Nature Climate Change, Published online: 09 May 2025; doi:10.1038/s41558-025-02347-5

Many voices are needed in the climate change discussion to reach across society. Pope Francis is one example who offered his voice and support, in the conversation that needs to continue.

The MIT Supply Chain Management (MCM) master’s program has recognized 34 exceptional students from nine renowned undergraduate programs specializing in supply chain management and engineering across the United States. Twenty-one students have won the 2025 MIT Supply Chain Excellence Award, while an additional 13 were named honorable mentions.

Presented annually, the MIT Supply Chain Excellence Awards honor undergraduate students who have demonstrated outstanding talent in supply chain management or industrial engineering. These students originate from the institutions that have collaborated with the MIT Center for Transportation and Logistics’ Supply Chain Management master’s program since 2013 to expand opportunities for graduate study and advance the field of supply chain and logistics.

In this year’s awards, the MIT SCM master’s program has provided over $800,000 in fellowship funding to the recipients. These students come from schools like Arizona State University, University of Illinois Urbana-Champaign, Lehigh University, Michigan State University, Monterrey Institute of Technology and Higher Education (Mexico), Penn State University, Purdue University, the University of Massachusetts at Amherst, and Syracuse University.

Recipients can use their awards by applying to the SCM program after gaining two to five years of professional experience post-graduation. Fellowship funds can be applied toward tuition fees for the SCM master’s program at MIT, or at MIT Supply Chain and Logistics Excellence (SCALE) network centers.

Winners ($30,000 fellowship awards):

• Grace Albano, Lehigh University
• Addison Clauss, Purdue University
• Avery Geiger, University of Illinois Urbana-Champaign
• Patrick Estefan, Michigan State University
• Addison Kiteley, Michigan State University
• Sarah Seo, Michigan State University
• Dakarai Young, Michigan State University
• Denver Zhang, Michigan State University
• Mickey Miller, University of Massachusetts Amherst
• Ana Paula Martínez Caldera, Monterrey Tech
• Valeria Quinto Lange, Monterrey Tech
• Alejandro Garza, Monterrey Tech
• Mariana Otero Becerril, Monterrey Tech
• Drew Gibble, Penn State University
• Gabe Marshall, Penn State University
• Eric Chen, Arizona State University
• Dachi Tabatadze, Arizona State University
• Srishti Garg, Arizona State University
• Amanda Gong, Arizona State University
• Austin Hurley, Arizona State University
• Emily Wong, Arizona State University

Honorable Mentions ($15,000 fellowship awards):

• Alisa Chen, Arizona State University
• Sean Ratigan, Arizona State University
• Natalie Alexander, Arizona State University
• Chris Lewis, Arizona State University
• Aiden Lyons, Arizona State University
• Mia Thorn, Syracuse University
• Devangi Deoras, Michigan State University
• Api Sen, Michigan State University
• Ashley Sheko, Michigan State University
• Mila Straskraba, Michigan State University
• Abeeha Zaidi, Michigan State University
• Valeria Gonzalez Garcia Monterrey Tech
• Ceci Herrera Guerrero, Monterrey Tech

The MIT Center for Transportation and Logistics (CTL) is a world leader in supply chain management research and education, with over 50 years of expertise. The center’s work spans industry partnerships, cutting-edge research, and the advancement of sustainable supply chain practices to creates supply chain innovation and drive it into practice through three pillars: research, outreach, and education. 

Founded in 1998 by the CTL, MIT SCM attracts a diverse group of talented and motivated students from across the globe. Students work directly with researchers and industry experts on complex and challenging problems in all aspects of supply chain management. MIT SCM students propel their classroom and laboratory learning straight into industry. They graduate from our programs as thought leaders ready to engage in an international, highly competitive marketplace. For more information, contact Kate Padilla.

The newly established Morningside Academy of Design (MAD) Professorships recognize outstanding faculty whose teaching, research, and service have significantly shaped the field of design at MIT and beyond. The appointments support a commitment to interdisciplinary collaboration, mentorship, and the development of new educational approaches to design. 

These appointments mark the creation of the MAD Professorships and were formally announced on April 29 at the MAD in Dialogue event, where faculty members, introduced by their department heads, each gave a short presentation on their work, followed by a shared conversation on the future of design education. 

