Timezone: »
The focus on this panel is the use of AI for Sustainable Development and will explore the many opportunities this technology presents to improve lives around the world, as well as address the challenges and barriers to its applications. While there is much outstanding work being done to apply AI to such situations, too often this research is not deployed and there is a disconnect between the research and industry communities and the public sector actors. With leading researchers and practitioners from across the academic, public, UN and private sectors this panel brings a diversity of experience to address these important issues.
Audience members are invited to submit questions at: https://app.sli.do/event/skexhgej/live/questions
Facilitator: I am an Assistant Professor in the Institute for Software Research in the School of Computer Science at Carnegie Mellon University.
Speaker bio: Carla Gomes is a Professor of Computer Science and the Director of the Institute for Computational Sustainability at Cornell University. Her research area is artificial intelligence with a focus on large-scale constraint-based reasoning, optimization and machine learning. She is noted for her pioneering work in developing computational methods to address challenges in sustainability.
Dr. Miguel Luengo-Oroz is the Chief Data Scientist at UN Global Pulse, an innovation initiative of the United Nations Secretary-General. He is the head of the data science teams across the network of Pulse labs in New York, Jakarta & Kampala. Over the last decade, Miguel has built and directed teams bringing data and AI to operations and policy through innovation projects with international organizations, govs, private sector & academia. He has worked in multiple domains including poverty, food security, refugees & migrants, conflict prevention, human rights, economic indicators, gender, hate speech and climate change.
Thomas G. Dietterich: Dr. Dietterich is Distinguished Emeritus Professor of computer science at Oregon State University and currently pursues interdisciplinary research at the boundary of computer science, ecology, and sustainability policy.
Julien Cornebise is an Honorary Associate Professor at University College London. He focuses on putting Machine Learning firmly into the hands of nonprofits, certain part of certain, governments, NGOs, UN agencies: those who actually work on tackling our societies' biggest problems: . He built and until recently was a Director of Research of Element AI's AI for Good team, and head of its London Office. Prior to this, Julien was at DeepMind (later acquired by Google) as an early employee, where he led several fundamental research projects used in early demos and fundraising then co-created its Health Research team. Since leaving DeepMind in 2016, he has been working with Amnesty International, Human Rights Watch, and other actors. Julien holds an MSc in Computer Engineering, an MSc in Mathematical Statistics, and a PhD in Mathematics, specialized in Computational Statistics, from University Paris VI Pierre and Marie Curie and Telecom ParisTech. He received the 2010 Savage Award in Theory and Methods from the International Society for Bayesian Analysis for his PhD work.
Author Information
Fei Fang (Carnegie Mellon University)
Carla Gomes (Cornell University)
Miguel Luengo-Oroz (United Nations)
Thomas Dietterich (Oregon State University)
Julien Cornebise (University College London)
More from the Same Authors
-
2021 : Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification »
Junwen Bai · Shufeng Kong · Carla Gomes -
2021 : Deep Gaussian Processes for Preference Learning »
Rex Chen · Norman Sadeh · Fei Fang -
2021 : Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label Classification »
Junwen Bai · Shufeng Kong · Carla Gomes -
2021 : Resolving Super Fine-Resolution SIF via Coarsely-Supervised U-Net Regression »
Joshua Fan · Di Chen · Jiaming Wen · Ying Sun · Carla Gomes -
2021 : A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction »
Joshua Fan · Junwen Bai · Zhiyun Li · Ariel Ortiz-Bobea · Carla Gomes -
2022 : Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction »
Junwen Bai · Yuanqi Du · Yingheng Wang · Shufeng Kong · John Gregoire · Carla Gomes -
2022 : Structure-based Drug Design with Equivariant Diffusion Models »
Arne Schneuing · Yuanqi Du · Charles Harris · Arian Jamasb · Ilia Igashov · weitao Du · Tom Blundell · Pietro Lió · Carla Gomes · Max Welling · Michael Bronstein · Bruno Correia -
2023 Workshop: AI for Science: from Theory to Practice »
Yuanqi Du · Max Welling · Yoshua Bengio · Marinka Zitnik · Carla Gomes · Jure Leskovec · Maria Brbic · Wenhao Gao · Kexin Huang · Ziming Liu · Rocío Mercado · Miles Cranmer · Shengchao Liu · Lijing Wang -
