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.
| Category | Before August 15 | After August 15 |
|---|---|---|
| Industry Professional | $150 | $200 |
| Academia/Non-Profit/Start-Up | $100 | $150 |
| Students | $40 | $75 |
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.
Coming soon.
Time
|
Session Chair |
Activity |
|---|---|---|
| 8:30 - 9:00 AM | Breakfast and Welcome Address Dr. Soumik Sarkar |
|
| 9:00 - 9:45 AM | Dr. Arti Singh | Keynote: The Strength to Say “I Don't Know”: expanding neural networks to address out of distribution samples and ambiguous inputs Dr. Alina Zare - University of Florida |
| 9:45 - 10:15 AM | Invited Talk 1 Dr. Rick van de Zedde - Wageningen University & Research, The Netherlands |
|
| 10:15 - 10:30 AM | Break | |
| 10:30 - 11:00 AM | Dr. Wei Guo | Invited Talk 2: DIY Plant Phenotyping: Application of digital phenotyping techniques in plant research and breeding Dr. Sachiko Isobe - The University of Tokyo, Japan |
| 11:00 - 11:30 AM | Invited Talk 3: Navigation and Manipulation Challenges in Urban High Tunnels Girish Krishnan - University of Illinois |
|
| 11:30 AM - 12:15 PM | Flash Talks (12) | |
| 12:15 - 12:45 PM | Lunch | |
| 12:45 - 1:15 PM | Dr. Baskar Ganapathysubramanian | Lunch Plenary: (Really) Open AI for food security: Lessons for Lincoln from Lincoln Dr. David P. Hughes - The Pennsylvania State University |
| 1:15 - 1:45 PM | Invited Talk 4: Advancing Crop Improvement From the Ground Up with ML-Driven Analysis of Root Systems and Soil Properties Dr. Nadia Shakoor - Donald Danforth Plant Science Center |
|
| 1:45 - 3:00 PM | Dr. Soumik Sarkar | Panel Discussion: Translating AI-Ag Research into Practice Dr. Ryan Kirk - Head of Data Science, John Deere Siddarth Tata - Product Leader for Amazon Fresh Supply Chain (Grocery Program) and Amazon Kisan (Farmer Engagement Program) Meaghan Anderson - Field Agronomist in Central Iowa and Extension Field Specialist at Iowa State University Extension and Outreach Dr. Matthew Carroll - Analytics & Insights Lead, Iowa Soybean Association Dr. Pieter Blok - Assistant Professor, Lab of Field Phenomics, The University of Tokyo, Japan |
| 3:00 - 3:15 PM | Break | |
| 3:15 - 3:45 PM | Dr. James Schnable | Competition Presentations and Award Ceremony |
| 3:45 - 5:00 PM | Poster Session, Networking and Sponsor Booths |
MLCAS Corn Yield Prediction Using Satellite Data
The details for participation can be found here.
In addition to the awards listed above, an additional prize of $1000 may be awarded to the top team comprising only undergraduate or high school students that is not among the top 3 teams overall.
At least one member from a winning team is expected to attend MLCAS 2024 in-person to present their work and participate in the award ceremony. In addition to the cash prizes listed above, one member from each winning team will receive a free registration for MLCAS 2024. If no team member is able to attend in-person due to VISA or other travel issues, the team is encouraged to contact the MLCAS 2024 organizers to discuss their eligibility to win a prize.
Paricipant teams must finalize their team members before the composition deadline on August 4. teams joining after August 4 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.
For details regarding the competition, please contact us:
Webpage managed by Timilehin Ayanlade, Iowa State University. For any concerns please contact ayanlade@iastate.edu
Powered by Github-Pages and Bootstrap4