The inaugural chair-holders are Behnaz Farahi, assistant professor of media arts and sciences and director of the Critical Matter Group in the MIT Media Lab; Skylar Tibbits, associate professor of architecture, co-founder and director of the MIT Self-Assembly Lab, and assistant director for education at MAD; and David Wallace, professor of mechanical engineering, MacVicar Fellow, and Class of 1960 Innovation in Education Fellow. 

John Ochsendorf, MAD’s founding director, reflects that “the professorships are more than titles — they’re affirming the central role of design in empowering students to solve complex challenges. Behnaz, Skylar, and David are all celebrated designers who each bring a unique perspective to design education and research. By supporting them, we will cultivate more agile, creative thinkers across MIT.”

Professor Farahi’s MAD professorship appointment will begin Sept. 1, upon the completion of her Asahi Broadcast Corp. professorship. Tibbits’ and Wallace’s appointments are effective immediately. The faculty members will remain affiliated with their respective departments. 

Behnaz Farahi

Having joined the MIT faculty in fall 2024 as an assistant professor in media arts and sciences, Behnaz Farahi brings her critical lens to design research and education. With a foundation in architecture, her career spans fashion and creative technology. Farahi takes interest in addressing critical social issues with a design practice engaging emerging technologies, human bodies, and the environment. As director of the Critical Matter research group at the MIT Media Lab, Farahi aims to re-integrate the tradition of critical thinking in philosophy and social sciences with the concerns of “matter” in science and technology. 

She has won awards including the Cooper Hewitt Smithsonian Design Museum Digital Design Award, Innovation by Design Fast Company Award, and the World Technology Award. Her work has been included in the permanent collection of the Museum of Science and Industry in Chicago and has been exhibited internationally.

Her most recent installation, “Gaze to the Stars,” projected video closeups of MIT community members’ eyes onto the Great Dome, with encoded personal stories of perseverance and transformation. The project integrated large language model and computer vision tools in service of a collective art experience.

Currently the recipient of the Asahi Broadcasting Corporation Career Development Professorship in Media Arts and Sciences, Farahi’s MAD appointment will begin after the completion of her present chair. She will remain affiliated with the MIT Media Lab. 

Skylar Tibbits

An architect by training, Skylar Tibbits combines design and computer science as co-founder and director of the Self-Assembly Lab at MIT and associate professor of design research in the Department of Architecture. Dedicated to broadening the reach of design education, he directs the undergraduate design programs at MIT and contributes to its curricula.

At the Self-Assembly Lab, Tibbits oversees the advancement of self-assembly and programmable material technologies such as 4D knitting and liquid metal printing, with a plurality of applications ranging from garments and housing to coastal resilience.

He has designed and built large-scale installations and exhibited in galleries around the world, including the Museum of Modern Art, Centre Pompidou, Philadelphia Museum of Art, Cooper Hewitt Smithsonian Design Museum, Victoria and Albert Museum, and various others. 

David Robert Wallace

David Wallace has long been a recognized leader in design research and education at MIT and around the world. Wallace began his research career focused on computational tools for design representation and has evolved his interests over time to environmentally-conscious design approaches, developing software tools to enhance design and creativity, and incorporating new media and tools into the design classroom to empower engineers and designers. His research goals are to develop new methods that impact upon the practice of product development and to help inspire and equip the next generation of engineering innovators.

Wallace is known both inside and outside of MIT for his development of two iconic design classes at MIT, 2.009 (Product Engineering Processes), and 2.00B (Toy Product Design). In sculpting and refining 2.009 over many years, Wallace merged a studio-based approach with rigorous engineering to create a new paradigm for team-based, project-based design. In these courses, students experience hands-on building and testing in real-world contexts so they experience what it means to design for real users, not just design in theory. 

His approach to design education is captured in the video series “Play Seriously!,” which follows one semester of 2.009. For his tremendous educational contributions, he has been awarded the Baker Award for Teaching Excellence and was named a MacVicar Faculty Fellow, which is MIT’s highest teaching award.

Researchers from MIT and Dana-Farber Cancer Institute have discovered that a class of peptides expressed in pancreatic cancer cells could be a promising target for T-cell therapies and other approaches that attack pancreatic tumors.