2022 Workshop: AI for Science: Progress and Promises »
Yi Ding · Yuanqi Du · Tianfan Fu · Hanchen Wang · Anima Anandkumar · Yoshua Bengio · Anthony Gitter · Carla Gomes · Aviv Regev · Max Welling · Marinka Zitnik -
2022 Poster: Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning »
Dieqiao Feng · Carla Gomes · Bart Selman -
2022 Poster: Open High-Resolution Satellite Imagery: The WorldStrat Dataset – With Application to Super-Resolution »
Julien Cornebise · Ivan Oršolić · Freddie Kalaitzis -
2021 : (Live) Panel Discussion: Cooperative AI »
Kalesha Bullard · Allan Dafoe · Fei Fang · Chris Amato · Elizabeth M. Adams -
2021 : A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction »
Joshua Fan · Junwen Bai · Zhiyun Li · Ariel Ortiz-Bobea · Carla Gomes -
2021 : Resolving Super Fine-Resolution SIF via Coarsely-Supervised U-Net Regression »
Joshua Fan · Di Chen · Jiaming Wen · Ying Sun · Carla Gomes -
2021 Poster: Towards Deeper Deep Reinforcement Learning with Spectral Normalization »
Nils Bjorck · Carla Gomes · Kilian Weinberger -
2021 Poster: Contrastively Disentangled Sequential Variational Autoencoder »
Junwen Bai · Weiran Wang · Carla Gomes -
2020 : Keynote: Tom Diettrich »
Thomas Dietterich -
2020 Poster: A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances »
Dieqiao Feng · Carla Gomes · Bart Selman -
2019 : Automated Quality Control for a Weather Sensor Network »
Thomas Dietterich -
2019 : Invited talk: Fei Fang (CMU) »
Fei Fang -
2019 : Carla Gomes (Cornell) »
Carla Gomes -
2019 : Lunch Break and Posters »
Xingyou Song · Elad Hoffer · Wei-Cheng Chang · Jeremy Cohen · Jyoti Islam · Yaniv Blumenfeld · Andreas Madsen · Jonathan Frankle · Sebastian Goldt · Satrajit Chatterjee · Abhishek Panigrahi · Alex Renda · Brian Bartoldson · Israel Birhane · Aristide Baratin · Niladri Chatterji · Roman Novak · Jessica Forde · YiDing Jiang · Yilun Du · Linara Adilova · Michael Kamp · Berry Weinstein · Itay Hubara · Tal Ben-Nun · Torsten Hoefler · Daniel Soudry · Hsiang-Fu Yu · Kai Zhong · Yiming Yang · Inderjit Dhillon · Jaime Carbonell · Yanqing Zhang · Dar Gilboa · Johannes Brandstetter · Alexander R Johansen · Gintare Karolina Dziugaite · Raghav Somani · Ari Morcos · Freddie Kalaitzis · Hanie Sedghi · Lechao Xiao · John Zech · Muqiao Yang · Simran Kaur · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · Sho Yaida · Zachary Lipton · Daniel Roy · Michael Carbin · Florent Krzakala · Lenka Zdeborová · Guy Gur-Ari · Ethan Dyer · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Behnam Neyshabur · Praneeth Netrapalli · Kris Sankaran · Julien Cornebise · Yoshua Bengio · Vincent Michalski · Samira Ebrahimi Kahou · Md Rifat Arefin · Jiri Hron · Jaehoon Lee · Jascha Sohl-Dickstein · Samuel Schoenholz · David Schwab · Dongyu Li · Sang Keun Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 : Climate Change: A Grand Challenge for ML »
Yoshua Bengio · Carla Gomes · Andrew Ng · Jeff Dean · Lester Mackey -
2019 : Translating AI Research into operational impact to achieve the Sustainable Development Goals »
Miguel Luengo-Oroz -
2019 : Computational Sustainability: Computing for a Better World and a Sustainable Future »
Carla Gomes -
2019 Workshop: Joint Workshop on AI for Social Good »
Fei Fang · Joseph Aylett-Bullock · Marc-Antoine Dilhac · Brian Green · natalie saltiel · Dhaval Adjodah · Jack Clark · Sean McGregor · Margaux Luck · Jonathan Penn · Tristan Sylvain · Geneviève Boucher · Sydney Swaine-Simon · Girmaw Abebe Tadesse · Myriam Côté · Anna Bethke · Yoshua Bengio -
2018 : Academia, Corporations, Society, Responsibility »
David Danks · Julien Cornebise · Lisa Di Jorio -
2018 : Exploiting data and human knowledge for predicting wildlife poaching »
Fei Fang -
2018 Poster: Understanding Batch Normalization »
Johan Bjorck · Carla Gomes · Bart Selman · Kilian Weinberger -
2016 Poster: Solving Marginal MAP Problems with NP Oracles and Parity Constraints »
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman -
2013 Workshop: Machine Learning for Sustainability »
Edwin Bonilla · Thomas Dietterich · Theodoros Damoulas · Andreas Krause · Daniel Sheldon · Iadine Chades · J. Zico Kolter · Bistra Dilkina · Carla Gomes · Hugo P Simao -
2013 Poster: Embed and Project: Discrete Sampling with Universal Hashing »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2012 Poster: Density Propagation and Improved Bounds on the Partition Function »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Poster: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Spotlight: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2006 Poster: Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints »
Carla Gomes · Ashish Sabharwal · Bart Selman