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Publications and Presentations

2022

Publications:

  • Bernard, G. C., Bolden-Tiller, O., Egnin, M., Bonsi, C., McKinstry, A., Landon, Z., Chen, Y. Y., Ritte, I., Archie, T., Shafait, M.D., Chowdhury, G., Charleston, C., Turner A., Brown, A., Idehen, O., Mitchell, I., Boone, J., Peterson C., Lockett, A. (2022). The Use of Autonomous Robots to Address Labor Demands and Improve Efficacy in Agriculture, COJ Rob Artificial Intelligence, 1(5). https://crimsonpublishers.com/cojra/pdf/COJRA.000523.pdf
  • Cisneros-Velarde, P., Lyu, B., Koyejo, S., Kolar, M. (2022). One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning, Arxiv, pre-print. https://arxiv.org/pdf/2205.15891.pdf
  • Kamtikar, S., Marri, S., Walt, B., Uppalapati, K. N., Krishnan, G., Chowdhary, G. (2022). Visual Servoing for Pose Control of Soft Continuum Arm in a Structured Environment,  IEEE Robotics and Automation Letters, 7(2). https://doi.org/5504-5511.10.1109/LRA.2022.3155821
  • Khanna, M., Atallah, S. S., Kar, S., Sharma, B., Wu, L., Yu, C., Chowdhary, G., Soman, C., Guan, K. (2022). Digital transformation for a sustainable agriculture in the United States: Opportunities and challenges. Agricultural Economics,00, 1-14. https://doi.org/10.1111/agec.12733
  • Khanna, M., Miao, R. (2022). Inducing the adoption of emerging technologies for sustainable intensification of food and renewable energy production: insights from applied economics. Australian Journal of Agricultural and Resource Economics, 66, 1-23. https://doi.org/10.1111/1467-8489.12461
  • Lai, T., Ji,. H., Zhai, C.X. (2022). Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking.  Findings of the Association for Computational Linguistics, 3696–3711. https://doi.org/10.48550/arXiv.2202.13404
  • Wang, S., Guan, K., Zhang, C., Lee, D., Margenot, A.J., Ge, Y., Peng, J., Zhou, W., Zhou, Q. and Huang, Y. (2022). Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing. Remote Sensing of Environment, 271, 112914. https://doi.org/10.1016/j.rse.2022.112914
  • Wu, J., He, J. (2022). A Unified Meta-Learning Framework for Dynamic Transfer Learning. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 3573-3579. https://doi.org/10.24963/ijcai.2022/496

Presentations

  • Adve, V. (2022, February). National AI Institutes program panel – Overview of AIFARMS [Panel presentation]. AAAI Conference on Artificial Intelligence. Online.
  • Adve, V. (2022, February). An overview of AIFARMS [Presentation]. Agricultural Genome to Phenome Initiative Field Day, Online. https://www.ag2pi.org/workshops-and-activities/field-day-2022-02-16/
  • Bolden-Tiller, O. (2022, February). Tuskegee University Project Updates/ Opportunities [Conference presentation]. 130th Annual Small Farmers Conference, Tuskegee, AL, United States.
  • He, J. (2022, February). Towards Understanding Rare Categories on Graphs [Conference presentation]. The International Workshop on Machine Learning on Graphs.
  • Tucker, C. (2022, February). History of Agriculture and Innovations [Education outreach presentation].National 4H Agriculture Innovators Challenge Training, Urbana, IL, United States.
  • Tong. H. (2022, February). NetFair: Toward the Why Question of Network Mining’ at Artificial Intelligence [Conference presentation]. Machine Learning and Data Science World Forum, Online.
  • He, J. (2022, February). Towards understanding rare categories of graphs [Conference presentation]. The international workshop on Machine Learning on graphs, Online.
  • Khanna, M. (2022, March). Economic Incentives for Robotic Weed Control in Row Crop Agriculture [Conference presentation]. DigiCrop 200 PhenoRob, Online. https://www.youtube.com/watch?v=PiTwrLT_JcE
  • Leakey, A. (2022, March). Bioenergy Research and Development for the Fuels and Chemicals of Tomorrow. Energy Subcommittee [Congressional House Committee]. Energy subcommittee hearing. Online. https://republicans-science.house.gov/hearings?ID=2E8CE7A5-616B-4794-A3EA-C88BE42D35BEHearing – Bioenergy Research and Development for the Fuels and Chemicals of Tomorrow – Hearings – House Committee on Science Space & Tech – Republicans
  • Guha, S. (2022, April). IoT Sensor networks for soil and water quality [Presentation]. Environmental Engineering Department, University of Wisconsin-Madison, Madison, WI, United States.
  • Bolden-Tiller, O., Bernard, G. C., Adve, V. S. (July, 2022). Can data science and Artificial Intelligence (AI) enable new collaborative platforms between diverse land-grant institutions and create more impactful outcomes? [Meeting, with presentations]. National Academies Sciences, Engineering, and Medicine. Online. https://www.nationalacademies.org/event/07-27-2022/enhancing-collaboration-and-deepening-impact-can-data-science-and-artificial-intelligence-ai-enable-new-collaborative-platforms-between-diverse-land-grant-institutions-and-create-more-impactful-outcomes
  • Wedow, J.M. (2022, July). AIFARMS Overview [Presentation]. The Internet of Things for Agriculture Summer Series, online. https://iot4ag.us/summerseries/
  • Wu, J., He, J. (2022, August). Domain Adaptation with Dynamic Open-Set Targets [Conference presentation]. Knowledge discovery and data mining (KDD), Washington DC, United States.
  • Yu, C. (2022, August). Economic Incentives for Robotic Weed Control in Row Crop Agriculture [Conference presentation]. Agricultural and Applied Economics Association Meetings, Anaheim, CA, United States.
  • Adve, V. (2022). A perspective on AI for Science [Panel discussion]. Communications of the ACM, Online.
  • Bernard, G.C. (2022). Current research and new agricultural technologies [Presentation]. Center for Research Excellence Symposium Research, Alcorn State University, Lorman, MS, United States.
  • Bernard, G.C. (2022). Current research developments, modern farming technologies, including autonomous farming and career readiness [Presentation]. North Carolina A&T State University, Greensboro, NC, United States.