Known as cryptic peptides, these molecules are produced from sequences in the genome that were not thought to encode proteins. Such peptides can also be found in some healthy cells, but in this study, the researchers identified about 500 that appear to be found only in pancreatic tumors.

The researchers also showed they could generate T cells targeting those peptides. Those T cells were able to attack pancreatic tumor organoids derived from patient cells, and they significantly slowed down tumor growth in a study of mice.

“Pancreas cancer is one of the most challenging cancers to treat. This study identifies an unexpected vulnerability in pancreas cancer cells that we may be able to exploit therapeutically,” says Tyler Jacks, the David H. Koch Professor of Biology at MIT and a member of the Koch Institute for Integrative Cancer Research.

Jacks and William Freed-Pastor, a physician-scientist in the Hale Family Center for Pancreatic Cancer Research at Dana-Farber Cancer Institute and an assistant professor at Harvard Medical School, are the senior authors of the study, which appears today in Science. Zackery Ely PhD ’22 and Zachary Kulstad, a former research technician at Dana-Farber Cancer Institute and the Koch Institute, are the lead authors of the paper.

Cryptic peptides

Pancreatic cancer has one of the lowest survival rates of any cancer — about 10 percent of patients survive for five years after their diagnosis.

Most pancreatic cancer patients receive a combination of surgery, radiation treatment, and chemotherapy. Immunotherapy treatments such as checkpoint blockade inhibitors, which are designed to help stimulate the body’s own T cells to attack tumor cells, are usually not effective against pancreatic tumors. However, therapies that deploy T cells engineered to attack tumors have shown promise in clinical trials.

These therapies involve programming the T-cell receptor (TCR) of T cells to recognize a specific peptide, or antigen, found on tumor cells. There are many efforts underway to identify the most effective targets, and researchers have found some promising antigens that consist of mutated proteins that often show up when pancreatic cancer genomes are sequenced.

In the new study, the MIT and Dana-Farber team wanted to extend that search into tissue samples from patients with pancreatic cancer, using immunopeptidomics — a strategy that involves extracting the peptides presented on a cell surface and then identifying the peptides using mass spectrometry.

Using tumor samples from about a dozen patients, the researchers created organoids — three-dimensional growths that partially replicate the structure of the pancreas. The immunopeptidomics analysis, which was led by Jennifer Abelin and Steven Carr at the Broad Institute, found that the majority of novel antigens found in the tumor organoids were cryptic antigens. Cryptic peptides have been seen in other types of tumors, but this is the first time they have been found in pancreatic tumors.

Each tumor expressed an average of about 250 cryptic peptides, and in total, the researchers identified about 1,700 cryptic peptides.

“Once we started getting the data back, it just became clear that this was by far the most abundant novel class of antigens, and so that’s what we wound up focusing on,” Ely says.

The researchers then performed an analysis of healthy tissues to see if any of these cryptic peptides were found in normal cells. They found that about two-thirds of them were also found in at least one type of healthy tissue, leaving about 500 that appeared to be restricted to pancreatic cancer cells.

“Those are the ones that we think could be very good targets for future immunotherapies,” Freed-Pastor says.

Programmed T cells

To test whether these antigens might hold potential as targets for T-cell-based treatments, the researchers exposed about 30 of the cancer-specific antigens to immature T cells and found that 12 of them could generate large populations of T cells targeting those antigens.

The researchers then engineered a new population of T cells to express those T-cell receptors. These engineered T cells were able to destroy organoids grown from patient-derived pancreatic tumor cells. Additionally, when the researchers implanted the organoids into mice and then treated them with the engineered T cells, tumor growth was significantly slowed.

This is the first time that anyone has demonstrated the use of T cells targeting cryptic peptides to kill pancreatic tumor cells. Even though the tumors were not completely eradicated, the results are promising, and it is possible that the T-cells’ killing power could be strengthened in future work, the researchers say.

Freed-Pastor’s lab is also beginning to work on a vaccine targeting some of the cryptic antigens, which could help stimulate patients’ T cells to attack tumors expressing those antigens. Such a vaccine could include a collection of the antigens identified in this study, including those frequently found in multiple patients.

This study could also help researchers in designing other types of therapy, such as T cell engagers — antibodies that bind an antigen on one side and T cells on the other, which allows them to redirect any T cell to kill tumor cells.

