Nipuna Chamara

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Nipuna Chamara

Research Assistant Professor, Biological Systems Engineering Emphasis Area: Digital Agricultural Systems University of Nebraska-Lincoln

Contact

Address
CHA 207
Lincoln, NE 68583-0726,
Phone
BSE Front Desk 402-472-1413
Email
nchamara2@nebraska.edu
Website
Website
Social Media

Appointment 

  • 100% Research

Areas of Research and Professional Interests

  • Digital Agriculture (AI, IoT, Sensors, and Instrumentation)

  • Agricultural Machinery

  • Precision Agriculture

Teaching Interests

  • Digital Agriculture

  • Computer-Aided Design and Manufacturing

  • Electronics and Instrumentation for Agricultural Applications

  • AI for Agricultural Applications

Professional Memberships

  • American Society of Agricultural and Biological Engineers (ASABE)

  • Institute of Electrical and Electronics Engineers (IEEE)

  • International Society of Precision Agriculture (ISPA)

Teaching

  • BSEN 130 - Computer Aided Design (Fall/Spring)

Research Profiles:

Google Scholar Profile 

Research Gate

Education

  1. Ph.D., Biological Engineering, University of Nebraska-Lincoln, USA, (2024)
  2. M.Sc., Agricultural and Biological Engineering, University of Nebraska- Lincoln, USA, (2021)
  3. PG Diploma in Manufacturing Systems Engineering, University of Moratuwa, Sri Lanka, (2015)
  4. B.Sc., (Hons) Mechanical Engineering, University of Moratuwa, Sri Lanka, (2013)

 

Selected Publications 

  1. Chamara, N., Pan, Y., Taghvaeian, S., Walters, C., Proctor, C., Rudnick, D., Redfearn, D., & Ge, Y. (2026). Can generative AI make farming decisions? Current status and future pathways–A case study in row crop production with ChatGPT. Artificial Intelligence in Agriculture.
  2. Chamara, N., Ge, Y., & Russo, S. (2025). FireLog: An open-source, low-cost system for temperature logging during wildland fires with high spatial and temporal resolution. HardwareX, e00722.
  3. Balabantaray, A., Behera, S., Liew, C., Chamara, N., Singh, M., Jhala, A. J., & Pitla, S. (2024). Targeted weed management of Palmer amaranth using robotics and deep learning (YOLOv7). Frontiers in Robotics and AI, 11, 1441371.
  4. Chamara, N. (2024). Next-generation Crop Monitoring Technologies: Case Studies about Edge Image Processing for Crop Monitoring and Soil Water Property Modeling via Above-Ground Sensors (Doctoral dissertation, The University of Nebraska-Lincoln).
  5. Chamara, N., Bai, G., & Ge, Y. (2023). AICropCAM: Deploying classification, segmentation, detection, and counting deep-learning models for crop monitoring on the edge. Computers and Electronics in Agriculture, 215, 108420.
  6. Chamara, N., Islam, M. D., Bai, G. F., Shi, Y., & Ge, Y. (2022). Ag-IoT for crop and environment monitoring: Past, present, and future. Agricultural systems, 203, 103497.
  7. Chamara, N. (2021). Development of an Internet of Things (IoT) Enabled Novel Wireless Multi Sensor Network for Infield Crop Monitoring.
  8. Gamlath, R., Gunathilke, H. A. W. S., & Chamara, A. H. M. N. (2018). A study on the current status of mechanization of paddy cultivation in Sri Lanka: case of Anuradhapura District. In Proceedings of 17th Agricultural Research Symposium (Vol. 129, p. 133).

In the News

  1. Can AI help growers make smarter irrigation decisions?
  2. Winning contest entry shows AI's agricultural potential

Media

  1. Use of Generative AI (ChatGPT) in Irrigation Decision Making in Sprinkler Irrigated Row Crop Production: Lessons Learned and Future Potential.
  2. Generative and Physical AI for Crop Production Decision-Making: Current Progress and Future Directions