Tag: robotics

MIT in the News: Financial Aid, 3D Printing, Cancer Research, and I.M. Pei Archive

MIT continues to make headlines with groundbreaking research, innovative startups, and transformative educational initiatives. Here is a roundup of recent media coverage highlighting MIT’s impact across diverse fields.

Free Tuition Program Gains Attention

Fortune reporter Emma Burleigh spotlights MIT’s financial aid programs that provide free tuition to students whose parents earn less than $200,000 a year. Additionally, tuition, housing, dining, fees, books, and personal expenses for students with parental incomes of less than $100,000 are covered by MIT. “Famed research university MIT is not only footing the tuition bill of its lower-income students—it’s making ‘free college’ a reality,” writes Burleigh.

VulcanForms to Create Over 1,000 Jobs

For The Boston Globe, reporter Aaron Pressman features MIT startup VulcanForms, a 3D printing manufacturer expected to create over 1,000 jobs with a new 1-million-square-foot plant in Devens, MA. The facility will bring capacity for more customers in medical devices, aerospace and defense, and consumer goods industries. “MIT professor John Hart started the company with grad student Martin Feldmann [’14] as a way to bring 3D printing techniques using lasers and powdered metals to larger-scale manufacturing jobs,” writes Pressman.

Colon Cancer Cells Can Change Identity

MIT researchers have found that colon cancer cells can “change their identity, allowing them to travel through the body and form new tumors,” reports Daniella Gray for Newsweek. The findings could point to future treatments that can prevent metastasis—the leading cause of death for colorectal cancer patients, Gray explains.

I.M. Pei Archive Donated to MIT Museum

For Archinect, reporter Niall Patrick Walsh spotlights how the full archive of architect and alumnus I.M. Pei ’40 has been donated to the MIT Museum. “Among the materials are drawings and documents from some of Pei’s best-known works, including the Louvre Museum modernization project in Paris, the John F. Kennedy Presidential Library and Museum in Boston, and the Rock and Roll Hall of Fame in Cleveland,” writes Walsh. “The archive also contains records relating to four buildings designed by Pei on the MIT campus: the Green Building, Dreyfus Building, Landau Building, and Wiesner Building.”

Schwarzman College of Computing Prepares Students for AI Era

Chronicle of Philanthropy reporter Maria Di Mento spotlights how the creation of the MIT Schwarzman College of Computing allowed MIT to develop new “interdisciplinary programs to prepare students for an AI-saturated world and help them understand the social and ethical implications of digital technologies.” Prof. Daniel Huttenlocher, dean of the Schwarzman College of Computing, explains that: “MIT realized that effective education in the age of AI has to look different than it has in the past. Traditional siloing of expertise won’t work when AI is expected to touch nearly every part of people’s lives and is changing the way people in disciplines outside of computing are advancing their work.”

New Robot System Describes Objects in Plain English

Writing for Forbes, contributor Ron Schmelzer highlights Describe Anything, Anywhere, at Any Moment (DAAAM), a new system developed by MIT researchers that could enable robots to capture details of objects they see while exploring an environment. In the future, the system could allow factory workers to send robotic assistants to find items. DAAAM “lets a robot build a detailed map of a space, attach descriptions to objects in that map, and answer plain English questions later,” Schmelzer explains.

Air-Guardian System Enhances Flight Safety

Writing for Forbes about efforts to improve air travel safety, Tanya Eves highlights the Air-Guardian system, an eye-tracking monitor for pilots developed by CSAIL researchers that assists when attention wavers. “In tests, it reduced flight risk and improved navigation success rates,” writes Eves. “It’s a model for how the virtual co-pilot relationship should work: not replacement, but a seamless, intelligent partnership that understands when to act and when to stay silent.”

AI’s Impact on Jobs and Economy

Prof. Simon Johnson discusses the impact of AI on jobs in an interview with Financial Times reporters Delphine Strauss and Sam Fleming. “We are trying very hard at MIT to find ways to incorporate AI into the curriculum but to push harder on the entrepreneurship angle, the creation of new products and services, the development of critical thinking,” says Johnson.