Any potential vaccine or T cell therapy is likely a few years away from being tested in patients, the researchers say.

The research was funded in part by the Hale Family Center for Pancreatic Cancer Research, the Lustgarten Foundation, Stand Up To Cancer, the Pancreatic Cancer Action Network, the Burroughs Wellcome Fund, a Conquer Cancer Young Investigator Award, the National Institutes of Health, and the National Cancer Institute.

Cameron Hamilton, the acting disaster chief, appeared to contradict Homeland Security Secretary Kristi Noem by defending the agency on Wednesday.

It’s been a scientific truth so universally acknowledged that it’s taught in classrooms and repeated in pop-science videos: An egg is strongest when dropped vertically, on its ends. But when MIT engineers actually put this assumption to the test, they cracked open a surprising revelation. 

Their experiments revealed that eggs dropped on their sides — not their tips — are far more resilient, thanks to a clever physics trick: Sideways eggs bend like shock absorbers, trading stiffness for superior energy absorption. Their open-access findings, published today in Communications Physics, don’t just rewrite the rules of the classic egg drop challenge — they’re a lesson in intellectual humility and curiosity. Even “settled” science can yield surprises when approached with rigor and an open mind.

At first glance, an eggshell may seem fragile, but its strength is a marvel of physics. Crack an egg on its side for your morning omelet and it breaks easily. Intuitively, we believe eggs are harder to break when positioned vertically. This notion has long been a cornerstone of the classic “egg drop challenge,” a popular science activity in STEM classrooms across the country that introduces students to physics concepts of impact, force, kinetic energy, and engineering design.

The annual egg drop competition is a highlight of first-year orientation in the MIT Department of Civil and Environmental Engineering. “Every year we follow the scientific literature and talk to the students about how to position the egg to avoid breakage on impact,” says Tal Cohen, associate professor of civil and environmental engineering and mechanical engineering. “But about three years ago, we started to question whether vertical really is stronger.” 

That curiosity sparked an initial experiment by Cohen’s research group, which leads the department’s egg drop event. They decided to put their remaining box of eggs to the test in the lab. “We expected to confirm the vertical side was tougher based on what we had read online,” says Cohen. “But when we looked at the data — it was really unclear.”

What began as casual inquiry evolved into a research project. To rigorously investigate the strength of both egg orientations, the researchers conducted two types of experiments: static compression tests, which applied gradually increasing force to measure stiffness and toughness; and dynamic drop tests, to quantify the likelihood of breaking on impact.

“In the static testing, we wanted to keep an egg at a standstill and push on it until it cracked,” explains Avishai Jeselsohn, an undergraduate researcher and an author in the study. “We used thin paper supports to precisely orient the eggs vertically and horizontally.”

What the researchers found was it required the same amount of force to initiate a crack in both orientations. “However, we noticed a key difference in how much the egg compressed before it broke, says Joseph Bonavia, PhD candidate who contributed to the work. “The horizontal egg compressed more under the same amount of force, meaning it was more compliant.”

Using mechanical modeling and numerical simulations to validate results of their experiments, the researchers concluded that even though the force to crack the egg was consistent, the horizontal eggs absorbed more energy due to their compliance. “This suggested that in situations where energy absorption is important, like in a drop, the horizontal orientation might be more resilient. We then performed the dynamic drop tests to see if this held true in practice,” says Jeselsohn.

The researchers designed a drop setup using solenoids and 3D-printed supports, ensuring simultaneous release and consistent egg orientation. Eggs were dropped from various heights to observe breakage patterns. The result: Horizontal eggs cracked less frequently when dropped from the same height.

“This confirmed what we saw in the static tests,” says Jeselsohn. “Even though both orientations experienced similar peak forces, the horizontal eggs absorbed energy better and were more resistant to breaking.”

Challenging common notions

The study reveals a misconception in popular science regarding the strength of an egg when subjected to impact. Even seasoned researchers in fracture mechanics initially assumed that vertical oriented eggs would be stronger. “It’s a widespread, accepted belief, referenced in many online sources,” notes Jeselsohn.

