. JAMIA (2024).

Topology / Type Theory / Other

  1. David Oniani. The Topology of Robotic Configuration and Motion Planning. (2019).

  2. David Oniani. Type Inference Rules For Container Types in CCL. (2019).

  3. David Oniani. Textual and Statistical Analysis of Russian IRA Facebook Advertisements. (2019).

  4. David Oniani. Cosine Similarity and Its Applications in the Domains of Artificial Intelligence. (2020).