@article{oguntoye2025maintenance,title={Maintenance record-enriched machine learning model for pavement international roughness index prediction},author={Oguntoye, Kunle S. and Ceylan, Halil and Kim, Sunghwan and Gulmezoglu, Berk and Sourav, Md. Abdullah All and Mo, Yunjeong L.},journal={International Journal of Pavement Engineering},volume={26},number={1},pages={2555992},year={2025},publisher={Taylor & Francis},doi={10.1080/10298436.2025.2555992},url={https://www.tandfonline.com/doi/pdf/10.1080/10298436.2025.2555992},}
ICTD
Low-Altitude sUAS Flights for Remote Sensing of Submillimeter Hairline Cracks: A Case Study
Kunle S. Oguntoye, Md. Abdullah All Sourav, Rajrup Mitra, and 3 more authors
In International Conference on Transportation and Development 2025, 2025
@inproceedings{oguntoye2025low,title={Low-Altitude sUAS Flights for Remote Sensing of Submillimeter Hairline Cracks: A Case Study},author={Oguntoye, Kunle S. and Sourav, Md. Abdullah All and Mitra, Rajrup and Jenkins, Abby and Ceylan, Halil and Kim, Sunghwan},booktitle={International Conference on Transportation and Development 2025},pages={800--809},year={2025},publisher={ASCE},url={https://digitalcommons.mtu.edu/michigantech-p2/1896/},}
ASCE
Automatic Pavement Maintenance Predictions Using Large Language and Machine Learning Models
Kunle S. Oguntoye, Halil Ceylan, Sunghwan Kim, and 3 more authors
@inproceedings{oguntoye2025automatic,title={Automatic Pavement Maintenance Predictions Using Large Language and Machine Learning Models},author={Oguntoye, Kunle S. and Ceylan, Halil and Kim, Sunghwan and Sourav, Md. Abdullah All and Gulmezoglu, Berk and Mo, Yunjeong},booktitle={Airfield and Highway Pavements 2025},pages={269--280},year={2025},publisher={ASCE},url={https://ascelibrary.org/doi/10.1061/9780784486221.026},}
InTrans
Demonstrating the Use of Small Uncrewed Aircraft Systems (Drones) Capabilities and Data for Iowa Transportation and Infrastructure Work
Kunle S. Oguntoye, Md. Abdullah All Sourav, Rajrup Mitra, and 6 more authors
@techreport{oguntoye2025demonstrating,title={Demonstrating the Use of Small Uncrewed Aircraft Systems (Drones) Capabilities and Data for Iowa Transportation and Infrastructure Work},author={Oguntoye, Kunle S. and Sourav, Md. Abdullah All and Mitra, Rajrup and Jenkins, Abby and Ceylan, Halil and Kim, Sunghwan and Gulmezoglu, Berk and Mo, Yunjeong L. and Brooks, Colin N.},institution={Institute for Transportation, Iowa State University},year={2025},number={InTrans Project 24-904},url={https://prosper.intrans.iastate.edu/wp-content/uploads/2025/07/use_of_sUAS_capabilities_and_data_Task_1_w_cvr.pdf},}
arXiv
PersonaAI: Leveraging Retrieval-Augmented Generation and Personalized Context for AI-Driven Digital Avatars
@article{kimara2025personaai,title={PersonaAI: Leveraging Retrieval-Augmented Generation and Personalized Context for AI-Driven Digital Avatars},author={Kimara, Elvis and Oguntoye, Kunle S. and Sun, Jing},journal={arXiv preprint arXiv:2503.15489},year={2025},eprint={2503.15489},archiveprefix={arXiv},primaryclass={cs.HC},url={https://arxiv.org/pdf/2503.15489},}
2024
Sensors
Probabilistic Method to Fuse Artificial Intelligence-Generated Underground Utility Mapping
Kunle S. Oguntoye, Simon Laflamme, Roy Sturgill, and 3 more authors
@article{oguntoye2024probabilistic,title={Probabilistic Method to Fuse Artificial Intelligence-Generated Underground Utility Mapping},author={Oguntoye, Kunle S. and Laflamme, Simon and Sturgill, Roy and Salazar Martinez, D. A. and Ceylan, Halil and Alipour, Alice},journal={Sensors},volume={24},number={11},pages={3559},year={2024},publisher={MDPI},doi={10.3390/s24113559},url={https://www.mdpi.com/1424-8220/24/11/3559/pdf},}
MSc Thesis
A practical framework for automatic underground utility mapping
@article{oguntoye2023review,title={Review of artificial intelligence applications for virtual sensing of underground utilities},author={Oguntoye, Kunle S. and Laflamme, Simon and Sturgill, Roy and Eisenmann, David J.},journal={Sensors},volume={23},number={9},pages={4367},year={2023},publisher={MDPI},doi={10.3390/s23094367},url={https://www.mdpi.com/1424-8220/23/9/4367/pdf},}