Everyday experience may reinforce that misconception. After all, we often crack eggs on their sides when cooking. “But that’s not the same as resisting impact,” explains Brendan Unikewicz, a PhD candidate and author on the paper. “Cracking an egg for cooking involves applying locally focused force for a clean break to retrieve the yolk, while its resistance to breaking from a drop involves distributing and absorbing energy across the shell.”

The difference is subtle but significant. A vertically oriented egg, while stiffer, is more brittle under sudden force. A horizontal egg, being more compliant, bends and absorbs energy over a greater distance — similar to how bending your knees during a fall softens the blow.

“In a way, our legs are ‘weaker’ when bent, but they’re actually tougher in absorbing impact,” Bonavia adds. “It’s the same with the egg. Toughness isn’t just about resisting force — it’s about how that force is dissipated.”

The research findings offer more than insight into egg behavior — they underscore a broader scientific principle: that widely accepted “truths” are worth re-examining.

Which came first?

“It’s great to see an example of ‘received wisdom’ being tested scientifically and shown to be incorrect. There are many such examples in the scientific literature, and it’s a real problem in some fields because it can be difficult to secure funding to challenge an existing, ‘well-known’ theory,” says David Taylor, emeritus professor in the Department of Mechanical, Manufacturing and Biomedical Engineering at Trinity College Dublin, who was not affiliated with the study.

The authors hope their findings encourage young people to remain curious and recognize just how much remains to be discovered in the physical world.

“Our paper is a reminder of the value in challenging common notions and relying on empirical evidence, rather than intuition,” says Cohen. “We hope our work inspires students to stay curious, question even the most familiar assumptions, and continue thinking critically about the physical world around them. That’s what we strive to do in our group — constantly challenge what we’re taught through thoughtful inquiry.”

In addition to Cohen, who serves as senior author on the paper, co-authors include lead authors Antony Sutanto MEng ’24 and Suhib Abu-Qbeitah, a postdoc at Tel Aviv University, as well as the following MIT affiliates: Avishai Jeselsohn, an undergraduate in mechanical engineering; Brendan Unikewicz, a PhD candidate in mechanical engineering; Joseph Bonavia, a PhD candidate in mechanical engineering; Stephen Rudolph, a lab instructor in civil and environmental engineering; Hudson Borja da Rocha, an MIT postdoc in civil and environmental engineering; and Kiana Naghibzadeh, Engineering Excellence Postdoctoral Fellow in civil and environmental engineering. The research was funded by U.S. Office of Naval Research with support from the U.S. National Science Foundation. 

Republicans and Democrats are trying to give Congress a voice in the future of the disaster agency.

The president’s budget threatens a $3.5 billion direct air capture initiative that has benefited Republican-led states.

The Danish wind giant Ørsted said its project near Rhode Island was 75 percent complete.

A bill to create a wildfire reinsurance program failed in committee, even though it had the support of Gov. Jared Polis (D).

The layoffs amount to a roughly 10 percent reduction of Amtrak managers.

Extending the state cap-and-trade program would be “particularly burdensome for lower-income households,” the Legislative Analyst’s Office said.

The state's spending plan includes a slight boost to a key environmental fund, plus $1 billion for climate programs.

“Extreme weather events and abrupt changes in transition policies can significantly affect our economies and financial sectors in the short run,” they warn.

The step is part of a drive by African countries, including Kenya and Zambia, to regulate the industry and gain greater control over it.

The country's environment regulator says that with reservoirs at 84 percent full, there's a summer shortage risk.

This past April was 1.51 degrees Celsius hotter than the preindustrial average, continuing a now nearly 2-year-old trend.

MIT engineers are getting in on the robotic ping pong game with a powerful, lightweight design that returns shots with high-speed precision.

The new table tennis bot comprises a multijointed robotic arm that is fixed to one end of a ping pong table and wields a standard ping pong paddle. Aided by several high-speed cameras and a high-bandwidth predictive control system, the robot quickly estimates the speed and trajectory of an incoming ball and executes one of several swing types — loop, drive, or chop — to precisely hit the ball to a desired location on the table with various types of spin.

In tests, the engineers threw 150 balls at the robot, one after the other, from across the ping pong table. The bot successfully returned the balls with a hit rate of about 88 percent across all three swing types. The robot’s strike speed approaches the top return speeds of human players and is faster than that of other robotic table tennis designs.

