AI of Nature & AI for Nature 🦋🤖 | Teaching machines to understand biology & biology to inform AI | Prof @FIU ➡️ @UAlberta soon | Lab website: rdinnager.github.io/dinnage_lab_website
Reposted by Ingolf Kühn, Russell Dinnage
🌍 Share knowledge across species
🧬 Capture complex environmental relationships
📊 Work with limited data
🔮 Predict distributions for rare species
Preprint: biorxiv.org/content/10.1101/2024.10.15.618541v1
P.S. 'It's not magic.'
It's like having an AI ecologist that learns from millions of species observations to predict where ANY species might live.
Ask me about it and its applications at #Evol2025! 🧵👇
Reposted by Julia Koricheva, Russell Dinnage
We make the case for precision ecology—using big data & predictive tools to tailor conservation actions to local contexts.
Can ecology learn from medicine & marketing to boost impact? We think so.
Read it here: rdcu.be/eoaR4
#Conservation #Ecology #BigData
That's what I'll be discussing at #Evol2025 in Athens, Georgia - showing how AI reveals that evolution moves along curved paths, not straight lines.
June 24, 12:15pm, Computational Biology session. See you there? 🧵👇
Lab: rdinnager.github.io/dinnage_lab_website/
Code: github.com/rdinnager
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📚 NicheFlow: First foundation model for species distributions
🌸 PhenoVision: AI analyzing 53M field photos (98.5% accuracy!)
📦 Open-source R packages: slimr, ENMTools, phyr
I believe in democratizing computational methods for all biologists.
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Reposted by Daijiang Li
My mission: Create AI systems that understand life from molecules to ecosystems, bridging computational innovation with biological insight 🧬🤖
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Reposted by Russell Dinnage
youtu.be/yYSIhzb14QI