Shinji Watanabe, an associate professor in Carnegie Mellon University's School of Computer Science, has been named a fellow of the International Speech Communication Association (ISCA) "for wide-ranging, fundamental contributions to research and leadership in speech recognition technologies." Founded in 2007, the ISCA Fellows Program recognizes and honors outstanding ISCA members who have made significant contributions to the science and technology of speech communication. Fellows are nominated by association members and selected by a committee of their peers. Since its inception, the program has recognized nearly 100 fellows from countries around the globe. Watanabe, who is part of CMU's Language Technologies Institute, studies automatic speech recognition, speech enhancement, spoken language understanding, and machine learning for speech and language processing.

Their paper "Hierarchical Collision Avoidance for Adaptive-Speed Multirotor Tele-Operation" was selected out of 56 accepted papers.

Research from Carnegie Mellon University's Robotics Institute could one day allow robots to seamlessly open drawers, doors and lids on hinges. While humans interact with various articulated objects daily -- opening a refrigerator door or lifting a toilet seat are good examples -- these tasks present a challenge in robotics. Ben Eisner and Harry Zhang, both graduate students in Assistant Professor David Held's Robots Perceiving and Doing Lab, designed a new way to train robots to perceive and manipulate articulated objects in their project, "FlowBot3D: Learning 3D Articulation Flow To Manipulate Articulated Objects." The team presented their research at Robotics: Science and Systems this year, where it was a finalist for a best paper award. FlowBot3D uses a vision-based system to help robots learn how to interact with many different kinds of articulated objects.

Gather AI, a startup using drones to inventory items in warehouses, today announced that it raised $10 million in a Series A round led by Tribeca Venture Partners with participation from Xplorer Capital, Dundee Venture Capital, Expa, Bling Capital, XRC Labs and 99 Tartans. The proceeds bring the company's total raised to $17 million, which CEO Sankalp Arora says is being put toward expanding Gather's deployment capacity and go-to-market plans as well as hiring new machine learning engineers. Arora co-founded Gather AI in 2019 with Daniel Maturana and Geetesh Dubey, graduate students at Carnegie Mellon's Robotics Institute. The trio had the idea to use drones to gather data -- specifically data in warehouses, such as the number of items on a shelf and the locations of particular pallets. Over the course of several years, they designed a prototype of an inventory monitoring system that used off-the-shelf autonomous drones, which became Gather's core product.

Two School of Computer Science students were part of teams awarded 2022 Qualcomm Innovation Fellowships for their work in pose estimation and optimization in distributed deep learning. As part of the program, each team will receive $100,000 in funding and mentoring from Qualcomm engineers. Zhengyi Luo, a Ph.D. student in the Robotics Institute (RI), and Yu-Jhe Li, a Ph.D. student in the Electrical and Computer Engineering Department, are researching pose estimation, an essential component for human-like 3D avatars in games or sci-fi-like telepresence. They were nominated for their proposal "Near- and Far-Field Sensor Fusion for 3D Body Pose Estimation and Tracking," which merges the two sensing techniques and leverages the advantages of each. By fusing the two data streams, their work could enhance the quality of immersive mixed-reality experiences.

On this episode of Yinzer Backstage Pass, I paid a visit to the Robotics Institute at Carnegie Mellon University in Oakland. We followed faculty member Matt Travers down a set of stairs into the basement of the building. It was a cavernous space -- lots of piled boxes and miscellaneous storage -- but that turns out to be the perfect space to train the robots that he has been developing. We turned the corner and entered the "MattLab," which was buzzing with activity. More than a dozen grad students were typing on desktops, tinkering with remote controls and referencing huge monitors displaying incomprehensible charts and data.

A team of researchers at Carnegie Mellon University believe they have developed the first AI pilot that enables autonomous aircraft to navigate a crowded airspace. The artificial intelligence can safely avoid collisions, predict the intent of other aircraft, track aircraft and coordinate with their actions, and communicate over the radio with pilots and air traffic controllers. The researchers aim to develop the AI so the behaviors of their system will be indistinguishable from those of a human pilot. "We believe we could eventually pass the Turing Test," said Jean Oh, an associate research professor at CMU's Robotics Institute (RI) and a member of the AI pilot team, referring to the test of an AI's ability to exhibit intelligent behavior equivalent to a human. To interact with other aircraft as a human pilot would, the AI uses both vision and natural language to communicate its intent with other aircraft, whether piloted or not.

Three Carnegie Mellon University researchers in the School of Computer Science recently earned Faculty Early Career Development Program (CAREER) awards from the National Science Foundation. The awards are the foundation's most prestigious for young faculty researchers. An assistant professor in the Computer Science and Electrical and Computer Engineering departments, Weina Wang received $500,000 to develop algorithms that guarantee ultra-low latency in edge computing, which supports emerging applications such as autonomous driving, augmented reality and automated mobile robots. This work will establish algorithms to optimize the time it takes for data to travel from one point to another and for the corresponding computation to be done without lag, even with a high volume of users in those systems. In addition to this research, Wang will also use the grant to continue expanding STEM outreach activities for K-12 students -- mentoring students from underrepresented groups, promoting the visibility of researchers from underrepresented groups and initiating online outreach seminars for the general public.

Researchers at Carnegie Mellon University's Argo AI Center for Autonomous Vehicle Research developed a system to use lidar data to visualize not just where other moving objects are on the roads now, but also where they are likely to be in a few seconds. This method enables autonomous vehicles (AVs) to better plan for the motions of cars, pedestrians and other moving objects around it. Using the moving object's current position, velocity and trajectory, their method, FutureDet, creates several possible future paths in lidar, ranks them by the confidence it has that the moving object will follow the predicted path, and shows all these paths to the AV as if they were occurring in real-time. FutureDet then sees how the AV plans to respond to each path. "This method basically takes in lidar measurements and spits out the possible future locations of objects," said Deva Ramanan, a professor in the School of Computer Science's Robotics Institute, head of the Argo AI Center, an Argo principal scientist and the supervising researcher on the paper.

Yet large amounts of clinical data may not be sufficient for use in AI because little data is labeled, and it is not always apparent whether data represent healthy patients or sick patients without human guidance. One priority is thus to develop new, efficient methods of capturing human expertise so that machines can understand the contexts that may not be well represented in the available data. That is crucial for applying AI to health care, but also important for equipment maintenance in the military, which is seeing retirements of an entire generation of veteran maintainers.