Now, the team is looking to increase the robot’s playing radius so that it can return a wider variety of shots. Then, they envision the setup could be a viable competitor in the growing field of smart robotic training systems.

Beyond the game, the team says the table tennis tech could be adapted to improve the speed and responsiveness of humanoid robots, particularly for search-and-rescue scenarios, and situations in a which a robot would need to quickly react or anticipate.

“The problems that we’re solving, specifically related to intercepting objects really quickly and precisely, could potentially be useful in scenarios where a robot has to carry out dynamic maneuvers and plan where its end effector will meet an object, in real-time,” says MIT graduate student David Nguyen.

Nguyen is a co-author of the new study, along with MIT graduate student Kendrick Cancio and Sangbae Kim, associate professor of mechanical engineering and head of the MIT Biomimetics Robotics Lab. The researchers will present the results of those experiments in a paper at the IEEE International Conference on Robotics and Automation (ICRA) this month.

Precise play

Building robots to play ping pong is a challenge that researchers have taken up since the 1980s. The problem requires a unique combination of technologies, including high-speed machine vision, fast and nimble motors and actuators, precise manipulator control, and accurate, real-time prediction, as well as higher-level planning of game strategy.

“If you think of the spectrum of control problems in robotics, we have on one end manipulation, which is usually slow and very precise, such as picking up an object and making sure you’re grasping it well. On the other end, you have locomotion, which is about being dynamic and adapting to perturbations in your system,” Nguyen explains. “Ping pong sits in between those. You’re still doing manipulation, in that you have to be precise in hitting the ball, but you have to hit it within 300 milliseconds. So, it balances similar problems of dynamic locomotion and precise manipulation.”

Ping pong robots have come a long way since the 1980s, most recently with designs by Omron and Google DeepMind that employ artificial intelligence techniques to “learn” from previous ping pong data, to improve a robot’s performance against an increasing variety of strokes and shots. These designs have been shown to be fast and precise enough to rally with intermediate human players.

“These are really specialized robots designed to play ping pong,” Cancio says. “With our robot, we are exploring how the techniques used in playing ping pong could translate to a more generalized system, like a humanoid or anthropomorphic robot that can do many different, useful things.”

Game control

For their new design, the researchers modified a lightweight, high-power robotic arm that Kim’s lab developed as part of the MIT Humanoid — a bipedal, two-armed robot that is about the size of a small child. The group is using the robot to test various dynamic maneuvers, including navigating uneven and varying terrain as well as jumping, running, and doing backflips, with the aim of one day deploying such robots for search-and-rescue operations.

Each of the humanoid’s arms has four joints, or degrees of freedom, which are each controlled by an electrical motor. Cancio, Nguyen, and Kim built a similar robotic arm, which they adapted for ping pong by adding an additional degree of freedom in the wrist to allow for control of a paddle.

The team fixed the robotic arm to a table at one end of a standard ping pong table and set up high-speed motion capture cameras around the table to track balls that are bounced at the robot. They also developed optimal control algorithms that predict, based on the principles of math and physics, what speed and paddle orientation the arm should execute to hit an incoming ball with a particular type of swing: loop (or topspin), drive (straight-on), or chop (backspin).

They implemented the algorithms using three computers that simultaneously processed camera images, estimated a ball’s real-time state, and translated these estimations to commands for the robot’s motors to quickly react and take a swing.

After consecutively bouncing 150 balls at the arm, they found the robot’s hit rate, or accuracy of returning the ball, was about the same for all three types of swings: 88.4 percent for loop strikes, 89.2 percent for chops, and 87.5 percent for drives. They have since tuned the robot’s reaction time and found the arm hits balls faster than existing systems, at velocities of 20 meters per second.

In their paper, the team reports that the robot’s strike speed, or the speed at which the paddle hits the ball, is on average 11 meters per second. Advanced human players have been known to return balls at speeds of between 21 to 25 meters second. Since writing up the results of their initial experiments, the researchers have further tweaked the system, and have recorded strike speeds of up to 19 meters per second (about 42 miles per hour).

“Some of the goal of this project is to say we can reach the same level of athleticism that people have,” Nguyen says. “And in terms of strike speed, we’re getting really, really close.”