In a separate piece for Bloomberg, Prof. Simon Johnson and Prof. Elisabeth Reynolds describe how the U.S. can maintain its technological leadership by investing in research focused on critical minerals, semiconductors, biotechnology, quantum computing, drones and advanced manufacturing.

In an interview with Fortune, Prof. Daron Acemoglu discusses AI’s economic impact and estimates AI will deliver roughly 0.55% in total factor productivity gains.

Solar-Electric Boat Launches on Charles River

For Axios Boston, reporter Steph Solis highlights “Anita,” a solar-electric boat created by alumnus James Worden ’89 that is due to launch this year. The boat was previewed at the 80th anniversary Charles River sail-a-thon. “The prototype, named ‘Anita’ after Worden’s late wife, moves silently with no fumes or exhaust and uses LiFePO4 battery cells with a battery management system (it lets you charge the batteries while they’re in use),” writes Solis.

June 27, 2026
MIT Develops Long-Term Memory System That Lets Robots Answer Where You Left Your Keys

Imagine asking a robot, “Where did I leave my keys?” and getting an accurate, real-time answer. MIT researchers have created a new spatial memory framework called DAAAM (Describe Anything, Anywhere, Anytime, at Any Moment) that gives robots the ability to form and recall detailed mental models of large-scale environments. This breakthrough could transform how robots assist humans in factories, homes, and beyond.

DAAAM combines advanced map representations with rich, language-based descriptions of objects a robot encounters as it explores. The system runs fast enough for mobile robots to use in real-time, answering complex queries in plain English with 21% to 53% higher accuracy than existing methods.

“If we want robots to work side-by-side with humans and interact better with humans, they must speak the same language,” says Luca Carlone, associate professor in MIT’s Department of Aeronautics and Astronautics and lead researcher on the project. “The robot must be able to reason about time and space the same way humans do.”

The framework bridges computer vision and robotic mapping. As a robot moves through an environment, DAAAM attaches detailed descriptions to objects—like noting that a red bicycle with a flat tire is in the bike rack outside the Stata Center. It stores this information in a 3D map-based representation arranged spatially, grouping objects into regions for efficient retrieval.

To overcome the speed limitations of existing annotation techniques, DAAAM aggregates nearby objects and uses an optimization method to select key frames—images with the clearest view of multiple objects—allowing the system to describe several items in parallel. This speeds up computation tenfold, making real-time performance possible.

“We annotate every object only once, so our framework can run in very large-scale environments in real time,” explains lead author Nicolas Gorlo, an MIT graduate student. “And by clustering objects into regions, it can answer a wide range of queries about objects and locations.”

The researchers used a large language model (LLM) that calls on various tools to retrieve specific information quickly, reducing hallucinations. For example, if asked about a sculpture near an MIT campus building, DAAAM can use a semantic search tool to retrieve information based on the word “sculpture” or a location-based tool to find the building.

Future work aims to expand DAAAM to capture significant events and incorporate confidence levels into responses. “Ultimately, we want to have robots that can help with any sort of tasks,” Gorlo says. “With this framework, we are trying to create the foundations to enable a generalist agent that can do anything you ask.”

The research was presented at the Conference on Computer Vision and Pattern Recognition (CVPR) and funded by the U.S. Army Research Laboratory and the Office of Naval Research.

June 26, 2026
Ultra-Low-Power Chip Lets Tiny Robots Create Real-Time 3D Maps for Navigation

MIT researchers have unveiled a new chip that could transform how tiny, battery-powered robots navigate complex environments. The chip, named Gleanmer, enables small autonomous vehicles and other power-limited devices to build detailed 3D maps of their surroundings in real time while consuming only about 6 milliwatts of power — roughly the same as a single LED.

