Josué Kpodo

Ph.D. Candidate
Michigan State Univeristy
kpodojos (at) msu (dot) edu


About Me

I am a dual Ph.D. candidate in Computer Science and Biosystems Engineering at Michigan State University. I am fortunate to be advised by Dr. Pouyan Nejadhashemi and Dr. Parisa Kordjamshidi.

My primary research is multidisciplinary and lies at the intersection of Natural Language Processing (NLP) and Process-based Modeling, involving the design of Neurosymbolic systems (Domain-specific LLMs & Crop Models) to solve challenging agricultural problems related to water management. A major part of my research work also revolves around the development of Decision Support Tools at the Decision Support & Informatics Lab.

Publications

Peer-Reviewed Journal Articles

  1. Kpodo, J., & Nejadhashemi, A. P. (2025). Navigating challenges/opportunities in developing smart agricultural extension platforms: Multi-media data mining techniques. Artificial Intelligence in Agriculture. https://doi.org/10.1016/j.aiia.2025.04.001.

  2. Razavi, M. A., Nejadhashemi, A. P., Majidi, B., Razavi, H. S., Kpodo, J., Eeswaran, R., Ciampitti, I., & Prasad, P. V. V. (2024). Enhancing crop yield prediction in Senegal using advanced machine learning techniques and synthetic data. Artificial Intelligence in Agriculture, 14, 99–114. https://doi.org/10.1016/j.aiia.2024.11.005

  3. Kpodo, J., Kordjamshidi, P., & Nejadhashemi, A. P. (2024). AgXQA: A benchmark for advanced Agricultural Extension question answering. Computers and Electronics in Agriculture, 225, 109349. https://doi.org/10.1016/J.COMPAG.2024.109349

  4. Banda, E., Rafiei, V., Kpodo, J., Nejadhashemi, A. P., Singh, G., Das, N. N., Kc, R., & Diallo, A. (2024). Millet yield estimations in Senegal: Unveiling the power of regional water stress analysis and advanced predictive modeling. Agricultural Water Management, 291. https://doi.org/10.1016/j.agwat.2023.108618.

  5. Ferriby, H., Nejadhashemi, A.P., Hernandez-Suarez, J.S., Moore, N., Kpodo, J., Kropp, I., Eeswaran, R., Belton, B. and Haque, M.M., 2021. Harnessing Machine Learning Techniques for Mapping Aquaculture Waterbodies in Bangladesh. Remote Sensing, 13(23), p.4890.

  6. Eeswaran, R., Nejadhashemi, A.P., Kpodo, J., Curtis, Z.K., Adhikari, U., Liao, H., Li, S.G., Hernandez-Suarez, J.S., Alves, F.C., Raschke, A. and Jha, P.K., 2021. Quantification of resilience metrics as affected by conservation agriculture at a watershed scale. Agriculture, Ecosystems & Environment, 320, p.107612.

Presentations

Invited Talks

Conferences

  1. Kpodo, J., P. Kordjamshidi, A.P. Nejadhashemi, 2024. Overcoming Challenges in Agricultural Extension with AgXQA and AgRoBERTa: A New Benchmark Dataset and Domain-Specific LLM. iEMSs 2024 Biennial Conference. East Lansing, USA.
  2. Kpodo, J., A.P. Nejadhashemi, 2024. Optimizing Digital Extension Platforms for Farmers: A Critical Analysis and Recommendations. iEMSs 2024 Biennial Conference. East Lansing, USA.
  3. Ghane, E., Y. Abdalaal, J. Kpodo, A.P. Nejadhashemi, M. Youssef, 2024. Development and Application of a DRAINMOD-based Decision-Support Tool for Optimizing the Performance of Saturated Buffers. iEMSs 2024 Biennial Conference. East Lansing, USA.
  4. Ghane, E., Y. Abdalaal, J. Kpodo, A.P. Nejadhashemi, M. Youssef, 2024. Application of a DRAINMOD-based Decision-Support Tool for Saturated Buffers. 79th SWCS International Annual Conference. Myrtle Beach, USA.
  5. Kpodo, J., A.P. Nejadhashemi, 2023. Advancing Smart Agriculture: Challenges and Opportunities in Extension Platforms. Alliance For Modernizing African Agrifood Systems Conference, Online.

Services

Peer Reviewer

Decision Support Tools