Their follow-up work has also enabled the robot to aim. The team incorporated control algorithms into the system that predict not only how but where to hit an incoming ball. With its latest iteration, the researchers can set a target location on the table, and the robot will hit a ball to that same location.

Because it is fixed to the table, the robot has limited mobility and reach, and can mostly return balls that arrive within a crescent-shaped area around the midline of the table. In the future, the engineers plan to rig the bot on a gantry or wheeled platform, enabling it to cover more of the table and return a wider variety of shots.

“A big thing about table tennis is predicting the spin and trajectory of the ball, given how your opponent hit it, which is information that an automatic ball launcher won’t give you,” Cancio says. “A robot like this could mimic the maneuvers that an opponent would do in a game environment, in a way that helps humans play and improve.”

This research is supported, in part, by the Robotics and AI Institute.

A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what’s inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar.

They developed a technique that enables robots to use only internal sensors to learn about an object’s weight, softness, or contents by picking it up and gently shaking it. With their method, which does not require external measurement tools or cameras, the robot can accurately guess parameters like an object’s mass in a matter of seconds.

This low-cost technique could be especially useful in applications where cameras might be less effective, such as sorting objects in a dark basement or clearing rubble inside a building that partially collapsed after an earthquake.

Key to their approach is a simulation process that incorporates models of the robot and the object to rapidly identify characteristics of that object as the robot interacts with it. 

The researchers’ technique is as good at guessing an object’s mass as some more complex and expensive methods that incorporate computer vision. In addition, their data-efficient approach is robust enough to handle many types of unseen scenarios.

“This idea is general, and I believe we are just scratching the surface of what a robot can learn in this way. My dream would be to have robots go out into the world, touch things and move things in their environments, and figure out the properties of everything they interact with on their own,” says Peter Yichen Chen, an MIT postdoc and lead author of a paper on this technique.

His coauthors include fellow MIT postdoc Chao Liu; Pingchuan Ma PhD ’25; Jack Eastman MEng ’24; Dylan Randle and Yuri Ivanov of Amazon Robotics; MIT professors of electrical engineering and computer science Daniela Rus, who leads MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL); and Wojciech Matusik, who leads the Computational Design and Fabrication Group within CSAIL. The research will be presented at the International Conference on Robotics and Automation.

Sensing signals

The researchers’ method leverages proprioception, which is a human or robot’s ability to sense its movement or position in space.

For instance, a human who lifts a dumbbell at the gym can sense the weight of that dumbbell in their wrist and bicep, even though they are holding the dumbbell in their hand. In the same way, a robot can “feel” the heaviness of an object through the multiple joints in its arm.

“A human doesn’t have super-accurate measurements of the joint angles in our fingers or the precise amount of torque we are applying to an object, but a robot does. We take advantage of these abilities,” Liu says.

As the robot lifts an object, the researchers’ system gathers signals from the robot’s joint encoders, which are sensors that detect the rotational position and speed of its joints during movement. 

Most robots have joint encoders within the motors that drive their moveable parts, Liu adds. This makes their technique more cost-effective than some approaches because it doesn’t need extra components like tactile sensors or vision-tracking systems.

To estimate an object’s properties during robot-object interactions, their system relies on two models: one that simulates the robot and its motion and one that simulates the dynamics of the object.

“Having an accurate digital twin of the real-world is really important for the success of our method,” Chen adds.

Their algorithm “watches” the robot and object move during a physical interaction and uses joint encoder data to work backward and identify the properties of the object.

For instance, a heavier object will move slower than a light one if the robot applies the same amount of force.

Differentiable simulations

They utilize a technique called differentiable simulation, which allows the algorithm to predict how small changes in an object’s properties, like mass or softness, impact the robot’s ending joint position. The researchers built their simulations using NVIDIA’s Warp library, an open-source developer tool that supports differentiable simulations.

Once the differentiable simulation matches up with the robot’s real movements, the system has identified the correct property. The algorithm can do this in a matter of seconds and only needs to see one real-world trajectory of the robot in motion to perform the calculations.

“Technically, as long as you know the model of the object and how the robot can apply force to that object, you should be able to figure out the parameter you want to identify,” Liu says.

The researchers used their method to learn the mass and softness of an object, but their technique could also determine properties like moment of inertia or the viscosity of a fluid inside a container.