Traditional 3D mapping systems require significant memory and energy because they store and process every pixel from depth images. The MIT team took a different approach, combining an efficient algorithm with custom hardware to dramatically reduce both power and memory demands.

How Gleanmer Works

Instead of representing the environment with rigid cube-shaped voxels (3D pixels), the chip uses flexible ellipsoid shapes called Gaussians. These ellipsoids can be smoothly adjusted in size, shape, and thickness to match curved objects more efficiently than voxels. This compact representation captures both obstacles and free space, allowing a robot to plan collision-free paths without storing massive amounts of data.

The researchers leveraged an algorithm developed in their lab called GMMap, which generates Gaussian-based maps from depth images in a single pass. By only comparing each pixel to its immediate neighbors, the algorithm avoids storing entire images at once — significantly reducing memory footprint.

“At any point in time, we only need to store a few pixels in memory, which significantly reduces the memory footprint our algorithm requires,” said co-lead author Peter Zhi Xuan Li, an MIT graduate student.

Co-Design for Maximum Efficiency

As a robot moves, it often sees the same object from multiple angles, creating overlapping Gaussians. The chip fuses these overlapping shapes directly — without revisiting the original pixels — keeping the map compact. This principle extends throughout the design: most computations operate on compact Gaussians rather than raw pixels, enabling major energy savings.

The hardware is built to keep active Gaussians in small, fast on-chip memory right next to the processing units. This eliminates the need to fetch data from distant, power-hungry off-chip storage.

“By having a dedicated memory that just stores the objects you’ve seen in the previous few frames, you can access the data much more efficiently,” explained co-lead author Zih-Sing Fu.

Real-World Testing and Future Applications

The team tested Gleanmer on diverse 3D environments and live data from an iPhone camera. The chip generated accurate maps in real time while using just 2.5% of the power required by the best existing map-construction chip. It also allowed a simulated robot to plan safe trajectories using only about 20% of the energy it would otherwise need.

Beyond robotics, the ultra-low-power operation makes the chip well-suited for lightweight augmented reality headsets that can be worn for extended periods — for applications like medical training simulations or detailed repair work.

“Real-time 3D mapping has been the missing piece for small autonomous systems. A drone inspecting a pipeline or a pair of AR glasses navigating a room both need to understand the space around them — instantly, continuously, and at almost no power cost. Gleanmer makes that possible for the first time in a chip you can hold between your fingers,” said co-author Sertac Karaman, a professor of aeronautics and astronautics.

The work was supported by the MIT-MathWorks Fellowship, Amazon, the U.S. National Science Foundation, and Intel. The paper was presented at the IEEE Very Large-Scale Integrated Circuits Symposium.

June 26, 2026
MIT’s 6-Milliwatt AI Chip Brings Real-Time 3D Mapping to Tiny Robots

Researchers at MIT have unveiled a new system-on-a-chip that could revolutionize how tiny, low-power robots navigate complex environments. The chip, named Gleanmer, enables autonomous drones and other battery-limited devices to construct detailed 3D maps in real time using only about 6 milliwatts of power—roughly the energy of a single LED. This breakthrough, presented at the IEEE Very Large-Scale Integrated Circuits Symposium, promises to make small-scale robotics more capable and energy-efficient than ever.

A Smarter Approach to 3D Mapping

Traditional 3D mapping for robots relies on power-hungry systems that process and store thousands of 3D pixels (voxels) per image. The MIT team took a radically different approach by combining an efficient algorithm called GMMap with custom hardware optimized for its workload. Instead of using rigid cube-shaped voxels, GMMap represents obstacles and free space with flexible ellipsoidal blobs known as Gaussians. These shapes can stretch and shrink to match curved objects, storing far less data than traditional methods while still capturing accurate geometry.

“This paper showcases a key example of how you can leverage co-design of the algorithm and hardware to really push energy efficiency,” says Vivienne Sze, a professor in EECS and senior author of the paper. “Our chip allows you to store very large maps in a very small space, and do it in a very energy efficient manner.”