2021

Publications:

  • Basso, B. (2021). Precision conservation for a changing climate. Nature Food, 2,322–323. https://doi.org/10.1038/s43016-021-00283-z
  • B. Basso, R. Martinez-Feria, R. A., Rill, L., Ritchie J. T. (2021). Contrasting long-term temperature trends reveal minor changes in projected potential evapotranspiration in the US Midwest. Nature Communications, 12, 1476. https://doi.org/10.1038/s41467-021-21763-7
  • Baquero A., Higuti V. A., Gasparino  M. V., Sivakumar A. N., Becker M., Chowdhary G. (2021). Multi-Sensor Fusion based Robust Row Following for Compact Agricultural Robots, Journal of Field Robotics. Journal of Field Robotics, 2, 1291-1319. https://doi.org/10.55417/fr.2022043
  • Graber, C., Tsai, G., Firman, M., Brostow, G., and Schwing, A. G. (2021). Panoptic Segmentation Forecasting, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), abs/2104.03962. 12517–12526. https://doi.org/10.48550/arXiv.2104.03962
  • Hu T.-T., Wang, J., Yeh, R. A., Schwing A, G. (2021). SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), abs/2105.08612. 1418–1428. https://doi.org/10.48550/arXiv.2105.08612
  • Jing, B., Tong, H., Zhu, Y. (2021). Network of Tensor Time Series. Proceedings of the Web Conference 2021 (WWW 2021), abs/2102.07736, 2425-2437. https://doi.org/10.1145/3442381.3449969
  • Khanna, M. (2021). Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications, Applied Economic Perspectives and Policy, 43(4), 1221-1242. https://doi.org/10.1002/aepp.13103
  • Kamtikar, S., Marri, S., Walt, B., Uppalapati, N. K., Krishnan, G., Chowdhary, G. (2021). Towards Autonomous Berry Harvesting using Visual Servoing of Soft Continuum Arm, Proceedings of AI for Agriculture and Food Systems. https://openreview.net/forum?id=nmFQlTk6WpV.
  • Maestrini, A., Basso, B. (2021). Subfield crop yields and temporal stability in thousands of US Midwest fields, Precision Agriculture, 22, 1749-1767. https://doi.org/10.1007/s11119-021-09810-1
  • Northrup, D. L., Basso, B., Wang, M. Q., Morgan, C. L. S., Benfey, P. N. (2021). Novel technologies for emission reduction complement conservation agriculture to achieve negative emissions from row-crop production, Proceedings of the National Academy of Sciences, 118(28). https://doi.org/10.1073/pnas.2022666118
  • Ren, Z., Misra, I., Schwing, A. G., Girdhar, R. (2021). 3D Spatial Recognition Without Spatially Labeled 3D, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), abs/2105.06461, 13204–13213. https://doi.org/10.48550/arXiv.2105.06461
  • Shirke A., Saifuddin, A., Luthra, A., Li, J., Williams, T., Hu, X., Kotnana, A., Kocabalkanli, O., Ahuja, N., Green-Miller, A., Condotta, I., Dilger, R., Caesar, M. (2021). Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras, AgEng2021, abs/2111.10971. https://doi.org/10.48550/arXiv.2111.10971
  • Wang, S., Guan, K., Wang, Z., Ainsworth, E.A., Zheng, T., Townsend, P.A., Liu, N., Nafziger, E., Masters, M.D., Li, K., Wu, G. (2021). Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling. International Journal of Applied Earth Observation and Geoinformation, 105, 102617. https://doi.org/10.1016/j.jag.2021.102617
  • Wu, J., He, J. (2021) Indirect Invisible Poisoning Attacks on Domain Adaptation, SIGKDD Conference on Knowledge Discovery & Data Mining, 1852–1862. https://doi.org/10.1145/3447548.3467214
  • Williams, T., Green-Miller, A. (2021). 4 Engineered Resilience in Livestock for Improved Animal Welfare, Journal of Animal Science, 99(Supp. 3), 1. https://doi.org/10.1093/jas/skab235.000
  • Xie, J. Fernandes, S., Mayfield-Jones, D., Erice, G., Choi, M., Lipka, A., Leakey, A. (2021). Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping, Plant Physiology, 187(3). https://doi.org/10.1093/plphys/kiab299.
  • Zhuang, P., Koyejo, O., Schwing, A. G. (2021). Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation, International Conference on Learning Representations, abs/2102.01187. https://doi.org/10.48550/arXiv.2102.01187

