Previous MLCAS workshops: MLCAS2023; MLCAS2022

Today, efficient, cost-effective sensors as well as high performance computing technologies are looking to transform traditional plant-based agriculture into an efficient cyber-physical system. The easy availability of cheap, deployable, connected sensor technology has created an enormous opportunity to collect vast amounts of data at varying spatial and temporal scales at both experimental and production agriculture levels. Therefore, both offline and real-time agricultural analytics that assimilates such heterogeneous data and provides automated, actionable information is a critical need for sustainable and profitable agriculture.

Data analytics and decision-making for Agriculture has been a long-standing application area. The application of advanced Artificial Intelligence (AI) and Machine Learning (ML) methods to this critical societal need can be viewed as a transformative extension for the agriculture community. In this workshop, we intend to bring together academic and industrial researchers and practitioners in the fields of machine learning, data science and engineering, plant sciences and agriculture, in the collaborative effort of identifying and discussing major technical challenges and recent results related to machine learning-based approaches. It will feature invited talks, oral/poster presentations of accepted papers, and an Ag-ML competition.

Registration categories and fees (for MLCAS only)
Note: If you are registering for IPPS8 and planning to add MLCAS to your registration, you need to go through the IPPS8 website and follow the IPPS8 rules and regulations. For IPPS8, the Early Bird Registration closes on May 31, 2024 and Registration closes on August 15, 2024.
Category Before August 15 After August 15
Industry Professional $150 $200
Academia/Non-Profit/Start-Up $100 $150
Students $40 $75
Gold Sponsors
John Deere Logo Bayer Logo
Silver Sponsors
Corteva logo
Bronze sponsors

Call for Contributions

Target Participants

The theme of MLCAS 2024 will be "User-centric AI applications in Agriculture" to highlight and discuss real life deployments of AI and ML-enabled tools for a variety of agricultural decision support applications relevant for diverse stakeholders including farmers, plant breeders and plant scientists. We invite extended 2-page-abstract for oral and/or poster presentations on topics Including but not limited to machine learning applications to field-scale plant phenotyping (e.g., trait extraction), plant pathology (e.g., disease, pest, and weed scouting), plant breeding (e.g., yield prediction) and enabling smart farm management practices. We particularly encourage applications of recent AI advances such as multi-modal generative models, large language models (LLM), 3D geometric deep learning, scientific machine learning, deep reinforcement learning, robotic perception and learning-enabled control, uncertainty quantification and robust machine learning, in enabling and accelerating research in plant science and agriculture. We also encourage work that results in creating annotated benchmark datasets for ML in agriculture.

Guidelines
  • Guidelines for Extended abstract submissions: Up to 2 pages including figures and tables (excluding references). Extended abstract template.
  • Submission Guidelines: Submissions are through Microsoft CMT. If you do not have an Microsoft CMT account, please create one first. If you already have an Microsoft CMT account, please login to your account and enter as an author for MLCAS 2024 by following this link.
Procedure

Coming soon.

Important Dates
  • Submission open: May 15
  • Paper (extended abstract) deadline: July 15 (Monday, AoE)
  • Decision sent to authors: August 12
  • Competition date: See below

Workshop Organization

Organizing Committee
  • Soumik Sarkar, Professor, Mechanical Engineering, Iowa State University.
  • Arti Singh, Assistant Professor, Department of Agronomy, Iowa State University
  • Wei Guo, Associate Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.
  • Baskar Ganapathysubramanian, Professor, Mechanical Engineering, Iowa State University
  • Asheesh K. Singh, Professor, Department of Agronomy, Iowa State University.
  • James C. Schnable, Professor, Department of Agronomy and Horticulture, University of Nebraska-Lincoln.
  • Masayuki Hirafuji,Project Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.
  • Seishi Ninomiya, Project Professor, Field Phenomics Laboratory, Graduate School of Agriculture and Life Sciences, The University of Tokyo.

Keynote Speakers

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Coming soon

Program

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Proceedings

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Time zone:

Competition

Topic
Coming soon

Important Dates
  • June 28: Start Date
  • Aug 2: Team composition Deadline
  • Aug 16: Start of test phase
  • Aug 26: Final Submission Deadline
  • Aug 30: Announcement of Results
Award amounts
Coming soon
Datasets
Coming soon
Disclaimer

Paricipant teams must finalize their team members before the composition deadline on August 2. teams joining after August 2 cannot change their team member composition during the competition phase. Prizes will be awarded to the winning teams. Funds will be paid in the most efficient manner, typically a check to winners living in the US with payment to each team member (up to 5 participants maximum). The team contact can suggest the distribution for the team members. If a team has more than five participants, five or fewer participants need to be identified to receive the prize money. For teams outside the US, prize money will be wired to a single individual representing the team. We will need full wire instructions in an appropriate format. Please note that there will be a wire fee on the receiving end of the transaction based on the recipient's bank/financial institution. At this time, we are unable to send wires to Iran, Cuba, North Korea, or Syria, therefore no prizes will be awarded there. Please note that prizes are tax reportable in the United States. Tax forms are required for payment recipients. US Citizens or permanent US residents: Form W9 including social security number and Foreign individuals: Form W-8BEN

Contacts

For details regarding the competition, please contact us:

  • Nikee Shrestha, Center for Plant Science Innovation, University of Nebraska-Lincoln: nshrestha5@huskers.unl.edu
  • Timilehin Ayanlade, Translational AI Center, Iowa State University: ayanlade@iastate.edu

Sponsorship Information

  • Gold sponsors -- $10K, 4 free registrations, 1 sponsor table/booth
  • Silver sponsors -- $5K, 2 free registrations, 1 sponsor table/booth
  • Bronze sponsors -- $2K, 1 free registration
Translational AI Center Logo AI Institute for Resilient Agriculture COntext-Aware LEarning for Sustainable CybEr-agricultural (COALESCE) systems National Science Foundation National Institute of Food and Agriculture United States Department Of Agriculture Japan Science and Technology Agency Logo Sarabetsu Super Village