Hardware-Algorithm Co-Design at Its Best

The chip’s efficiency stems from several clever optimizations. First, the GMMap algorithm processes each depth image in a single pass, comparing only neighboring pixels rather than all pixels in an image. This drastically reduces the amount of data that needs to be stored and retrieved. Second, as the robot moves and observes the same object from different angles, overlapping Gaussians are fused into a single compact representation without re-examining the original pixels. Because Gaussians are more compact than raw pixel data, this fusion process runs on-chip with minimal memory traffic.

The hardware design keeps active Gaussians in small, fast on-chip memory right next to the processing units. “By having a dedicated memory that just stores the objects you’ve seen in the previous few frames, you can access the data much more efficiently,” explains co-lead author Zih-Sing Fu.

Unmatched Energy Efficiency

In tests, Gleanmer generated detailed 3D maps in real time while consuming only about 6 milliwatts of power—just 2.5 percent of what the best existing mapping chip requires. When used for path planning, the chip reuses compact Gaussians along the planned route, using only about 20 percent of the energy that conventional approaches would need.

The low power consumption makes Gleanmer ideal not only for tiny drones inspecting HVAC systems or pipelines, but also for lightweight augmented reality headsets that require continuous environmental mapping for educational medical simulations or repair work. Sertac Karaman, a professor of aeronautics and astronautics and co-author, notes: “Real-time 3D mapping has been the missing piece for small autonomous systems. Gleanmer makes that possible for the first time in a chip you can hold between your fingers.”

Looking Ahead

The researchers plan to push energy efficiency even further by moving processing units closer to the sensors that gather environmental data. They are also exploring applications beyond robotics, such as using Gaussians to represent complex schematics for AI reasoning systems. This work was supported by the MIT-MathWorks Fellowship, Amazon, the U.S. National Science Foundation, and Intel.

June 26, 2026
Two LLMs Team Up to Help Robots Interpret Vague Instructions and Prioritize What Matters

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new method that uses two large language models (LLMs) to help robots understand ambiguous instructions and focus on key details. The approach, called Masked Inverse Reinforcement Learning (Masked IRL), reduces the amount of demonstration data needed to teach a robot by nearly five times, while improving the robot’s ability to infer unspoken user preferences.

Traditional robot training often requires either extensive physical demonstrations or detailed written instructions. Masked IRL automates the process: first, one LLM clarifies ambiguous prompts (e.g., turning “stay close” into “stay close to the surface of the table”) by comparing a user’s demonstration trajectory to the shortest possible path. Then a second LLM evaluates the environment and “masks” irrelevant details – such as a person leaning on a table – while highlighting critical ones like obstacles to avoid. The robot then uses these prioritized details to generate a safe motion plan.

In experiments, the system correctly identified unstated user preferences up to 15 percent more often than comparable baselines. Real-world tests showed a robotic arm successfully moving a coffee mug around a laptop, wiping a table while “staying close” to it, and handing a user a bag of chips while “staying away” from both the person and the table – all after fewer than 50 kinesthetic demonstrations.

The team plans to enhance Masked IRL with camera input, allowing robots to visually focus on relevant objects in dynamic environments. The work was supported by the Tata Group via the MIT Generative AI Impact Consortium Award and the Department of Defense, and will be presented at the 2026 IEEE International Conference on Robotics and Automation.

June 26, 2026
Recent Breakthroughs from MIT Schwarzman College of Computing: AI, Robotics, and Beyond

The MIT Schwarzman College of Computing continues to drive innovation across artificial intelligence, robotics, quantum computing, and more. Here are some of the latest developments from MIT researchers and affiliates.

