MIT in the media: For the future of tech, "Massachusetts can absolutely lead"

On June 9, The Boston Globe released its 2026 “Tech Power Players” list, recognizing 50 influential local leaders in technology and business across Massachusetts. The list includes eight MIT affiliates including President Sally Kornbluth, Prof. Daniela Rus (director of CSAIL), Prof. Regina Barzilay, Prof. Yet-Ming Chiang, Prof. Max Tegmark, Ana Bakshi (executive director of the Martin Trust Center for MIT Entrepreneurship), Katie Rae CEO and Managing Partner of Engine Ventures), and Senior Lecturer Brian Halligan, along with a number of MIT alumni.

In addition to recognizing individual leaders, the Power Players coverage highlights MIT’s research labs, its culture of innovation and entrepreneurship, industry connections, new AI initiatives, and the Institute’s deep commitment to maintaining Massachusetts’ technological leadership.

“Massachusetts can absolutely lead in this next wave,” says President Kornbluth, noting that the future is bright with burgeoning opportunities to advance technologies in fields from manufacturing, life and health sciences to quantum technologies and energy in service of Americans across the country.

Advancing AI and entrepreneurship 

When it comes to AI, MIT is “working to drive artificial intelligence forward in sectors where the region is strongest, from biotechnology and robotics to defense and clean energy. It’s also trying to broaden entrepreneurship through a ‘dorm-to-startup’ push, creating a pipeline of support services — from hack-a-thons to venture funding — to help students to start companies between classes,” writes Robert Weisman for The Globe. 

Looking ahead, The Globe highlights how MIT aims to remain a central driver of AI advancement within higher ed. 

“President Sally Kornbluth is reinvigorating the school’s support of the local innovation ecosystem,” writes Aaron Pressman, noting how MIT is “unveiling new online classes dedicated to AI — with free entry-level classes for anyone — and encouraging more entrepreneurship on campus.”

MIT’s free, online AI courses could help local tech leaders in their challenge “to ensure people, not only corporations, benefit from the technology,” writes Pressman.

And when it comes to applying AI technologies to real-world problems, MIT aims to ensure the greater Boston area remains a leader.

“Some schools in Massachusetts, including MIT, are carving out a specialty in applied AI — sometimes called ‘AI+X’ — deploying the technology to help businesses, hospitals, and research institutions to supercharge productivity, innovation, and scientific breakthroughs,” explains Weisman.

Aman Narang ‘04, CEO of Toast, adds: “The superpower has always been the university system. The best thing Boston can do is keep these people around.”

MIT startups are a key driver of the region’s entrepreneurial ecosystem. To ensure the greater Boston area remains a hub for innovators and to respond to growing student interest, MIT is looking to build upon its existing entrepreneurship resources for students, including the more than 150 courses and 85 centers and programs dedicated to fostering an entrepreneurial community. Additionally, President Sally Kornbluth and Provost Anantha Chandrakasan recently formed the Committee on Accelerating Translation and Entrepreneurship (CATE) to explore anew how the Institute can best support, remove barriers to, and accelerate the movement of ideas from MIT’s research and innovative discoveries into new ventures. 

Further, reflecting on the optimism surrounding the Greater Boston tech scene, The Globe describes how applications for The Martin Trust Center for MIT Entrepreneurship’s startup accelerator program have doubled from last year, and nearly one-fifth of MIT undergraduates — about 800 students — attended a recent startup career fair.

Innovating change beyond MIT

The simple worm could drive the future of AI. This might sound like a squishy premise, but that’s the idea behind MIT startup Liquid AI, which is developing AI models inspired by the brain structure of a simple worm and could significantly reduce AI energy consumption. Liquid AI’s models, “which can uncover financial fraud and pilot autonomous drones, require far less electricity to operate than large language models, saving energy and water, which is used to cool data centers,” Pressman explains.

The Globe highlights how Liquid AI recently signed a deal with Mercedes-Benz to incorporate its technology into the onboard systems of cars sold in North America.

To power new AI technologies – and ensure Americans across the country can have reliable and affordable energy sources – researchers at MIT and a number of alumni are also turning their attention to the future of energy. 

In Prof. Yet-Ming Chiang’s lab, researchers are developing batteries that can store more electricity over longer periods, creating “more opportunities for wind, solar, and other clean energy sources.”

Weisman highlights how “Chiang’s lab and other MIT research centers are also working on innovations in microchips, critical minerals, fusion technology, and defense tech. All are examples of ‘tough tech’ projects combining science and engineering, which Chiang says ‘are in the sweet spot of the Boston ecosystem.’“

Soon, 80 MIT students will work as summer interns and employees at GE Vernova, thanks to the MIT-GE Vernova Climate and Energy Alliance, a collaboration aimed at advancing research and education that will accelerate the global energy transition.

GE Vernova CEO Scott Strazik wanted his organization to “plug into the city’s innovation culture,” particularly the MIT campus and community. The company announced it would dedicate $50 million over five years to fund internships and research projects in which students and faculty work alongside GE Vernova engineers and technicians.

The most promising area for the Greater Boston tech scene

The Globe concludes by asking each Power Player what the most promising thing about the Greater Boston tech scene is right now.

For Rus, the answer is: “talent. Boston has the best AI researchers in the world, and they're producing genuinely new ideas, not incremental ones,” she explains. 

When it comes to realizing the potential of fusion energy, Bob Mumgaard SM ’15, co-founder and CEO of Commonwealth Fusion Systems, explains that he couldn’t have built the company anywhere but Massachusetts thanks to the region’s expertise in engineering, designing, and manufacturing hardware and equipment and access to university researchers.

“The ecosystem has the building blocks,” says Mumgaard. “Massachusetts is the strongest in the nation in innovation in energy.”

President Kornbluth points to quantum.

“There isn’t a more important technological field right now than quantum science and technology, and the Boston area has the greatest concentration of quantum talent anywhere in the world,” Kornbluth emphasizes.

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“We can’t ship goods without functioning ports”

In the small coastal town of Prince Rupert, British Columbia, the port is the backbone of the community.

Growing up there, with a father who works as a longshoreman, Chelsea Mitchell witnessed the port’s importance firsthand. From an early age, she understood that the port was essential to the transportation of goods in and out of not only Prince Rupert but all of British Columbia’s North Coast. Disruptions to port operations could have ripple effects reaching from dockworkers’ families to the regional economy and beyond. 

“The port is central to my hometown’s economy,” Mitchell says. “Having family in the industry gave me visibility into the complexity and the volatility of the shipping industry.”

Today, that industry and the forces that shape it are the subject of Michell’s research as a fourth-year PhD student in MIT’s Department of Economics. She studies how ports and shipping companies compete, how goods move through congested terminals, and how disruptions affect global supply chains.

“When I was younger, I never would have imagined I would get to conduct research at MIT,” Mitchell says. “Prince Rupert is largely a blue-collar town, so I had minimal insight into the world of academic research growing up. But in high school I realized I thrived in an academic environment, especially studying math, and hoped one day I could pursue a PhD.”

She left British Columbia to attend the University of Toronto, where she studied math and economics. There, faculty mentors introduced her to economic research and encouraged her to apply to doctoral programs, eventually leading her to the Institute.

“I was lucky to have mentors in college who encouraged me to apply to MIT. The level of support and quality of advising here has consistently amazed me,” Mitchell says.

Her research focus became clearer in 2023, when longshore workers along Canada’s West Coast walked off the job during a labor dispute centered, in part, on automation and its effect on port employment. The strike lasted roughly two weeks and shut down 35 terminals across the province. That experience left a lasting impression on Mitchell.

“These labor disruptions made me acutely aware that ports were a choke point in our supply chains,” Mitchell says. “They seemed understudied relative to how important they are.”

Because of her family’s ties to the industry, Mitchell was able to spend time speaking not only with her father’s co-workers who were involved in the strike but also with people working throughout the shipping industry. 

One of her first major projects examined labor negotiations and competition among American ports. She found that even just the possibility of work disruptions in ports could alter shipping patterns, prompting companies to reroute cargo away from West Coast ports and toward East Coast facilities despite added logistical cost.

Her current work focuses on another major shift in the industry: the growing number of shipping companies that own container terminals.

Traditionally, carriers relied on independent terminal operators to load and unload cargo. Increasingly, however, major shipping lines have begun acquiring terminals themselves. Using detailed vessel-tracking and port-call data, Mitchell studies what happens after those acquisitions occur.

Her findings suggest that ships operated by the acquiring carrier often receive faster service, particularly during periods of congestion when terminal capacity is limited. Competing carriers, meanwhile, face longer wait times and are more likely to divert cargo to other terminals.

“Ports are notoriously capacity constrained, but all carriers need access to them,” Mitchell says. “A central question is what advantages these acquisitions create and whether they affect competition.”

More broadly, Mitchell hopes her work highlights the importance of an industry that has often gone unnoticed by consumers. Approximately 80 percent of global trade moves by sea, making ports essential infrastructure for the modern economy.

“People have become increasingly aware of the shipping industry, but we can’t ship goods without functioning ports,” she says. “We want ports to be reliable and efficient so that supply chains function and goods can remain affordable.”

Mitchell credits her advisors, Nancy Rose and Tobias Salz, with helping her navigate her research, especially through difficult obstacles. More broadly, she says the people she has met at MIT have been the most rewarding part of her experience thus far.

Outside of economics, Mitchell enjoys exercising, skiing, reading, and spending time with friends. She finds that having a work-life balance is essential to her success as a researcher.

“Research is extremely challenging,” Mitchell says. “You invest a lot of time trying to answer questions that you don’t necessarily know are answerable given the data you have. It’s important to have rewarding aspects of your life outside of research that can help keep you motivated.”

Still, whether she is analyzing data in Cambridge, Massachusetts, or returning home to the rugged coastline of northern British Columbia, Mitchell takes a people-first approach to her research.

“I see numbers. I see data. But it’s challenging to tell a story with that data when you don’t have insights from the people who are actually doing the work,” Mitchell says. “Talking to people in the industry has been fundamental to understanding what’s really happening.”

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QS ranks MIT the world’s No. 1 university for 2026-27

MIT has again been named the world’s top university by the QS World University Rankings, which were announced today. This is the 15th year in a row MIT has received this distinction.

The full 2027 edition of the rankings — published by Quacquarelli Symonds, an organization specializing in education and study abroad — can be found at TopUniversities.com. The QS rankings are based on factors including academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students. 

MIT was also ranked the world’s top university in 12 of the subject areas ranked by QS, as announced in March of this year. 

The Institute received a No. 1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Engineering and Technology; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research.

MIT also placed second in seven subject areas: Architecture/Built Environment; History of Art; Biological Sciences; Economics and Econometrics; Marketing; Natural Sciences; and Statistics and Operational Research.

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Flexible cryogenic cables solve a challenge in quantum system development

By harnessing the unique properties of quantum mechanics, scientists and engineers worldwide seek to enable systems with extraordinary capabilities. Many of them are working on the highly anticipated development of quantum computers capable of completing complex calculations at unprecedented speeds. These computers could meet the growing computational demands of both scientific research and data-intensive industries like finance, cybersecurity, and medicine.  

Necessary for quantum system development is an environment in which the fragile nature of quantum bits (qubits) is stabilized and the thermal noise (fluctuations in current/voltage) inherent in superconducting electronics is dampened. That environment requires cryogenic temperatures, those ranging from 5 to 10 millikelvins, colder than the extreme temperatures encountered in space. Dilution refrigerators create this needed cryogenic condition.

Dilution refrigerators used for quantum R&D need a wiring system that can operate in cryogenic temperatures, maintain a power-efficient direct current, and support high-speed data transmission. Researchers at MIT Lincoln Laboratory prototyped flexible, ribbon-like, low-frequency (LF) cables that not only meet these demands, but also are compatible with commercial circuit-board manufacturing processes. Maybell Quantum, a Colorado-based company supplying hardware for developing quantum systems, licensed the design for these cables and is adapting them for use in their dilution refrigerators.

"We’re planning to integrate Maybell LF CryoTrace, the ribbon wiring system transferred from MIT Lincoln Laboratory, across all thermal stages of our dilution refrigerators. Initially, the cables will be used for LF services, such as thermometry, heaters, and sensors, with feasibility studies planned for additional functions," says Lasse Nielsen, strategy and operations lead at Maybell Quantum. "After qualification testing, LF CryoTrace is planned for the next iteration of our internal wiring across the Maybell product family."

Motivation for invention

To support government initiatives in quantum computing, the Lincoln Laboratory research team investigated alternatives to conventional coaxial cables for use in hardware like dilution refrigerators. Coaxial cables can generate heavy heat loads for cryogenic hardware to address. And, as the number of qubits in quantum computers will increase, so will the number of coaxial cables in the infrastructure, making it difficult to fit stiff, bulky cable arrays into hardware supporting superconducting qubits.    

The team chose a stripline cable configuration with conductive layers positioned between flexible polymer layers that shield against electromagnetic interference (also known as crosstalk). Striplines offer consistency across different frequencies and minimal signal loss. The new cables were designed to accommodate large numbers of simultaneous signal transmissions; support direct-current operation without warming the cryogenic environment; and, importantly, provide easier integration into hardware than achievable with brittle coaxial cables.

"The main innovation is that the laboratory's cables can be fabricated by a traditional printed-circuit-board manufacturer. They're cheaper to fabricate and easier to install than traditional coaxial cables," says John Cummings, a principal investigator in the flexible cables project of the Lincoln Laboratory Quantum-Enabled Computation Group.

Citing ease of installation and durability as two factors making these cables attractive, Maybell Quantum says the ribbon format is mechanically robust, reducing handling-related breakages common with thin coaxials and improving repeatability in production. The supple flex cables allow assembly tasks that took days to complete to be done in a few hours.

"Over time, we think ribbonized, quantum-specific internal wiring can reshape manufacturing norms: faster and more consistent builds, easier field service, and more modular upgrades," Nielsen says.

Future outlook

Maybell Quantum is looking toward supporting quantum computing's transition from a laboratory-based capability to an industrial, commercially viable one. The huge gap between the current highly specialized quantum-laboratory environment and the robust infrastructure required for future industrial quantum computing lies in the hardware promoting the development of functional chips.

Maybell's mission is to develop reliable tools that commercial developers of quantum computers can use with ease and without the high costs and expert training associated with the equipment in today's quantum labs. The flex cables and Maybell's continued R&D into their capabilities and integration into various tools will foster a future infrastructure that could enable industry to scale manufacture of quantum computers to a level at which these powerful machines could cost-effectively find use in myriad enterprises.

"If you want to scale to hundreds of chips, you need interconnects that can handle more signals more reliably. That’s why the Lincoln Laboratory cables are so exciting for us — they enable true scalability," says Kyle Thompson, founder and chief technology officer of Maybell Quantum. "We believe this technology will materially improve our systems and strengthen the broader U.S. quantum ecosystem by moving federally funded innovation into American manufacturing."

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MIT Open Learning reaches all the way to the South Pole

From the icy expanse of the South Pole, John Della Costa, a researcher on the Background Imaging of Cosmic Extragalactic Polarization (BICEP) project, watches STS.042/8.225 (Einstein, Oppenheimer, Feynman: Physics in the 20th Century), a free online class from MIT Open Learning’s OpenCourseWare, as part of a weekly “Fysics Fridays” series he started with his team.

MIT Professor David Kaiser, who teaches the course, often receives thoughtful notes from remote learners, but says an email from Della Costa stood out.

“Hearing that John and his team are spending a part of their time with this course was just the best message to receive,” says Kaiser.

The BICEP collaboration uses a series of radio telescopes at the South Pole to study the cosmic microwave background — the oldest light, emitted about 380,000 years after the start of the universe. The team is looking for signs of primordial gravitational waves, which would help to support MIT Professor Alan Guth’s theory of cosmic inflation that explains the rapid early expansion of the universe.

“Inflation is really important in making sense of our observations of our universe,” says Della Costa. “We have yet to discover the evidence for inflation that definitively proves that it did happen, and BICEP’s main role here at the South Pole is to discover gravitational waves from the very early universe.”

Kaiser co-directs a research group on early-universe cosmology with Guth. He says he has colleagues who have worked as Antarctica winter-overs, and can appreciate the immense challenge of this work.

“It’s very exciting to see this important research flourishing,” says Kaiser. “It takes enormous effort and dedication.” 

Bringing Open Learning to the South Pole

Della Costa first discovered MIT OpenCourseWare, part of MIT Open Learning, as a graduate student at San Diego State University. At the time, the Covid-19 pandemic had altered his schedule and created more downtime to pursue additional independent learning. He was taking a nuclear physics course as part of his graduate program in astrophysics, and wanted to learn much more about the topic. A little bit of online research led to his discovery of class 22.01 (Introduction to Nuclear Engineering and Ionizing Radiation), taught by Professor Michael Short.

“I found the course so interesting, and I’ve been exploring OpenCourseWare ever since then,” says Della Costa.

Preparing to spend an entire year at the South Pole (from November 2025 to December 2026), he realized he would need a productive way to occupy his downtime and stay entertained while isolated from much of the world.

“The station is completely isolated. After a certain point, no planes can fly in because it’s too cold,” says Della Costa. “The station closed on February 14, and it will reopen at the end of October or early November, depending on the weather.”

Because internet access is so limited at the South Pole, he downloaded several courses ahead of time, including: STS.042/8.225, 8.02 (Physics II: Electricity and Magnetism), 8.03 (Physics III: Vibrations and Waves), and Guth’s course, 8.286 (The Early Universe).

Like Della Costa’s discovery of OpenCourseWare, STS.042/8.225 was rooted in the disruptive days of the Covid-19 pandemic. Kaiser had taught the course in its traditional, in-person format many times, until fall 2020, when the courses needed to be taught entirely remotely. He made slides and taught the course via Zoom — for synchronous and asynchronous learning — to approximately 100 students located throughout the world. The materials were initially posted on the course site. The online version was later refined and expanded, launching on OpenCourseWare in August 2022. Unlike many physics offerings, this course includes background readings by physicists, as well as historians, philosophers, and sociologists.

“In this course, we get to talk about some really amazing ideas from modern physics,” says Kaiser. “We start in the middle of the 19th century, still in an era of what we would now call classical physics, and we rapidly go through things like relativity, quantum theory, nuclear physics, and particle physics. We end up with some of my favorite material about cosmology and the Big Bang — the kinds of things that John and his team are actively working on right now from their perch at the South Pole.”

Building community and learning together

Beyond finding ways to stay occupied during downtime from his research, Della Costa realized the importance of engaging the 45-person community at the South Pole. He describes it as a tight-knit group that needs to work together and look out for one another, especially given the extreme isolation, cold, and darkness, which can take a serious toll on mental health during the winter months.

“It’s very important to have community activities here,” says Della Costa, who thought of the idea to launch the “Fysics Fridays” series a couple of months ago. 

The group gathers to watch lectures and documentaries about physics every Friday. The series kicked off with a documentary about atomic bombs, drawing strong interest from the very beginning. 

Della Costa realized that STS.042/8.225 would be an ideal offering for Fysics Fridays.

“I thought this would be a perfect lecture series for us to watch, because it’s fairly introductory,” says Della Costa. “Not everyone here is a physicist, actually. It’s widely accessible, but still meaty, and worth people’s time to watch.”

Team members have been very interested in watching the course, and they’ve also started doing experiments before watching the lectures. Della Costa says that they’ve done the double-slit experiment and plan to also make a cloud chamber to see cosmic rays going through it.

Now that Della Costa and Kaiser are in contact, Kaiser has made plans to provide a special Zoom colloquium for the community at the South Pole.

“This use of the course is especially inspiring,” says Kaiser. “It really speaks to the excellence and far reach of OpenCourseWare and Open Learning.”

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Could AI tell you where you left your keys?

An auto factory worker can remember the storage bin where she left a partly assembled component the night before, and quickly return to that spot to pick it up. But robots that may work side-by-side with her would struggle to develop and access this same type of “spatiotemporal” memory.

Now, MIT researchers have developed a long-term memory framework that allows robots to rapidly form and recall a detailed mental model of complicated, large-scale environments.

In the future, this advance could allow the factory worker to send a robotic assistant to fetch the item, simply by asking it to “go and grab the component we started assembling last night.”

This new method combines advanced map representations with rich descriptions of the environment that the robot gathers as it travels over a long period of time. The robot can quickly access this memory to answer complex queries about its environment in plain language.

This memory framework, which answers questions more accurately than state-of-the-art methods, runs fast enough for a mobile robot to use in real-time.

In addition to its potential uses in robotics, this method could have applications in augmented reality systems that aid maintenance workers in anomaly detection or assist commuters in wayfinding.

“If we want robots to work side-by-side with humans and interact better with humans, they must speak the same language. The robot must be able to reason about time and space the same way humans do. That is essentially what our method is doing. It is turning a traditional map into a language-based map that is easier for the robot to think about and access using language,” says Luca Carlone, an associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory.

He is joined on the paper by lead author Nicolas Gorlo, an MIT graduate student; and Lukas Schmid, a former research scientist at MIT and now professor at the University of Technology Nuremberg in Germany. The research was recently presented at the Conference on Computer Vision and Pattern Recognition (CVPR).

Spatiotemporal memory

Memory allows an artificial intelligence system, like a chatbot, to answer complex questions and reason about previous interactions with its user.

“We want to design a new type of memory, a spatiotemporal memory, that enables an AI-powered robot to remember real interactions and sensor observations. Like ChatGPT, but grounded in the real world and capable of answering any question about the environment, like ‘Where did I leave my wallet?’” Carlone says.

To develop such a memory framework, the MIT researchers bridged two lines of work: computer vision and robotic mapping.

Multimodal computer vision models can understand and richly describe the objects in a scene, but they often only process a single annotation at a time. On the other hand, robotic mapping frameworks create 3D maps of an environment, like an entire apartment or university campus, but usually lack detailed descriptions of objects or are computationally expensive.

The method the MIT researchers created, called Describe Anything, Anywhere, Anytime, at Any Moment (DAAAM), takes the best of both approaches.

Using DAAAM, as a robot traverses its environment, it attaches rich descriptions to objects it sees. For instance, the robot may note that a particular building on the MIT campus is called the Stata Center and is designed with a certain type of architecture, or that a bike rack holds five bicycles and the red one has a flat tire. 

It stores this detailed information in a 3D map-based representation that is arranged spatially, so objects will be grouped into separate regions. In this way, the robot can remember that the red bicycle with the flat tire is in the bike rack outside the Stata Center.

But existing techniques that capture such rich descriptions typically take a few seconds to annotate a few objects. This is too slow for real-time performance, since a robot might see hundreds of objects during a few minutes of exploration.

“The faster the robot can form this spatial memory, the more efficient it will be performing actions in the environment,” Carlone adds.

Streamlining the process

To speed things up, DAAAM aggregates nearby objects as it travels and uses an optimization method to select key frames to annotate. These are images with the clearest view of multiple objects, allowing the system to thoroughly describe several items in parallel, speeding up computation tenfold.

As the robot explores the space, it attaches each batch of annotations to multiple objects in a particular location on the 3D map.

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

Once the system builds this spatial memory, it must retrieve information from an enormous database of objects and descriptions in an efficient manner. 

To enable this, the researchers used an LLM that calls on various tools, which can quickly retrieve specific information in a way that reduces hallucinations. This allows DAAAM to answer a user query accurately in only a few seconds. 

For instance, if one asks a robot about a certain sculpture it saw near an MIT campus building, DAAAM can use a semantic search tool to retrieve information based on the word “sculpture” or a different tool to retrieve information based on the location of the building.

When tested and compared with other methods, DAAAM was between 21 percent and 53 percent more accurate, depending on the question type. 

In the future, the researchers want to expand DAAAM so the system can capture significant events that happened in the environment. They are also working to incorporate confidence levels into the system’s responses.

“Ultimately, we want to have robots that can help with any sort of tasks. With this framework, we are trying to create the foundations to enable a generalist agent that can do anything you ask,” Gorlo says.

This research was funded, in part, by the U.S. Army Research Laboratory and the Office of Naval Research. Carlone is currently on sabbatical as an Amazon Scholar; this article describes work performed at MIT and is not associated with Amazon.

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MIT’s Initiative for New Manufacturing builds momentum

In May, the Initiative for New Manufacturing (INM) marked its first anniversary with MIT Manufacturing Week, four days of events that attracted more than 800 registrants including students, faculty, industry leaders, investors, entrepreneurs, and government officials to explore topics ranging from how companies are using AI on factory floors to the role of startups in introducing innovation to new workforce solutions to address the worker shortage.

“INM launched a year ago with the premise that strengthening the industrial base needed a coordinated response, and MIT has a responsibility to lead it,” says Paula T. Hammond, dean of MIT’s School of Engineering and co-chair of INM’s Steering Committee. “The response and participation level has been huge. MIT Manufacturing Week proved that the appetite for change — from students to chief executives — is real and urgent.”

The week opened with a cybersecurity workshop co-led by INM and Google Cloud for the initiative’s industry members. It continued with the MIT MIMO (Machine Intelligence for Manufacturing Operations) symposium focused on deploying artificial intelligence on factory floors, alongside discussions on workforce development, emerging technologies, startups, and industrial transformation. The week closed with a regional research showcase and competition that drew more than 140 graduate students and postdocs from across New England.

Over the past year, INM has also continued its distinguished speaker series featuring manufacturing leaders including Keith Flynn, senior vice president of manufacturing at Anduril; Roland Busch, president and CEO of Siemens; and Venky Alagirisamy, COO of Nike.

Inspiring a new generation of manufacturing startups

A central goal of INM is to help more students see manufacturing as a frontier for scientific discovery, technological innovation, entrepreneurship, and societal impact.

To support that effort, INM is launching and leading programs to help move early-stage ideas and new technologies from the lab to real-world development, and to catalyze new manufacturing companies. 

This year, INM partnered with NSF I-Corps New England, which helps researchers turn their startup ideas into companies, to host its first manufacturing research showcase. More than 140 teams from 17 universities across New England applied to participate. Forty finalist teams received mentorship on their ideas and advanced to the final competition, where eight teams shared $50,000 in prize funding.

The top prize in the category “most transformative innovation” went to MIT PhD student Jake Read for “The End of G Code,” a project focused on modular machine control architectures designed to accelerate the development of new manufacturing equipment and processes. Vatsal Patel from MIT and Joshua Grace from Yale University won the top prize in the research excellence category, for “VisFT,” scalable six-axis force-torque sensors.

Project themes presented by participating teams included AI tools for manufacturing, semiconductor manufacturing and process control, robotics and autonomous assembly, digital twins and simulation, new materials, additive manufacturing, next-generation shipbuilding, and biomanufacturing. 

“Entrepreneurship is a transformative pathway to take research to market, and to drive faster innovation and scale-up,” says John Hart, INM faculty co-director and head of MIT’s Department of Mechanical Engineering. “At INM’s inaugural research showcase, we had tremendous interest from universities across New England, along with enthusiastic participation from industry, investors, and experienced founders across the ecosystem. We are excited to build on this success and work toward a nationwide program and platform for entrepreneurship and translation in manufacturing.” 

The Cheng Wu Foundation supported the showcase. 

Growing industry membership

During MIT Manufacturing Week, First Solar became INM’s eighth industry member, joining Amgen, Autodesk, GE Vernova, Flex, PTC, Sanofi and Siemens. 

The growth of INM’s consortium reflects a broader recognition that the challenges facing modern manufacturing — from supply chain resilience to workforce development and industrial competitiveness — are too complex for any single sector or company to address alone. 

This reflects renewed interest in manufacturing at a moment when advances in artificial intelligence, robotics, energy systems, and advanced materials are transforming industrial production. INM provides a platform to convene and provide solutions.

INM’s industry consortium model brings industry, researchers, and educators together around shared manufacturing challenges, with a focus on emerging technologies, workforce transformation, and commercialization pathways. Members participate in workshops and working groups on topics including cybersecurity and digital twins, implementing automated systems, AI agents in regulatory environments, and AI and continuous innovation. INM helps them connect with students, meet with startups, and learn from one another.

“Our members see MIT as a partner that can help them both address today’s challenges and think far into the future,” says Rick Locke, dean of the MIT Sloan School of Management and co-chair of INM’s steering committee. “This kind of multi-industry engagement is unusual and powerful.”

A year of rapid progress

When MIT launched INM a year ago, the goal was to create stronger connections between research, industry, workforce development, and entrepreneurship — helping accelerate how new manufacturing technologies move from the laboratory into real-world development.

Since then, the initiative has expanded quickly across research, industry, workforce training, and student engagement. INM issued a call for proposals focused on artificial intelligence and automation, receiving an incredible response from faculty and researchers, and funding eight seed research projects. In June, the initiative plans to publish eight white papers as part of a broader study examining the future of manufacturing. 

During MIT’s Independent Activities Period (IAP) in January 2026, INM collaborated with NSF I-Corps to guide 13 early-stage teams through customer discovery as part of the I-Corps Spark program.

Workforce development has also been a major focus. This fall, MIT launched the Technologist Advanced Manufacturing Program (TechAMP), led by Principal Research Scientist John Liu, to create a new generation of shop floor leaders and drivers of productivity — becoming“‘technologists” — at six sites across New England, including three community colleges. 

“INM has the potential to transform the national manufacturing workforce,” says Liu. “It will require deep engagement between how people learn and lead, and how firms adopt new technologies and transform. We’re just getting started.” 

INM is now exploring a national rollout of TechAMP, along with expansion into areas including biomanufacturing and semiconductor manufacturing.

On campus, INM supported student engagements including an AI and automation lunch series that Professor Faez Ahmed and colleagues organized, and visited factories through its Factory Observatory program that Ben Armstrong and the MIT Industrial Performance Center led. This spring, students also founded MIT’s first manufacturing club, holding its launch event during MIT Manufacturing Week. “We’re thrilled students are taking the lead,” says Sloan associate professor and INM faculty co-director Karen Zheng. “It was really exciting to see a full room of 80-plus students across campus coming together for the kickoff event during the busiest final period of a semester. This speaks to the students’ enthusiasm.” 

An eye toward the long term

While maintaining a deep focus on strengthening domestic manufacturing, INM aims to have a global reach. For example, the initiative is collaborating with NAMTECH, a new education institute in Ahmedabad, India, where students are now taking an adaptation of MIT’s well-known “yo-yo course,” or 2.008 (Design and Manufacturing II), focused on the fundamentals of manufacturing processes.

Next year, INM plans to bring more manufacturing leaders to campus, offer additional programming for emerging entrepreneurs, graduate the first cohort of TechAMP students, bring TechAMP to new states, grow the consortium to include new industries, and deepen research into manufacturing productivity. 

“INM aims to be a catalyst for transforming manufacturing across the nation to drive innovation, economic growth, and new types of jobs,” says Chris Love, faculty co-director of INM. “MIT’s work on the PIE (Production in the Innovation Economy) study in 2013 highlighted the value of proximity between production and innovation. INM seeks to rekindle this relationship in manufacturing across the country.”

de MIT News https://ift.tt/O4KUenM