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Natural disasters are one of the oldest threats to not just individuals but to the societies they co-exist in. As a result, humanity has ceaselessly sought way to provide assistance to people in need after disasters have struck. Further, natural disasters are but a single, extreme example of the many possible humanitarian crises. Disease outbreak, famine, and oppression against disadvantaged groups can pose even greater dangers to people that have less obvious solutions.
In this proposed workshop, we seek to bring together the Artificial Intelligence (AI) and Humanitarian Assistance and Disaster Response (HADR) communities in order to bring AI to bear on real-world humanitarian crises.
Through this workshop, we intend to establish meaningful dialogue between the communities.
By the end of the workshop, the NeurIPS research community can come to understand the practical challenges of in aiding those in crisis, while the HADR can understand the landscape that is the state of art and practice in AI.
Through this, we seek to begin establishing a pipeline of transitioning the research created by the NeurIPS community to real-world humanitarian issues.
Fri 8:00 a.m. - 8:15 a.m.
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Introduction and Welcome
(Programmatic)
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Ritwik Gupta · Sandra Sajeev 🔗 |
Fri 8:15 a.m. - 10:15 a.m.
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Invited Talks (x4)
(Talks)
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Yossi Matias · Tracy Adole · Jason M Brown · Alejandro Jaimes 🔗 |
Fri 10:15 a.m. - 10:30 a.m.
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Break
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🔗 |
Fri 10:30 a.m. - 12:00 p.m.
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Spotlight Talks 1
(Talks)
Paper IDs * 8 - "Two Case Studies of Building Modeling using Machine Learning" * 9 - "Feature Engineering for Entity Resolution with Arabic Names: Improving Estimates of Observed Casualties in the Syrian Civil War" * 12 - "Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector" * 13 - "FireNet: Real-time Segmentation of Fire Perimeter from Aerial Video" * 14 - "Deep Crowd-Flow Prediction in Built Environments" * 15 - "Few-shot Tweet Detection in Emerging Disaster Events" |
Chaofeng Wang · Niccolo Dalmasso · Jigar Doshi · Junghoon Seo · Mubbasir Kapadia · Anna Kruspe 🔗 |
Fri 12:00 p.m. - 1:30 p.m.
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Lunch
(Food)
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🔗 |
Fri 1:30 p.m. - 2:30 p.m.
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Invited Talks (x2)
(Talks)
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Eric Rasmussen · Megan Stromberg 🔗 |
Fri 2:30 p.m. - 3:30 p.m.
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Spotlight Talks 2
(Talks)
Paper IDs * 18 - "Flood Detection On Low Cost Orbital Hardware" * 19 - "Machine Learning for Generalizable Prediction of Flood Susceptibility" * 20 - "Inundation Modeling in Data Scarce Regions" * 24 - "Explainable Semantic Mapping for First Responders" |
Josh Veitch-Michaelis · Chelsea Sidrane · Sella Nevo · Jean Oh 🔗 |
Fri 3:30 p.m. - 3:45 p.m.
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Break
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🔗 |
Fri 3:45 p.m. - 4:30 p.m.
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Spotlight Talks 3
(Talks)
Paper IDs * 7 - "Language Transfer for Early Warning of Epidemics from Social Media" * 26 - "Cognitive Agent Based Simulation Model For Improving Disaster Response Procedures" * 27 - "Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks" |
Patrick Schrempf · Rohit K. Dubey · Wenhan Lu 🔗 |
Fri 4:30 p.m. - 5:15 p.m.
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Convergence: Two-Way Limitations in Taking Theory to Applications
(Panel Discussion)
Speakers from Berkeley, Oak Ridge National Lab, Red Cross, and more. |
Rachel Dzombak · Lexie Yang · 🔗 |
Fri 5:15 p.m. - 6:00 p.m.
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Poster Session
(Posters)
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🔗 |
Author Information
Ritwik Gupta (Carnegie Mellon University - Software Engineering Institute)
I am currently a first year Ph.D. student at the University of California, Berkeley co-advised by Drs. Trevor Darrell and Shankar Sastry. My focus is on efficient machine learning for humanitarian assistance and disaster response and the polciy surrounding the use of ML in developing areas. I am also the Founder and President of Neural Tangent, a company aimed at creating ML solutions to humanitarian assistance and disaster response problems. I also provide consulting in the space of machine learning, artificial intelligence, edge computing, and remote sensing.
Robin Murphy (Texas A&M University)
Trevor Darrell (UC Berkeley)
Eric Heim (Carnegie Mellon University, Software Engineering Institute)
Zhangyang Wang (TAMU)
Bryce Goodman (Defense Innovation Unit)
Piotr Biliński (University of Warsaw / University of Oxford)
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2014 Poster: Weakly-supervised Discovery of Visual Pattern Configurations »
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2013 Poster: Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies »
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2012 Poster: Learning with Recursive Perceptual Representations »
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2012 Poster: Timely Object Recognition »
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