LLMs Help Robots Understand Vague Instructions

MIT researchers have developed a method using two language models: one to clarify user instructions and another to ignore irrelevant details, enabling robots to perform chores in homes and factories more effectively. (June 26, 2026)

Exploring How Curiosity-Driven Science Fuels American Success

Scientific American highlights the history and future of America’s scientific engine, featuring promising young scientists and icons at MIT and beyond. (June 25, 2026)

Summer 2026 Recommended Reading from MIT

Enjoy these recent titles from Institute faculty and staff. (June 25, 2026)

Improving Speed and Energy-Efficiency of AI Agents

A new system called Murakkab optimizes the design and deployment of multistep workflows that power AI applications. (June 25, 2026)

Exploring the Societal Impacts of AI

During the AI and Society Forum, leading MIT researchers examined critical questions about AI’s influence on employment and democracy. (June 23, 2026)

New Chip Helps Tiny Robots Navigate Complex Environments

Researchers combined an efficient algorithm with dedicated hardware to rapidly generate 3D maps for navigation using minimal memory and power. (June 23, 2026)

QS Ranks MIT World’s No. 1 University for 2026-27

Ranking at the top for the 15th consecutive year, the Institute also places first in 12 subject areas. (June 17, 2026)

In Game Theory, Generalists Sometimes Win Out Over Specialists

Researchers show that for certain kinds of games, an overlooked class of algorithms performs much better than expected. (June 17, 2026)

Could AI Tell You Where You Left Your Keys?

A new spatial memory system for robots efficiently captures details about the objects they see while exploring their environment. (June 17, 2026)

The Tenured Engineers of 2026

Ten faculty members have been granted tenure in five units across MIT’s School of Engineering. (June 15, 2026)

How to Create Distinguishable States for Quantum Systems

Researchers establish key insights for reading and writing information for quantum sensing, communication, computing, and control. (June 15, 2026)

When It Comes to Predicting People’s Preferences, It Pays to Consider “The Power of Three”

MIT researchers provide a major upgrade to the nearly century-old idea of random utility models. (June 11, 2026)

MIT Affiliates Win 2026 Hertz Foundation Fellowships

The fellowships in applied sciences, engineering, and mathematics recognize doctoral students pursuing solutions to pressing challenges. (June 11, 2026)

To Study How Chips Really Work, MIT Researchers Built Their Own Operating System

A new kernel called Fractal gives researchers a cleaner view of what’s happening inside a processor, and has already surfaced previously unknown behavior in Apple’s M1. (June 10, 2026)

3D-Printed Devices Could Streamline Production of Drug-Delivery Microparticles

The cost-effective devices, built in hours, leverage electrospray emitter technology to efficiently produce three-layered particles at scale. (June 9, 2026)

June 26, 2026
MIT School of Engineering: Latest Research and Innovations (June 2026)

The MIT School of Engineering continues to drive breakthroughs across multiple disciplines. Recent highlights include a hands-on photonics boot camp at MIT.nano for community college students, new AI systems that help robots interpret vague instructions, and a chip design that enables tiny robots to navigate complex environments with minimal power. Researchers have also developed a computer model for more material-efficient bridges and buildings, and a new approach to modeling metal alloys at the atomic level. In game theory, generalists have been shown to outperform specialists in certain scenarios. The Institute was ranked the world’s No. 1 university by QS for the 15th consecutive year, and MIT’s Initiative for New Manufacturing is gaining momentum. Ten engineering faculty members were granted tenure in 2026. These stories reflect the breadth and impact of engineering research at MIT.

June 26, 2026
Trump’s Beijing Visit Opens Door for Nvidia Chips to Power Chinese AI Giants

President Donald Trump’s recent trip to Beijing, accompanied by a delegation including Apple’s Tim Cook, Tesla’s Elon Musk, and Nvidia’s Jensen Huang, signals a potential reset in AI supply chains between the U.S. and China. The visit, focused on high-level negotiations, suggests a shift toward a transactional relationship where American semiconductor technology may support Chinese AI development.