Presentations:

  • Khanna, M. (2021, August). Digital Transformation for a Sustainable Agriculture in the US: Opportunities and Challenges [Conference presentation]. International Conference of Agricultural Economists, Online.
  • Khanna, M. (2021, September). Economic Incentives for Robotic Weed Control [Presentation]. PhenoRob Cluster of Excellence – University of Bonn, Online.
  • Leakey, A. (2021, September). Phenotyping stomatal anatomy and function [Virtual workshop]. Society for Experimental Biology Environmental Physiology Group, Virtual Workshop on Field and Laboratory Techniques, Online.
  • Adve, V. (2021, October). Beyond ML in Agricultural Intelligence [Presentation]. Online.
  • Chowdhary, G. (2021, November). The robots are coming to you farm [Seminar]. Michigan State University, Robotics and Control seminar, Online.
  • Wang, H. (2021, November). Deep Active Learning for Agricultural Tasks [Flash talk]. Third International Workshop on Machine Learning for Cyber-Agricultural Systems, Online.
  • Wu, J. (2021, November). Adaptive Transfer Learning for Plant Phenotyping [Conference presentation]. Third International Workshop on Machine Learning for Cyber-Agricultural Systems, Online.
  • Bernard, G.C. (2021, December). Agricultural robots and Autonomous farming: Ag Modernization to improve efficacy in agricultural production [Conference presentation]. Professional Agricultural Worker’s Conference, Online. 
  • Kuhl, A.S., Guha, S., He, J., Tong, H., Margenot, A.J., Douglass, M., Kemner, J., Matamala, R. (2021, December). An AI Approach to Soil Health and Nutrient Management [Conference presentation]. American Geophysical Union Fall Meeting, New Orleans, LA, USA.
  • Margenot, A. (2021, December). AIFARMS – Soil Health and Monitory Thrust Summary [Conference presentation]. American Geophysical Union Fall Meeting, New Orleans, LA, United States.
  • Wang, S., Guan, K., Zhou, Q., Zhang, C., Jiang, C., Li, K., Qin, Z., Ainsworth, E.A., Margenot, A.J., Schaefer, D. Gentry, L. (2021, December). Airborne hyperspectral imaging of cover crop outcomes and tillage intensity in croplands by machine learning and radiative transfer modeling [Conference presentation]. American Geophysical Union Fall Meeting, New Orleans, LA, USA.

2020

Publications

  • Basso, B., Antle, J. (2020). Digital agriculture to design sustainable agricultural systems. Nature Sustainability, 3, 254–256. https://doi.org/10.1038/s41893-020-0510-0
  • Khanna, M. (2020). Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications, Applied Economic Perspectives and Policy, 43(4), 1221-1242. https://doi.org/10.1002/aepp.13103
  • Liu, I-J., Yeh. R., Schwing, A.G. (2020). High-Throughput Synchronous Deep RL, Advances in Neural Information Processing Systems, 1432. 17070–17080.  https://ioujenliu.github.io/HTS-RL/
  • Ren, Z., Yeh, R., Schwing, A.G. (2020). Not All Unlabeled Data Are Equal: Learning to Weight Data in Semi-Supervised Learning, Conference on Neural Information Processing Systems,1828, 21786-21797. https://doi.org/10.48550/arXiv.2007.01293
  • Sun, R., Fang, T., Schwing, A.G. (2020). Towards a Better Global Loss Landscape of GANs, Advances in Neural Information Processing Systems. https://doi.org/10.48550/arXiv.2011.04926

Presentations

  • A. Leakey, “The Phenomics of Stomata and Water Use Efficiency in C4 crops,” Virtual, Dec. 2020.
  • V. Adve, “Why Digital Agriculture is Fertile Ground for Software Systems Research,” SPLASH 2020, the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity, Nov. 19, 2020.
  • V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, Nov. 10, 2020.
  • V. Adve, “AIFARMS: Artificial Intelligence for Future Agricultural Resilience, Management and Sustainability,” Virtual, Oct. 07, 2020.
  • Andrew Leakey, The Phenomics of Stomata and Water Use Efficiency in C4 crops (October 2020). Martin and Ruth Massengale Lecture to the Annual Meeting of the Crop Science Society of AmericaAndrew Leakey, The Phenomics of Stomata and Water Use Efficiency in C4 crops (Feb 2021). University of Missouri Interdisciplinary Plant Group seminar