"Neural Lander" Uses AI to Land Drones Smoothly


Professors Chung, Anandkumar, and Yue have teamed up to develop a system that uses a deep neural network to help autonomous drones "learn" how to land more safely and quickly, while gobbling up less power. The system they have created, dubbed the "Neural Lander," is a learning-based controller that tracks the position and speed of the drone, and modifies its landing trajectory and rotor speed accordingly to achieve the smoothest possible landing. The new system could prove crucial to projects currently under development at CAST, including an autonomous medical transport that could land in difficult-to-reach locations (such as a gridlocked traffic). "The importance of being able to land swiftly and smoothly when transporting an injured individual cannot be overstated," says Professor Gharib who is the director of CAST; and one of the lead researchers of the air ambulance project. [Caltech story]

Tags: research highlights Morteza Gharib Yisong Yue Soon-Jo Chung Animashree Anandkumar

Professor Anandkumar Receives 2018 Good Tech Award


Professor Animashree (Anima) Anandkumar has been recognized by the New York Times “good tech” awards as a leading Artificial intelligence (A.I.) researchers who uses “ technology to help others in real, tangible ways.” The New York Times article states, “Artificial intelligence will be one of the most important areas of computer science in the coming years. It’s also one of the least diverse. Just 12 percent of A.I. researchers are women, and the number of black and Latino executives in the field is vanishingly small… Anandkumar, Nvidia’s director of machine learning research and a professor at Caltech, saw that the name of the A.I. field’s marquee annual event — the Neural Information Processing Systems conference, or NIPS — had been used as fodder for sexist jokes. So she started a #ProtestNIPS campaign to change the name, and drew up a petition that gathered more than 2,000 signatures. Eventually, the conference’s board relented, and the event is now abbreviated as “NeurIPS.” It was a small gesture of inclusion that could go a long way toward making women feel more welcome in the field for years to come.” [NYTimes article] [Tensorial-Professor Anima on AI]

Tags: honors CMS Animashree Anandkumar

Award For Technical Clarity and Ease of Understanding


Animashree (Anima) Anandkumar, Bren Professor of Computing and Mathematical Sciences, and colleagues have won a Best Poster Award at the Neural Information Processing Systems (NIPS) MLtrain workshop. The submission was called “Tensor Regression Networks with TensorLy and MXNet” and the work showed that tensor contractions and regression layers are an effective replacement for fully connected layers in deep learning architectures. The MLtrain workshop focuses on making research more accessible through ipython notebooks and the submissions are judged based on the technical clarity and ease of understanding of the poster and the code. [View the poster]

Tags: honors CMS Animashree Anandkumar

Best Poster Award At Neural Information Processing Systems Conference


CMS postdoctoral scholar Qi (Rose) Yu, working with Professor Anandkumar, and graduate student Stephan Zheng, working with Professor Yue, have won the Best Poster Presentation Award at the 2017 Neural Information Processing Systems (NIPS) Time Series Workshop. Dr. Yu works on the challenge of long-term forecasting in environments with nonlinear dynamics such as those involving climate and traffic data. She is tackling this challenge uses Tensor-Train RNN which are a novel family of neural sequence models that learn nonlinear dynamics directly using higher order moments and high-order state transition functions. [View her poster]

Tags: honors CMS Yisong Yue Animashree Anandkumar postdocs Qi (Rose) Yu Stephan Tao Zheng

AWS and Caltech Partner to Accelerate AI and Machine Learning


From autonomous robotics to state of-the-art computer vision, Caltech and Amazon have a lot in common, including the belief that pushing the boundaries of artificial intelligence (AI) and machine learning (ML) will not only disrupt industries, but it will fundamentally change the nature of scientific research. As part of this two-year renewable research collaboration, Amazon will provide both financial support, in the form of funding for graduate fellowships, and computing resources, in the form of AWS Cloud credits, to accelerate the work of faculty and students at Caltech in these areas. [AWS AI Blog]

Tags: CMS Adam Wierman Pietro Perona Joel Tropp Yisong Yue Aaron Ames Animashree Anandkumar

Teaching Machines How to Learn


Animashree (Anima) Anandkumar, Bren Professor of Computing and Mathematical Sciences, develops efficient techniques to speed up optimization algorithms that underpin machine-learning systems. Speaking about the connections between industry and academia she explains,“bridging the gap between industry and academia is really important. It is a big part of what brought me to Caltech. The sooner we can take theory and deploy it practically, the faster innovation moves and the more impact it can have.” [Interview with Professor Anandkumar]

Tags: research highlights CMS Animashree Anandkumar