At the state banquet, President Xi Jinping emphasized the possibility of common cause between China’s rejuvenation goals and America’s “Make America Great Again” agenda. Behind the diplomatic smiles, however, lies a strategic contest: Beijing’s “new productive forces” policy prioritizes AI, advanced manufacturing, and robotics, exemplified by the transformation of Chongqing into a high-tech megacity. Yet China remains dependent on U.S.-controlled high-end accelerators for training frontier AI models.

Nvidia’s Jensen Huang’s presence is particularly significant. After years of tightening export controls, Washington is now considering case-by-case reviews for advanced AI compute exports. Nvidia is positioned to ship H200 data center GPUs to major Chinese cloud platforms like Alibaba and Tencent. Although not the top-tier Blackwell-class chips, the H200 is roughly six times more powerful than any domestic Chinese alternative, potentially compressing AI training timelines for Chinese firms.

For Apple and Tesla, the mission focuses on supply chain stability and regulatory clarity. Apple aims to protect its manufacturing resilience and consumer base, where the iPhone 17 has seen success. Tesla views China as crucial for production and full self-driving deployment, seeking clarity on mapping and data policies to compete with domestic rivals.

This delegation represents an attempt to reverse the 20% decline in U.S. imports from China. By leveraging tech leaders for targeted access—compute in exchange for market openness and IP protections—both nations may enter a more transactional era. The true metrics of success will be the speed of Chinese hyperscalers building H200 clusters and the regulatory wins secured by Apple and Tesla. Ultimately, compute access shapes capability, and this visit suggests a hard-nosed accommodation that keeps the AI flywheel spinning on both sides of the Pacific.

June 26, 2026
MIT Media Lab: Cutting-Edge Research at the Intersection of Technology, Innovation, and Society

The MIT Media Lab stands as one of the world’s premier research institutions, where technology, media, science, and art converge to drive innovation. With a diverse portfolio spanning from augmented reality in healthcare to the ethics of AI, the Lab continuously pushes boundaries to solve real-world challenges.

Augmented Reality System Could Make Medical Ultrasounds Easier to Interpret

MIT researchers have designed an ultrasound system that creates a real-time 3D representation of the object being imaged, offering clearer visualization for medical professionals. This breakthrough could transform diagnostic procedures and improve patient outcomes.

The Consequences of Relying on AI for Accurate News

A Media Lab study reveals that, much like how GPS has weakened our navigation skills, AI can make us worse at detecting fake news. The research underscores the critical need for human oversight in information consumption.

The Crucial Human Component in Computing and AI

The MIT Ethics of Computing Research Symposium brought together experts and researchers working at the heart of ethical and social impact in technology. Discussions emphasized the importance of embedding human values into technological development.

Startup Helps Retailers Track Their Products in Real-Time

Using technology invented at MIT, Cartesian’s system for locating objects could also find uses in manufacturing, logistics, and robotics. This innovation enables real-time inventory management and operational efficiency.

PATH to Boost AI Training and Career Opportunities for Industry-Aligned Jobs

MIT RAISE and Georgia State University announce an initiative to connect universities, community colleges, industry, and government to expand industry-aligned AI training and career pathways, addressing the growing demand for skilled AI professionals.

Tod Machover Receives George Peabody Medal for Contributions to Music and Technology

The George Peabody Medal is the highest honor bestowed by the Peabody Institute of the Johns Hopkins University, recognizing Machover’s pioneering work at the intersection of music and technology.

Alejandro Aravena Urges School of Architecture and Planning Graduates to Lead with Kindness, Honor the Truth

“All of us need to feel we are valuable,” says the SA+P Commencement speaker, a Chilean architect and Pritzker Prize winner. His address inspired graduates to prioritize humanity in their professional endeavors.

Eleven from MIT Accept 2026 Fulbright Awards

This year, over half of MIT’s Fulbright applicants won awards. The current students and alumni will embark on research projects and teaching abroad in 2026-27, fostering global collaboration.

Bridging Real Human Movement with Digital Technology

MIT.nano Immersion Lab collaborates with Emerson College students to advance the art of virtual production, combining human motion capture with digital environments for creative applications.

Mapping the Ocean with Autonomous Sensors

Founded by Ravi Pappu SM ’95, PhD ’01, Apeiron Labs is deploying low-cost ocean sensors to improve storm forecasts, detect endangered species, and more, demonstrating how technology can aid environmental monitoring.

Celebrating Dorm-to-Market Social Entrepreneurship at MIT

At the 25th IDEAS Social Innovation Incubator Showcase and Awards, 21 student-led ventures joined 1,200 alumni-led ventures tackling the world’s most pressing problems through social entrepreneurship, highlighting MIT’s commitment to impact-driven innovation.

A New Type of Electrically Driven Artificial Muscle Fiber

Electrofluidic fibers mimic how natural muscle fibers bundle, and could enable compact, silent robotic and prosthetic systems, opening new possibilities in assistive technology.

Turning Muscles into Motors Gives Static Organs New Life

A new biohybrid system developed at MIT is the first living implant that uses rewired nerves to revive paralyzed organs, offering hope for patients with organ failure.

Lasers, Robots, Action: MIT Workshop Explores Raman Spectroscopy

Participants learn how laser “fingerprinting” can help identify materials in fields ranging from law enforcement to art restoration, showcasing the versatility of spectroscopic techniques.

Generative AI Improves a Wireless Vision System That Sees Through Obstructions

With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals, advancing capabilities in autonomous navigation and security.

June 26, 2026
MIT AeroAstro Department: Pioneering Research in AI, Robotics, and Spaceflight

MIT’s Department of Aeronautics and Astronautics (AeroAstro) continues to lead in aerospace engineering and technology. Below are recent highlights from the department, showcasing breakthroughs in robotics, artificial intelligence, quantum systems, and space traffic management.

LLMs Help Robots Understand Vague Instructions

Researchers used large language models to help robots interpret ambiguous commands and ignore irrelevant details, improving task performance in dynamic environments like homes and factories. (June 26, 2026)

Exploring the Societal Impacts of AI

The AI and Society Forum at MIT brought together leading researchers to discuss critical questions about AI’s influence on employment and democracy. (June 23, 2026)

New Chip Enables Tiny Robots to Traverse Complex Environments

A novel chip combining an efficient algorithm with dedicated hardware allows small robots to rapidly generate 3D navigation maps using minimal memory and power. (June 23, 2026)

QS Ranks MIT World’s No. 1 University for 2026-27

MIT secured the top spot for the 15th consecutive year, also ranking first in 12 subject areas. (June 17, 2026)

The Tenured Engineers of 2026

Ten faculty members received tenure across MIT’s School of Engineering, reflecting excellence in research and teaching. (June 15, 2026)

Creating Distinguishable Quantum States

Researchers established key insights for reading and writing information in quantum systems, advancing quantum sensing, communication, and computing. (June 15, 2026)

New Imaging System Sees Through Murky Waters

The ‘Sonar-MASt3R’ system combines sonar and visual data to generate real-time 3D maps even in cloudy water, aiding underwater exploration. (June 11, 2026)

The Crucial Human Component in Computing and AI

The MIT Ethics of Computing Research Symposium highlighted work at the intersection of ethical and social impact in technology. (June 5, 2026)

MIGHTY: Open-Source Robot Path Planning

A new open-source system rapidly produces smooth path plans that cut travel time and avoid obstacles, useful for disaster recovery and delivery. (May 19, 2026)

Managing Traffic in Space

Associate Professor Richard Linares develops techniques to help satellites navigate safely in increasingly congested orbits. (April 19, 2026)

Flying at the Edge of the Stratosphere

MIT students experience the Earth’s curvature through a reborn AeroAstro introductory course, combining hands-on flight with education. (April 14, 2026)

These stories represent the breadth of innovation at MIT AeroAstro, from fundamental research to real-world applications. For more details, visit the official MIT News site.

June 26, 2026