Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Award-Winning Researcher Trains Robots to Make Educated Guesses
Yen-Ling Kuo, an assistant professor of computer science at the University of Virginia, has been recognized for her significant contributions to robotics and automation. Last year, she received the IEEE Robotics and Automation Society’s inaugural Outstanding Women in Robotics and Automation Early Career Contribution Award for her paper, “Diff-DAgger: Uncertainty Estimation with Diffusion Policy for Robotic Manipulation.” This innovative research introduces a method that enhances robots' ability to identify and manage uncertainty during unfamiliar tasks, thereby reducing the need for human supervision and increasing task completion rates. Kuo’s journey began in Taiwan, where her fascination with science and technology was sparked by early exposure to programming and computer logic. After earning her degrees from National Taiwan University and MIT, she gained practical experience at Google, where she contributed to AI-driven shopping technologies. This experience motivated her to pursue a Ph.D. to deepen her understanding of neural networks. Her current research focuses on developing computational models that enable robots to interpret both explicit data and subtle social cues, aiming to replicate human-like reasoning in machines. Kuo's work has garnered attention from the National Science Foundation, which awarded her a five-year Career Award to support her research on human-robot interactions. As robotics and autonomous vehicles become more prevalent, Kuo envisions creating robots that can seamlessly integrate into social environments, enhancing human-robot collaboration.
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7 Ways New Engineers Can Flourish in the Age of AI
As new graduates enter the workforce, they are navigating a landscape where artificial intelligence (AI) is essential rather than optional. Successful engineers are learning to leverage AI as a tool rather than viewing it as competition. To remain competitive in this rapidly evolving field, experts recommend several strategies for young professionals. First, mastering fundamental skills in data structures, algorithms, and core programming languages like C++, Java, and Python is crucial. Understanding these basics enables engineers to effectively debug and optimize their work, even when using AI tools. Additionally, engineers should learn to collaborate with AI by crafting clear prompts, reviewing AI-generated code, and using AI to enhance productivity while exercising critical judgment. Building projects that demonstrate comprehensive system design is increasingly important, as employers seek candidates who can define requirements and deliver scalable, maintainable products. Early development of system design skills is also vital, as even junior engineers are expected to discuss responsible AI integration and system reliability. Strong communication skills are essential, as engineers must articulate design choices and collaborate within teams—an area where AI cannot replace human input. Continuous learning and curiosity about industry developments, new tools, and community engagement are also emphasized as key to staying relevant. Finally, engineers are encouraged to think beyond coding, focusing on problem-framing, architectural judgment, and ethical considerations in AI use. For ongoing career insights, professionals can subscribe to the IEEE Spectrum Career Alert Newsletter, which offers biweekly updates on jobs, education, and the engineering workplace.
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The USC Professor Who Pioneered Socially Assistive Robotics
Maja Matarić, a professor at the University of Southern California, has been a pioneering force in the field of socially assistive robotics since co-defining the area in 2005. Her work focuses on developing robots that provide personalized therapy and support through social interactions, particularly for individuals with anxiety, depression, and autism spectrum disorder. Matarić's research has led to the creation of robots like Bandit, which helps children with autism improve communication skills, and Blossom, designed to assist students in practicing cognitive behavioral therapy (CBT). Recently, Matarić was honored with the 2025 Robotics Medal from MassRobotics, recognizing her contributions to advancing robotics. The award ceremony took place in Boston, where she expressed her joy and gratitude for the support of her peers. Matarić's journey began in Belgrade, Serbia, and she credits her family for inspiring her interest in engineering and computer science. Her current research includes a clinical trial funded by the U.S. National Institute of Mental Health, exploring the effectiveness of Blossom in delivering CBT to students. The trial involves 120 participants and aims to assess the robot's ability to adapt to individual user preferences while measuring their mental health outcomes. Matarić emphasizes the importance of combining engineering with psychology in her work and encourages her students to engage with professional communities like IEEE, which she joined as a graduate student in 1992.
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Sarang Gupta Builds AI Systems With Real-World Impact
Sarang Gupta, a data scientist at OpenAI in San Francisco, has leveraged his childhood curiosity and engineering skills to make significant contributions to the field of artificial intelligence. From a young age, Gupta demonstrated a knack for problem-solving, fixing household items and later developing software solutions, including an online ordering system for a local restaurant. After earning dual degrees in industrial engineering and business management from the Hong Kong University of Science and Technology, he began his career at Goldman Sachs, where he automated trade reconciliation processes, enhancing operational efficiency. In 2020, Gupta earned a master's degree in data science with a focus on AI from Columbia University, where he collaborated on projects that aimed to improve journalism through technology. He then joined Asana as a product data scientist, leading the launch of AI-powered features to enhance user experience. His work gained momentum alongside the rise of generative AI, prompting him to transition to OpenAI in September 2025. At OpenAI, Gupta collaborates with the marketing team to develop data-driven models that optimize customer outreach and measure the effectiveness of various marketing channels. He emphasizes the transformative potential of AI across industries and plans to continue his work in this rapidly evolving field. Gupta, an IEEE member since 2024, values the organization for its resources and networking opportunities, which he believes inspire and enhance his professional journey.
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30 Years Ago, Robots Learned to Walk Without Falling
Honda's Prototype 2 (P2), a groundbreaking autonomous humanoid robot, will be honored as an IEEE Milestone during a dedication ceremony on April 28 at the Honda Collection Hall in Japan. Developed in 1996, P2 was the first robot capable of walking without falling, marking a significant advancement in robotics. The IEEE Nagoya Section highlighted that P2 demonstrated the feasibility of humanlike locomotion, setting new standards in the field. The journey to create P2 began in 1986 when Honda researchers aimed to develop a "domestic robot" that could assist with household tasks. Through extensive analysis of human movement and numerous prototypes, the team successfully engineered P2 to walk, climb stairs, and perform various tasks autonomously. This innovation shifted the focus of robotics from industrial applications to designs centered on human interaction. P2's influence extends beyond its initial release, inspiring advancements in humanoid robots and contributing to research in biomechanics and artificial intelligence. The recognition as an IEEE Milestone underscores P2's role in propelling the field of humanoid robotics forward, demonstrating the potential for robots to assist humans in meaningful ways. The plaque commemorating this achievement will be installed at the Honda Collection Hall, celebrating the technical benchmarks set by P2 in mobility, autonomy, and human-robot interaction.
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