Though machine learning has achieved notable success in modeling sequential and spatial data for speech recognition and in computer vision, applications to remote sensing and climate science problems are seldom considered. In this paper, we demonstrate techniques from unsupervised learning of future video frame prediction, to increase the accuracy of ice flow tracking in multi-spectral satellite images. As the volume of cryosphere data increases in coming years, this is an interesting and important opportunity for machine learning to address a global challenge for climate change, risk management from floods, and conserving freshwater resources. Future frame prediction of ice melt and tracking the optical flow of ice dynamics presents modeling difficulties, due to uncertainties in global temperature increase, changing precipitation patterns, occlusion from cloud cover, rapid melting and glacier retreat due to black carbon aerosol deposition, from wildfires or human fossil emissions. We show the adversarial learning method helps improve the accuracy of tracking the optical flow of ice dynamics compared to existing methods in climate science. We present a dataset, IceNet, to encourage machine learning research and to help facilitate further applications in the areas of cryospheric science and climate change.

Recently, power systems are facing the challenges of growing power demand, depleting fossil fuel and aggravating environmental pollution (caused by carbon emission from fossil fuel based power generation). The incorporation of alternative low carbon energy generation, i.e., Renewable Energy Sources (RESs), becomes crucial for energy systems. Effective Demand Side Management (DSM) and RES incorporation enable power systems to maintain demand, supply balance and optimize energy in an environmentally friendly manner. The wind power is a popular energy source because of its environmental and economical benefits. However, the uncertainty of wind power makes its incorporation in energy systems really difficult.

Recently, power systems are facing the challenges of growing power demand, depleting fossil fuel and aggravating environmental pollution (caused by carbon emission from fossil fuel based power generation). The incorporation of alternative low carbon energy generation, i.e., Renewable Energy Sources (RESs), becomes crucial for energy systems. Effective Demand Side Management (DSM) and RES incorporation enable power systems to maintain demand, supply balance and optimize energy in an environmentally friendly manner. The wind power is a popular energy source because of its environmental and economical benefits. However, the uncertainty of wind power makes its incorporation in energy systems really difficult.

The summer of 2019 gave us some of the clearest examples yet of how climate change is transforming our world. The hottest June ever was followed up with the hottest July ever -- which also turned out to be the hottest month in recorded history. Scientists memorialized the first Icelandic glacier to lose glacier status and predicted the country would be glacier-free in 200 years. And unprecedented wildfires raged in the normally frozen Arctic, throwing up a smoke cloud nearly the size of Europe. The 2018 report from the International Panel on Climate Change gives us a stark time horizon: 20 years.

A fully autonomous ship called the "Mayflower" will make its voyage across the Atlantic Ocean next September, to mark the 400-year anniversary of the trip of the first Mayflower, which was very much not autonomous. It's a stark way to drive home just how much technology has advanced in the last four centuries, but also a key demonstration of autonomous seafaring technology, put together by marine research and exploration organization Promare and powered by IBM technology. The autonomous Mayflower will be decked out with solar panels, as well as diesel and wind turbines to provide it with its propulsion power, as it attempts the 3,220-mile journey from Plymouth in England, to Plymouth in Massachusetts in the U.S. The trip, if successful, will be among the first for full-size seafaring vessels navigating the Atlantic on their own, which Promare is hoping will open the doors to other research-focused applications of autonomous seagoing ships. To support that use case, it'll have research pods on board while it makes its trip. Three to be specific, developed by academics and researchers at the University of Plymouth, who will aim to run experiments in areas including maritime cybersecurity, sea mammal monitoring and even addressing the challenges of ocean-borne microplastics.

W e explore machine learning methods for AC Optimal Powerflow (ACOPF) - the task of optimizing power generation in a transmission network according while respecting physical and engineering constraints. W e present two formulations of ACOPF as a machine learning problem: 1) an end-to-end prediction task where we directly predict the optimal generator settings, and 2) a constraint prediction task where we predict the set of active constraints in the optimal solution.

Motivated by the recent advancements in deep Reinforcement Learning (RL), we develop an RL agent to manage the operation of storage devices in a household designed to maximize demand-side cost savings. The proposed technique is data-driven, and the RL agent learns from scratch on how to efficiently use the energy storage device under variable tariff-structures Contracting the concept of the "black box" where the techniques learned by the agent are ignored. We explain the learning progression of the RL agent, and the strategies it follows based on the capacity of the storage device.

At Toyota Research Institute (TRI), we're working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We're dedicated to building a world of "mobility for all" where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Our work is guided by a dedication to safety – in how we research, develop, and validate the performance of vehicle technology to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies.

At Toyota Research Institute (TRI), we're working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We're dedicated to building a world of "mobility for all" where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Our work is guided by a dedication to safety – in how we research, develop, and validate the performance of vehicle technology to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies.

At Toyota Research Institute (TRI), we're working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We're dedicated to building a world of "mobility for all" where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Our work is guided by a dedication to safety – in how we research, develop, and validate the performance of vehicle technology to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies.