Generative AI and robotics are moving us ever closer to the day when we can ask for an object and have it created within a few minutes. In fact, MIT researchers have developed a speech-to-reality system, an AI-driven workflow that allows them to provide input to a robotic arm and “speak objects into existence,” creating things like furniture in as little as five minutes.  

With the speech-to-reality system, a robotic arm mounted on a table is able to receive spoken input from a human, such as “I want a simple stool,” and then construct the objects out of modular components. To date, the researchers have used the system to create stools, shelves, chairs, a small table, and even decorative items such as a dog statue.

“We’re connecting natural language processing, 3D generative AI, and robotic assembly,” says Alexander Htet Kyaw, an MIT graduate student and Morningside Academy for Design (MAD) fellow. “These are rapidly advancing areas of research that haven’t been brought together before in a way that you can actually make physical objects just from a simple speech prompt.”  

The idea started when Kyaw — a graduate student in the departments of Architecture and Electrical Engineering and Computer Science — took Professor Neil Gershenfeld’s course, “How to Make Almost Anything.” In that class, he built the speech-to-reality system. He continued working on the project at the MIT Center for Bits and Atoms (CBA), directed by Gershenfeld, collaborating with graduate students Se Hwan Jeon of the Department of Mechanical Engineering and Miana Smith of CBA.

The speech-to-reality system begins with speech recognition that processes the user’s request using a large language model, followed by 3D generative AI that creates a digital mesh representation of the object, and a voxelization algorithm that breaks down the 3D mesh into assembly components.

After that, geometric processing modifies the AI-generated assembly to account for fabrication and physical constraints associated with the real world, such as the number of components, overhangs, and connectivity of the geometry. This is followed by creation of a feasible assembly sequence and automated path planning for the robotic arm to assemble physical objects from user prompts.

By leveraging natural language, the system makes design and manufacturing more accessible to people without expertise in 3D modeling or robotic programming. And, unlike 3D printing, which can take hours or days, this system builds within minutes.

“This project is an interface between humans, AI, and robots to co-create the world around us,” Kyaw says. “Imagine a scenario where you say ‘I want a chair,’ and within five minutes a physical chair materializes in front of you.”

The team has immediate plans to improve the weight-bearing capability of the furniture by changing the means of connecting the cubes from magnets to more robust connections. 

“We’ve also developed pipelines for converting voxel structures into feasible assembly sequences for small, distributed mobile robots, which could help translate this work to structures at any size scale,” Smith says.

The purpose of using modular components is to eliminate the waste that goes into making physical objects by disassembling and then reassembling them into something different, for instance turning a sofa into a bed when you no longer need the sofa.

Because Kyaw also has experience using gesture recognition and augmented reality to interact with robots in the fabrication process, he is currently working on incorporating both speech and gestural control into the speech-to-reality system.

Leaning into his memories of the replicator in the “Star Trek” franchise and the robots in the animated film “Big Hero 6,” Kyaw explains his vision.

“I want to increase access for people to make physical objects in a fast, accessible, and sustainable manner,” he says. “I’m working toward a future where the very essence of matter is truly in your control. One where reality can be generated on demand.”

The team presented their paper “Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assembly” at the Association for Computing Machinery (ACM) Symposium on Computational Fabrication (SCF ’25) held at MIT on Nov. 21. 

Both Rohit Karnik and Nathan Wilmers personify the type of mentorship that any student would be fortunate to receive — one rooted in intellectual rigor and grounded in humility, empathy, and personal support. They show that transformative academic guidance is not only about solving research problems, but about lifting up the people working on them.

Whether it’s Karnik’s quiet integrity and commitment to scientific ethics, or Wilmers’ steadfast encouragement of his students in the face of challenges, both professors cultivate spaces where students are not only empowered to grow as researchers, but affirmed as individuals. Their mentees describe feeling genuinely seen and supported; mentored not just in theory or technique, but in resilience. It’s this attention to the human element that leaves a lasting impact.

Professors Karnik and Wilmers are two of the 2023–25 Committed to Caring cohort who are cultivating confidence and craft across disciplines. For MIT graduate students, the Committed to Caring program recognizes those who go above and beyond.

Rohit Karnik: Rooted in rigor, guided by care

Rohit Karnik is Abdul Latif Jameel Professor in the Department of Mechanical Engineering at MIT, where he leads the Microfluidics and Nanofluidics Research Group and serves as director of the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS). His research explores the physics of micro- and nanofluidic flows and systems. Applications of his work include the development of water filters, portable diagnostic tools, and sensors for environmental monitoring. 

Karnik is genuinely excited about his students’ ideas, and open to their various academic backgrounds. He validates students by respecting their research, encouraging them to pursue their interests, and showing enthusiasm for their exploration within mechanical engineering and beyond.

One student reflected on the manner in which Karnik helped them feel more confident in their academic journey. When a student from a non-engineering field joined the mechanical engineering graduate program, Karnik never viewed their background as a barrier to success. The student wrote, “from the start, he was enthusiastic about my interdisciplinarity and the perspective I could bring to the lab.”

He allowed the student to take remedial undergraduate classes to learn engineering basics, provided guidance on leveraging their previous academic background, and encouraged them to write grants and apply for fellowships that would support their interdisciplinary work. In addition to these concrete supports, Karnik also provided the student with the freedom to develop their own ideas, offering constructive, realistic feedback on what was attainable. 

“This transition took time, and Karnik honored that, prioritizing my growth in a completely new field over getting quick results,” the nominator reflected. Ultimately, Karnik’s mentorship, patience, and thoughtful encouragement led the student to excel in the engineering field.

Karnik encourages his advisees to explore their interests in mechanical engineering and beyond. This holistic approach extends beyond academics and into Karnik’s view of his students as whole individuals. One student wrote that he treats them as complete humans, with ambitions, aspirations, and passions worthy of his respect and consideration — and remains truly selfless in his commitment to their growth and success.

Karnik emphasizes that “it’s important to have dreams,” regularly encouraging his mentees to take advantage of opportunities that align with their goals and values. This sentiment is felt deeply by his students, with one nominator sharing that Karnik “encourag[ed] me to think broadly and holistically about my life, which has helped me structure and prioritize my time at MIT.”

Nathan Wilmers: Cultivating confidence, craft, and care

Nathan Wilmers is the Sarofim Family Career Development Associate Professor of Work and Organizations at MIT Sloan School of Management. His research spans wage and earnings inequality, economic sociology, and the sociology of labor. He is also affiliated with the Institute for Work and Employment Research, and the Economic Sociology program at Sloan. Wilmers studies wage and earnings inequality, economic sociology, and the sociology of labor, bringing insights from economic sociology to the study of labor markets and the wage structure.

A remarkable mentor, Wilmers is known for guiding his students through different projects while also teaching them more broadly about the system of academia. As one nominator illustrates, “he … helped me learn the ‘tacit’ knowledge to understand how to write a paper,” while also emphasizing the learning process of the PhD as a whole, and never reprimanding any mistakes along the way. 

Students say that Wilmers “reassures us that making mistakes is a natural part of the learning process and encourages us to continuously check, identify, and rectify them.” He welcomes all questions without judgment, and generously invests his time and patience in teaching students.

Wilmers is a strong advocate for his students, both academically and personally. He emphasizes the importance of learning, growth, and practical experience, rather than solely focusing on scholarly achievements and goals. Students feel this care, describing “an environment that maximizes learning opportunities and fosters the development of skills,” allowing them to truly collaborate rather than simply aim for the “right” answers.

In addition to his role in the classroom and lab, Wilmers also provides informal guidance to advisees, imparting valuable knowledge about the academic system, emphasizing the significance of networking, and sharing insider information. 

“Nate’s down-to-earth nature is evident in his accessibility to students,” expressed one nominator, who wrote that “sometimes we can freely approach his office without an appointment and receive valuable advice on both work-related and personal matters.” Moreover, Wilmers prioritizes his advisees’ career advancement, dedicating a substantial amount of time to providing feedback on thesis projects, and even encouraging students to take a lead in publishing research.

True mentorship often lies in the patient, careful transmission of craft — the behind-the-scenes work that forms the backbone of rigorous research. “I care about the details,” says Wilmers, reflecting a philosophy shaped by his own graduate advisors. Wilmers’ mentors instilled in him a deep respect for the less-glamorous but essential elements of scholarly work: data cleaning, thoughtful analysis, and careful interpretation. These technical and analytical skills are where real learning happens, he believes. 

By modeling this approach with his own students, Wilmers creates a culture where precision and discipline are valued just as much as innovation. His mentorship is grounded in the belief that becoming a good researcher requires not just vision, but also an intimate understanding of process — of how ideas are sharpened through methodical practice, and how impact comes from doing the small things well. His thoughtful, detail-oriented mentorship leaves a lasting impression on his students.

A nominator acclaimed, “Nate’s strong enthusiasm for my research, coupled with his expressed confidence and affirmation of its value, served as a significant source of motivation for me to persistently pursue my ideas.”

Lost nationwide: $1.6 billion for building emergency shelters, treating drinking water and adapting to a changing climate.

But Gov. Kathy Hochul is holding off on creating a statewide cap-and-trade market, drawing criticism and a lawsuit from advocates.

Researchers reviewed reports from S&P 500 companies and found businesses often downplay climate pollution and revise them later.

The decision is a victory for landowners who oppose carbon injection beneath their property.

Brussels wants to dig up more critical minerals in the bloc but says "regulatory bottlenecks" are slowing things down.

A sequence of three tropical cyclones coincided with the regular northeast monsoon to deliver rainfall totals unseen in decades.

Global production of new plastic is set to increase by 52 percent, twice as much as waste management systems.

Swine fever can’t infect humans but is a major threat to pig farmers.

A new anonymous phone service allows you to sign up with just a zip code.

Everyone is talking about new quantum technologies, but what exactly is quantum and why are scientists, engineers and technologists so excited by the potential for this new field? On Monday, December 8, MIT will launch the MIT Quantum Initiative (or QMIT), an Institute-wide effort to apply quantum breakthroughs to the most consequential challenges in science, technology, industry, and national security. 

The interdisciplinary endeavor, the newest of MIT President Sally Kornbluth’s strategic initiatives, will bring together MIT researchers and domain experts from a range of industries to identify and tackle practical challenges wherever quantum solutions could achieve the greatest impact. In collaboration with MIT Lincoln Laboratory, industry leaders and end users from all domains, researchers from across the traditional quantum disciplines will work to identify and advance the most significant practical applications in science, technology, industry and national security.

The QMIT launch event will feature:

• Introductory remarks by Massachusetts Governor Maura Healey and MIT President Sally Kornbluth;
• MIT quantum luminaries, from Nobel Laureates Moungi Bawendi and Wolfgang Ketterle to Peter Shor, Nergis Mavalvala, Pablo Jarillo-Herrero, Paola Cappellaro, Isaac Chuang, Will Oliver, Vladan Vuletić and many others
• Industry leaders including Jay M. Gambetta (Director of Research, IBM), Hartmut Neven (Founder and Lead, Google Quantum AI) – and a range of MIT startups
• Eric Lander, Broad Institute founding director emeritus, offering reflections on the early adoption of innovative technology
• A lunchtime poster session highlighting student research in quantum science and engineering

More information on QMIT can be found here and the full agenda can be found here. 

There are some jobs human bodies just weren’t meant to do. Unloading trucks and shipping containers is a repetitive, grueling task — and a big reason warehouse injury rates are more than twice the national average.

The Pickle Robot Company wants its machines to do the heavy lifting. The company’s one-armed robots autonomously unload trailers, picking up boxes weighing up to 50 pounds and placing them onto onboard conveyor belts for warehouses of all types.

The company name, an homage to The Apple Computer Company, hints at the ambitions of founders AJ Meyer ’09, Ariana Eisenstein ’15, SM ’16, and Dan Paluska ’97, SM ’00. The founders want to make the company the technology leader for supply chain automation.

The company’s unloading robots combine generative AI and machine-learning algorithms with sensors, cameras, and machine-vision software to navigate new environments on day one and improve performance over time. Much of the company’s hardware is adapted from industrial partners. You may recognize the arm, for instance, from car manufacturing lines — though you may not have seen it in bright pickle-green.

The company is already working with customers like UPS, Ryobi Tools, and Yusen Logistics to take a load off warehouse workers, freeing them to solve other supply chain bottlenecks in the process.

“Humans are really good edge-case problem solvers, and robots are not,” Paluska says. “How can the robot, which is really good at the brute force, repetitive tasks, interact with humans to solve more problems? Human bodies and minds are so adaptable, the way we sense and respond to the environment is so adaptable, and robots aren’t going to replace that anytime soon. But there’s so much drudgery we can get rid of.”

Finding problems for robots

Meyer and Eisenstein majored in computer science and electrical engineering at MIT, but they didn’t work together until after graduation, when Meyer started the technology consultancy Leaf Labs, which specializes in building embedded computer systems for things like robots, cars, and satellites.

“A bunch of friends from MIT ran that shop,” Meyer recalls, noting it’s still running today. “Ari worked there, Dan consulted there, and we worked on some big projects. We were the primary software and digital design team behind Project Ara, a smartphone for Google, and we worked on a bunch of interesting government projects. It was really a lifestyle company for MIT kids. But 10 years go by, and we thought, ‘We didn’t get into this to do consulting. We got into this to do robots.’”

When Meyer graduated in 2009, problems like robot dexterity seemed insurmountable. By 2018, the rise of algorithmic approaches like neural networks had brought huge advances to robotic manipulation and navigation.

To figure out what problem to solve with robots, the founders talked to people in industries as diverse as agriculture, food prep, and hospitality. At some point, they started visiting logistics warehouses, bringing a stopwatch to see how long it took workers to complete different tasks.

“In 2018, we went to a UPS warehouse and watched 15 guys unloading trucks during a winter night shift,” Meyer recalls. “We spoke to everyone, and not a single person had worked there for more than 90 days. We asked, ‘Why not?’ They laughed at us. They said, ‘Have you tried to do this job before?’”

It turns out warehouse turnover is one of the industry’s biggest problems, limiting productivity as managers constantly grapple with hiring, onboarding, and training.

The founders raised a seed funding round and built robots that could sort boxes because it was an easier problem that allowed them to work with technology like grippers and barcode scanners. Their robots eventually worked, but the company wasn’t growing fast enough to be profitable. Worse yet, the founders were having trouble raising money.

“We were desperately low on funds,” Meyer recalls. “So we thought, ‘Why spend our last dollar on a warm-up task?’”

With money dwindling, the founders built a proof-of-concept robot that could unload trucks reliably for about 20 seconds at a time and posted a video of it on YouTube. Hundreds of potential customers reached out. The interest was enough to get investors back on board to keep the company alive.

The company piloted its first unloading system for a year with a customer in the desert of California, sparing human workers from unloading shipping containers that can reach temperatures up to 130 degrees in the summer. It has since scaled deployments with multiple customers and gained traction among third-party logistics centers across the U.S.

The company’s robotic arm is made by the German industrial robotics giant KUKA. The robots are mounted on a custom mobile base with an onboard computing systems so they can navigate to docks and adjust their positions inside trailers autonomously while lifting. The end of each arm features a suction gripper that clings to packages and moves them to the onboard conveyor belt.

The company’s robots can pick up boxes ranging in size from 5-inch cubes to 24-by-30 inch boxes. The robots can unload anywhere from 400 to 1,500 cases per hour depending on size and weight. The company fine tunes pre-trained generative AI models and uses a number of smaller models to ensure the robot runs smoothly in every setting.

The company is also developing a software platform it can integrate with third-party hardware, from humanoid robots to autonomous forklifts.

“Our immediate product roadmap is load and unload,” Meyer says. “But we’re also hoping to connect these third-party platforms. Other companies are also trying to connect robots. What does it mean for the robot unloading a truck to talk to the robot palletizing, or for the forklift to talk to the inventory drone? Can they do the job faster? I think there’s a big network coming in which we need to orchestrate the robots and the automation across the entire supply chain, from the mines to the factories to your front door.”

“Why not us?”

The Pickle Robot Company employs about 130 people in its office in Charlestown, Massachusetts, where a standard — if green — office gives way to a warehouse where its robots can be seen loading boxes onto conveyor belts alongside human workers and manufacturing lines.

This summer, Pickle will be ramping up production of a new version of its system, with further plans to begin designing a two-armed robot sometime after that.

“My supervisor at Leaf Labs once told me ‘No one knows what they’re doing, so why not us?’” Eisenstein says. “I carry that with me all the time. I’ve been very lucky to be able to work with so many talented, experienced people in my career. They all bring their own skill sets and understanding. That’s a massive opportunity — and it’s the only way something as hard as what we’re doing is going to work.”

Moving forward, the company sees many other robot-shaped problems for its machines.

“We didn’t start out by saying, ‘Let’s load and unload a truck,’” Meyers says. “We said, ‘What does it take to make a great robot business?’ Unloading trucks is the first chapter. Now we’ve built a platform to make the next robot that helps with more jobs, starting in logistics but then ultimately in manufacturing, retail, and hopefully the entire supply chain.”

Nature Climate Change, Published online: 05 December 2025; doi:10.1038/s41558-025-02511-x

We consider potential non-permanence of carbon removal not as an obstacle but as a feature to focus on the compensation for the short-term warming of methane emissions. This could re-open climate finance for nature-based solutions and provide an immediate reduction in temperature stress.

Nature Climate Change, Published online: 05 December 2025; doi:10.1038/s41558-025-02502-y

Decarbonization of the tourism sector faces challenges of structural lock-ins. This Comment challenges the conventional narratives of green tourism and emphasizes to practice more transformative eco-friendly solutions rather than to consume less, with ecotourism as a promising alternative to encourage more low-carbon behaviour in daily life.

Nature Climate Change, Published online: 05 December 2025; doi:10.1038/s41558-025-02517-5

Recent United Nations policymaking on international emissions trading fails to reconcile longstanding flaws that could jeopardize the integrity of these programmes. We call for urgent action by policymakers to safeguard the future of the Paris Agreement.

Nature Climate Change, Published online: 05 December 2025; doi:10.1038/s41558-025-02487-8

Methane emissions have a large short-term impact on temperature, which can be potentially offset by nature-based solutions that provide temporary carbon storage. This research demonstrates such matching could minimize intertemporal welfare trade-offs and avoid various risks for permanent removal.

The European Commission (EC) is considering a “Digital Omnibus” package that would substantially rewrite EU privacy law, particularly the landmark General Data Protection Regulation (GDPR). It’s not a done deal, and it shouldn’t be.

The GDPR is the most comprehensive model for privacy legislation around the world. While it is far from perfect and suffers from uneven enforcement, complexities and certain administrative burdens, the omnibus package is full of bad and confusing ideas that, on balance, will significantly weaken privacy protections for users in the name of cutting red tape.

It contains at least one good idea: improving consent rules so users can automatically set consent preferences that will apply across all sites. But much as we love limiting cookie fatigue, it’s not worth the price users will pay if the rest of the proposal is adopted. The EC needs to go back to the drawing board if it wants to achieve the goal of simplifying EU regulations without gutting user privacy.

Let’s break it down. 

 Changing What Constitutes Personal Data 

 The digital package is part of a larger Simplification Agenda to reduce compliance costs and administrative burdens for businesses, echoing the Draghi Report’s call to boost productivity and support innovation. Businesses have been complaining about GDPR red tape since its inception, and new rules are supposed to make compliance easier and turbocharge the development of AI in the EU. Simplification is framed as a precondition for firms to scale up in the EU, ironically targeting laws that were also argued to promote innovation in Europe. It might also stave off tariffs the U.S. has threatened to levy, thanks in part to heavy lobbying from Meta and tech lobbying groups.  

 The most striking proposal seeks to narrow the definition of personal data, the very basis of the GDPR. Today, information counts as personal data if someone can reasonably identify a person from it, whether directly or by combining it with other information.  

 The proposal jettisons this relatively simple test in favor of a variable one: whether data is “personal” depends on what a specific entity says it can reasonably do or is likely to do with it. This selectively restates part of a recent ruling by the EU Court of Justice but ignores the multiple other cases that have considered the issue. 

 This structural move toward entity specific standards will create massive legal and practical confusion, as the same data could be treated as personal for some actors but not for others. It also creates a path for companies to avoid established GDPR obligations via operational restructuring to separate identifiers from other information—a change in paperwork rather than in actual identifiability. What’s more, it will be up to the Commission, a political executive body, to define what counts as unidentifiable pseudonymized data for certain entities.

Privileging AI 

In the name of facilitating AI innovation, which often relies on large datasets in which sensitive data may residually appear, the digital package treats AI development as a “legitimate interest,” which gives AI companies a broad legal basis to process personal data, unless individuals actively object. The proposals gesture towards organisational and technical safeguards but leave companies broad discretion.  

 Another amendment would create a new exemption that allows even sensitive personal data to be used for AI systems under some circumstances. This is not a blanket permission:  “organisational and technical measures” must be taken to avoid collecting or processing such data, and proportionate efforts must be taken to remove them from AI models or training sets where they appear. However, it is unclear what will count as an appropriate or proportionate measures.

Taken together with the new personal data test, these AI privileges mean that core data protection rights, which are meant to apply uniformly, are likely to vary in practice depending on a company’s technological and commercial goals.  

And it means that AI systems may be allowed to process sensitive data even though non-AI systems that could pose equal or lower risks are not allowed to handle it. 

A Broad Reform Beyond the GDPR

There are additional adjustments, many of them troubling, such as changes to rules on automated-decision making (making it easier for companies to claim it’s needed for a service or contract), reduced transparency requirements (less explanation about how users’ data are used), and revised data access rights (supposed to tackle abusive requests). An extensive analysis by NGO noyb can be found here.  

Moreover, the digital package reaches well beyond the GDPR, aiming to streamline Europe’s digital regulatory rulebook, including the e-Privacy Directive, cybersecurity rules, the AI Act and the Data Act. The Commission also launched “reality checks” of other core legislation, which suggests it is eyeing other mandates.

Browser Signals and Cookie Fatigue

There is one proposal in the Digital Omnibus that actually could simplify something important to users: requiring online interfaces to respect automated consent signals, allowing users to automatically reject consent across all websites instead of clicking through cookie popups on each. Cookie popups are often designed with “dark patterns” that make rejecting data sharing harder than accepting it. Automated signals can address cookie banner fatigue and make it easier for people to exercise their privacy rights. 

While this proposal is a step forward, the devil is in the details: First, the exact format of the automated consent signal will be determined by technical standards organizations where Big Tech companies have historically lobbied for standards that work in their favor. The amendments should therefore define minimum protections that cannot be weakened later. 

Second, the provision takes the important step of requiring web browsers to make it easy for users sending this automated consent signal, so they can opt-out without installing a browser add-on. 

However, mobile operating systems are excluded from this latter requirement, which is a significant oversight. People deserve the same privacy rights on websites and mobile apps. 

Finally, exempting media service providers altogether creates a loophole that lets them keep using tedious or deceptive banners to get consent for data sharing. A media service’s harvesting of user information on its website to track its customers is distinct from news gathering, which should be protected. 

A Muddled Legal Landscape

The Commission’s use of the "Omnibus" process is meant to streamline lawmaking by bundling multiple changes. An earlier proposal kept the GDPR intact, focusing on easing the record-keeping obligation for smaller businesses—a far less contentious measure. The new digital package instead moves forward with thinner evidence than a substantive structural reform would require, violating basic Better Regulation principles, such as coherence and proportionality.

The result is the opposite of  “simple.” The proposed delay of the high-risk requirements under the AI Act to late 2027—part of the omnibus package—illustrates this: Businesses will face a muddled legal landscape as they must comply with rules that may soon be paused and later revived again. This sounds like "complification” rather than simplification.

The Digital Package Is Not a Done Deal

Evaluating existing legislation is part of a sensible legislative cycle and clarifying and simplifying complex process and practices is not a bad idea. Unfortunately, the digital package misses the mark by making processes even more complex, at the expense of personal data protection. 

Simplification doesn't require tossing out digital rights. The EC should keep that in mind as it launches its reality check of core legislation such as the Digital Services Act and Digital Markets Act, where tidying up can too easily drift into a verschlimmbessern, the kind of well-meant fix that ends up resembling the infamous ecce homo restoration. 

Around 25 million Americans have rare genetic diseases, and many of them struggle with not only a lack of effective treatments, but also a lack of good information about their disease. Clinicians may not know what causes a patient’s symptoms, know how their disease will progress, or even have a clear diagnosis. Researchers have looked to the human genome for answers, and many disease-causing genetic mutations have been identified, but as many as 70 percent of patients still lack a clear genetic explanation.

In a paper published in Molecular Cell on Nov. 7, Whitehead Institute for Biomedical Research member Iain Cheeseman, graduate student Jimmy Ly, and colleagues propose that researchers and clinicians may be able to get more information from patients’ genomes by looking at them in a different way.

The common wisdom is that each gene codes for one protein. Someone studying whether a patient has a mutation or version of a gene that contributes to their disease will therefore look for mutations that affect the “known” protein product of that gene. However, Cheeseman and others are finding that the majority of genes code for more than one protein. That means that a mutation that might seem insignificant because it does not appear to affect the known protein could nonetheless alter a different protein made by the same gene. Now, Cheeseman and Ly have shown that mutations affecting one or multiple proteins from the same gene can contribute differently to disease.

In their paper, the researchers first share what they have learned about how cells make use of the ability to generate different versions of proteins from the same gene. Then, they examine how mutations that affect these proteins contribute to disease. Through a collaboration with co-author Mark Fleming, the pathologist-in-chief at Boston Children’s Hospital, they provide two case studies of patients with atypical presentations of a rare anemia linked to mutations that selectively affect only one of two proteins produced by the gene implicated in the disease.

“We hope this work demonstrates the importance of considering whether a gene of interest makes multiple versions of a protein, and what the role of each version is in health and disease,” Ly says. “This information could lead to better understanding of the biology of disease, better diagnostics, and perhaps one day to tailored therapies to treat these diseases.”

Cells have several ways to make different versions of a protein, but the variation that Cheeseman and Ly study happens during protein production from genetic code. Cellular machines build each protein according to the instructions within a genetic sequence that begins at a “start codon” and ends at a “stop codon.” However, some genetic sequences contain more than one start codon, many of them hiding in plain sight. If the cellular machinery skips the first start codon and detects a second one, it may build a shorter version of the protein. In other cases, the machinery may detect a section that closely resembles a start codon at a point earlier in the sequence than its typical starting place, and build a longer version of the protein.

These events may sound like mistakes: the cell’s machinery accidentally creating the wrong version of the correct protein. To the contrary, protein production from these alternate starting places is an important feature of cell biology that exists across species. When Ly traced when certain genes evolved to produce multiple proteins, he found that this is a common, robust process that has been preserved throughout evolutionary history for millions of years.

Ly shows that one function this serves is to send versions of a protein to different parts of the cell. Many proteins contain ZIP code-like sequences that tell the cell’s machinery where to deliver them so the proteins can do their jobs. Ly found many examples in which longer and shorter versions of the same protein contained different ZIP codes and ended up in different places within the cell.

In particular, Ly found many cases in which one version of a protein ended up in mitochondria, structures that provide energy to cells, while another version ended up elsewhere. Because of the mitochondria’s role in the essential process of energy production, mutations to mitochondrial genes are often implicated in disease.

Ly wondered what would happen when a disease-causing mutation eliminates one version of a protein but leaves the other intact, causing the protein to only reach one of its two intended destinations. He looked through a database containing genetic information from people with rare diseases to see if such cases existed, and found that they did. In fact, there may be tens of thousands of such cases. However, without access to the people, Ly had no way of knowing what the consequences of this were in terms of symptoms and severity of disease.

Meanwhile, Cheeseman, who is also a professor of biology at MIT, had begun working with Boston Children’s Hospital to foster collaborations between Whitehead Institute and the hospital’s researchers and clinicians to accelerate the pathway from research discovery to clinical application. Through these efforts, Cheeseman and Ly met Fleming.

One group of Fleming’s patients have a type of anemia called SIFD — sideroblastic anemia with B-cell immunodeficiency, periodic fevers, and developmental delay — that is caused by mutations to the TRNT1 gene. TRNT1 is one of the genes Ly had identified as producing a mitochondrial version of its protein and another version that ends up elsewhere: in the nucleus.

Fleming shared anonymized patient data with Ly, and Ly found two cases of interest in the genetic data. Most of the patients had mutations that impaired both versions of the protein, but one patient had a mutation that eliminated only the mitochondrial version of the protein, while another patient had a mutation that eliminated only the nuclear version.

When Ly shared his results, Fleming revealed that both of those patients had very atypical presentations of SIFD, supporting Ly’s hypothesis that mutations affecting different versions of a protein would have different consequences. The patient who only had the mitochondrial version was anemic, but developmentally normal. The patient missing the mitochondrial version of the protein did not have developmental delays or chronic anemia, but did have other immune symptoms, and was not correctly diagnosed until his 50s. There are likely other factors contributing to each patient’s exact presentation of the disease, but Ly’s work begins to unravel the mystery of their atypical symptoms.

Cheeseman and Ly want to make more clinicians aware of the prevalence of genes coding for more than one protein, so they know to check for mutations affecting any of the protein versions that could contribute to disease. For example, several TRNT1 mutations that only eliminate the shorter version of the protein are not flagged as disease-causing by current assessment tools. Cheeseman lab researchers, including Ly and graduate student Matteo Di Bernardo, are now developing a new assessment tool for clinicians, called SwissIsoform, that will identify relevant mutations that affect specific protein versions, including mutations that would otherwise be missed.

“Jimmy and Iain’s work will globally support genetic disease variant interpretation and help with connecting genetic differences to variation in disease symptoms,” Fleming says. “In fact, we have recently identified two other patients with mutations affecting only the mitochondrial versions of two other proteins, who similarly have milder symptoms than patients with mutations that affect both versions.”

Long term, the researchers hope that their discoveries could aid in understanding the molecular basis of disease and in developing new gene therapies: Once researchers understand what has gone wrong within a cell to cause disease, they are better equipped to devise a solution. More immediately, the researchers hope that their work will make a difference by providing better information to clinicians and people with rare diseases.

“As a basic researcher who doesn’t typically interact with patients, there’s something very satisfying about knowing that the work you are doing is helping specific people,” Cheeseman says. “As my lab transitions to this new focus, I’ve heard many stories from people trying to navigate a rare disease and just get answers, and that has been really motivating to us, as we work to provide new insights into the disease biology.”

Each year, faculty and researchers across the MIT School of Engineering are recognized with prestigious awards for their contributions to research, technology, society, and education. To celebrate these achievements, the school periodically highlights select honors received by members of its departments, institutes, labs, and centers. The following individuals were recognized in summer 2025:

Iwnetim Abate, the Chipman Career Development Professor and assistant professor in the Department of Materials Science and Engineering, was honored as one of MIT Technology Review’s 2025 Innovators Under 35. He was recognized for his research on sodium-ion batteries and ammonia production.

Daniel G. Anderson, the Joseph R. Mares (1924) Professor in the Department of Chemical Engineering and the Institute of Medical Engineering and Science (IMES), received the 2025 AIChE James E. Bailey Award. The award honors outstanding contributions in biological engineering and commemorates the pioneering work of James Bailey.

Regina Barzilay, the School of Engineering Distinguished Professor for AI and Health in the Department of Electrical Engineering and Computer Science (EECS), was named to Time’s AI100 2025 list, recognizing her groundbreaking work in AI and health.

Richard D. Braatz, the Edwin R. Gilliland Professor in the Department of Chemical Engineering, received the 2025 AIChE CAST Distinguished Service Award. The award recognizes exceptional service and leadership within the Computing and Systems Technology Division of AIChE.

Rodney Brooks, the Panasonic Professor of Robotics, Emeritus in the Department of Electrical Engineering and Computer Science, was elected to the National Academy of Sciences, one of the highest honors in scientific research.

Arup K. Chakraborty, the John M. Deutch (1961) Institute Professor in the Department of Chemical Engineering and IMES, received the 2025 AIChE Alpha Chi Sigma Award. This award honors outstanding accomplishments in chemical engineering research over the past decade.

Connor W. Coley, the Class of 1957 Career Development Professor and associate professor in the departments of Chemical Engineering and EECS, received the 2025 AIChE CoMSEF Young Investigator Award for Modeling and Simulation. The award recognizes outstanding research in computational molecular science and engineering. Coley was also one of 74 highly accomplished, early-career engineers selected to participate in the Grainger Foundation Frontiers of Engineering Symposium, a signature activity of the National Academy of Engineering.

Henry Corrigan-Gibbs, the Douglas Ross (1954) Career Development Professor of Software Technology and associate professor in the Department of EECS, received the Google ML and Systems Junior Faculty Award, presented to assistant professors who are leading the analysis, design and implementation of efficient, scalable, secure, and trustworthy computing systems.

Christina Delimitrou, the KDD Career Development Professor in Communications and Technology and associate professor in the Department of EECS, received the Google ML and Systems Junior Faculty Award. The award supports assistant professors advancing scalable and trustworthy computing systems for machine learning and cloud computing. Delimitrou also received the Google ML and Systems Junior Faculty Award, presented to assistant professors who are leading the analysis, design, and implementation of efficient, scalable, secure, and trustworthy computing systems.

Priya Donti, the Silverman (1968) Family Career Development Professor and assistant professor in the Department of EECS, was named to Time’s AI100 2025 list, which honors innovators reshaping the world through artificial intelligence.

Joel Emer, a professor of the practice in the Department of EECS, received the Alan D. Berenbaum Distinguished Service Award from ACM SIGARCH. He was honored for decades of mentoring and leadership in the computer architecture community.

Roger Greenwood Mark, the Distinguished Professor of Health Sciences and Technology, Emeritus in IMES, received the IEEE Biomedical Engineering Award for leadership in ECG signal processing and global dissemination of curated biomedical and clinical databases, thereby accelerating biomedical research worldwide.

Ali Jadbabaie, the JR East Professor and head of the Department of Civil and Environmental Engineering, received the 2025 Multidisciplinary University Research Initiative (MURI) award for research projects in areas of critical importance to national defense.

Yoon Kim, associate professor in the Department of EECS, received the Google ML and Systems Junior Faculty Award, presented to assistant professors who are leading the analysis, design, and implementation of efficient, scalable, secure, and trustworthy computing systems.

Mathias Kolle, an associate professor in the Department of Mechanical Engineering, received the 2025 Multidisciplinary University Research Initiative (MURI) award for research projects in areas of critical importance to national defense.

Muriel Médard, the NEC Professor of Software Science and Engineering in the Department of EECS, was elected an International Fellow of the United Kingdom's Royal Academy of Engineering. The honor recognizes exceptional contributions to engineering and technology across sectors.

Pablo Parrilo, the Joseph F. and Nancy P. Keithley Professor in Electrical Engineering in the Department of EECS, received the 2025 INFORMS Computing Society Prize. The award honors outstanding contributions at the interface of computing and operations research. Parrilo was recognized for pioneering work on accelerating gradient descent through stepsize hedging, introducing concepts such as Silver Stepsizes and recursive gluing.

Nidhi Seethapathi, the Frederick A. (1971) and Carole J. Middleton Career Development Professor of Neuroscience and assistant professor in the Department of EECS, was named to MIT Technology Review’s “2025 Innovators Under 35” list. The honor celebrates early-career scientists and entrepreneurs driving real-world impact.

Justin Solomon, an associate professor in the Department of EECS, was named a 2025 Schmidt Science Polymath. The award supports novel, early-stage research across disciplines, including acoustics and climate simulation.

Martin Staadecker, a research assistant in the Sustainable Supply Chain Lab, received the MIT-GE Vernova Energy and Climate Alliance Technology and Policy Program Project Award. The award recognizes his work on Scope 3 emissions and sustainable supply chain practices.

Antonio Torralba, the Delta Electronics Professor and faculty head of AI+D in the Department of EECS, received the 2025 Multidisciplinary University Research Initiative (MURI) award for research projects in areas of critical importance to national defense.

Ryan Williams, a professor in the Department of EECS, received the Best Paper Award at STOC 2025 for his paper “Simulating Time With Square-Root Space,” recognized for its technical merit and originality. Williams was also selected as a Member of the Institute for Advanced Study for the 2025–26 academic year. This prestigious fellowship recognizes the significance of these scholars' work, and it is an opportunity to advance their research and exchange ideas with scholars from around the world.

Gioele Zardini, the Rudge (1948) and Nancy Allen Career Development Professor in the Department of Civil and Environmental Engineering, received the 2025 DARPA Young Faculty Award. The award supports rising stars among early-career faculty, helping them develop research ideas aligned with national security needs.