Plus, because their algorithm does not need an extensive dataset for training like some methods that rely on computer vision or external sensors, it would not be as susceptible to failure when faced with unseen environments or new objects.

In the future, the researchers want to try combining their method with computer vision to create a multimodal sensing technique that is even more powerful.

“This work is not trying to replace computer vision. Both methods have their pros and cons. But here we have shown that without a camera we can already figure out some of these properties,” Chen says.

They also want to explore applications with more complicated robotic systems, like soft robots, and more complex objects, including sloshing liquids or granular media like sand.

In the long run, they hope to apply this technique to improve robot learning, enabling future robots to quickly develop new manipulation skills and adapt to changes in their environments.

“Determining the physical properties of objects from data has long been a challenge in robotics, particularly when only limited or noisy measurements are available. This work is significant because it shows that robots can accurately infer properties like mass and softness using only their internal joint sensors, without relying on external cameras or specialized measurement tools,” says Miles Macklin, senior director of simulation technology at NVIDIA, who was not involved with this research.

This work is funded, in part, by Amazon and the GIST-CSAIL Research Program.

President Trump’s attack on public broadcasting has attracted plenty of deserved attention, but there’s a far more technical, far more insidious policy change in the offing—one that will take away Americans’ right to unencumbered access to our publicly owned airwaves.

The FCC is quietly contemplating a fundamental restructuring of all broadcasting in the United States, via a new DRM-based standard for digital television equipment, enforced by a private “security authority” with control over licensing, encryption, and compliance. This move is confusingly called the “ATSC Transition” (ATSC is the digital TV standard the US switched to in 2009 – the “transition” here is to ATSC 3.0, a new version with built-in DRM).

The “ATSC Transition” is championed by the National Association of Broadcasters, who want to effectively privatize the public airwaves, allowing broadcasters to encrypt over-the-air programming, meaning that you will only be able to receive those encrypted shows if you buy a new TV with built-in DRM keys. It’s a tax on American TV viewers, forcing you to buy a new TV so you can continue to access a public resource you already own. 

This may not strike you as a big deal. Lots of us have given up on broadcast and get all our TV over the internet. But millions of American still rely heavily or exclusively on broadcast television for everything from news to education to simple entertainment. Many of these viewers live in rural or tribal areas, and/or are low-income households who can least afford to “upgrade.” Historically, these viewers have been able to rely on access to broadcast because, by law, broadcasters get extremely valuable spectrum licenses in exchange for making their programming available for free to anyone within range of their broadcast antennas. 

If broadcasters have cool new features the public will enjoy, they don’t need to force us to adopt them

Adding DRM to over-the-air broadcasts upends this system. The “ATSC Transition” is a really a transition from the century-old system of universally accessible programming to a privately controlled web of proprietary technological restrictions. It’s a transition from a system where anyone can come up with innovative new TV hardware to one where a centralized, unaccountable private authority gets a veto right over new devices. 

DRM licensing schemes like this are innovation killers. Prime example: DVDs and DVD players, which have been subject to a similar central authority, and haven’t gotten a single new feature since the DVD player was introduced in 1995. 

DRM is also incompatible with fundamental limits on copyright, like fair use.  Those limits let you do things like record a daytime baseball game and then watch it after dinner, skipping the ads. Broadcasters would like to prevent that and DRM helps them do it. Keep in mind that bypassing or breaking a DRM system’s digital keys—even for lawful purposes like time-shifting, ad-skipping, security research, and so on—risks penalties under Section 1201 of the Digital Millennium Copyright Act. That is, unless you have the time and resources to beg the Copyright Office for an exemption (and, if the exemption is granted, to renew your plea every three years). 

Broadcasters say they need this change to offer viewers new interactive features that will serve the public interest. But if broadcasters have cool new features the public will enjoy, they don’t need to force us to adopt them. The most reliable indicator that a new feature is cool and desirable is that people voluntarily install it. If the only way to get someone to use a new feature is to lock up the keys so they can’t turn it off, that’s a clear sign that the feature is not in the public interest. 

That's why EFF joined Public Knowledge, Consumer Reports and others in urging the FCC to reject this terrible, horrible, no good, very bad idea and keep our airwaves free for all of us. We hope the agency listens, and puts the interests of millions of Americans above the private interests of a few powerful media cartels.