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MIT Technology Review’s 2023 Innovators Under 35 list recognized 35 researchers, engineers, entrepreneurs, and technologists from around the world. Their work covered artificial intelligence, biotechnology, medicine, climate technology, energy, robotics, materials, space, transportation, and computing. The associated TR35 Festival took place online on December 6, 2023, but the festival’s 10 featured speakers were only a subset of the complete global cohort.
This is the 2023 global list, not a regional edition. Inclusion represents editorial recognition of promising work; it does not prove that a technology is commercially successful, clinically validated, safe, or ready for mass adoption.
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What does “2023 Innovators Under 35” mean?
In this context, “2023” refers to MIT Technology Review’s global cohort for that year. The 35 honorees were selected through the publication’s Innovators Under 35 program, which recognizes young people whose technical work could influence important technologies and problems in the coming decades.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteThe program began in 1999, during MIT Technology Review’s centennial year. It initially contemplated a larger list of 100 innovators before evolving into an annual group of 35. Regional editions were added in 2010. The program now includes global and regional lists, including editions associated with places such as Europe, Japan, MENA, India, China, Korea, and Asia Pacific.
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The official program description says the recognition can include new inventions as well as creative applications of existing technology to major challenges. The honorees are not necessarily founders or company executives: the cohort includes academic researchers, software developers, engineers, scientists, and entrepreneurs.
The complete 2023 global list
The table below paraphrases the official descriptions on the 2023 global list. “Status” describes the kind of work represented, not a claim that the project has reached a particular commercial or regulatory milestone.
| Honoree | Area | What they worked on | Work type and caveat |
|---|---|---|---|
| Christina Kim | Biology and neuroscience | A technique for identifying nerve cells associated with different animal behaviors. | Research method; its significance depends on validation and application in neuroscience. |
| Danielle Mai | Biotechnology and materials | Used proteins from whooping cough to engineer a material intended to behave like human skin and muscle. | Bioengineered material; an intended biological function is not the same as clinical deployment. |
| Tetsuhiro Harimoto | Medicine and synthetic biology | Worked on “intelligent living medicines”: bacteria that could be trained to seek and attack cancer. | Experimental therapeutic platform; it should not be described as a cancer cure. |
| Pranav Rajpurkar | AI and medicine | Developed an approach for training AI to interpret medical images accurately. | Medical-AI method; clinical usefulness requires evaluation in real healthcare settings. |
| Tyler Allen | Cancer research | Built a live-imaging system to observe how tumor cells move through the body. | Research and imaging platform rather than a treatment. |
| Jiawen Li | Cardiology | Engineered a tiny device intended to help cardiologists address a common clinical problem. | Medical device concept; the list description does not establish broad clinical adoption. |
| Anna Blakney | RNA biotechnology | Conducted research aimed at improving RNA vaccines. | Vaccine research; this does not mean she created a specific COVID-19 vaccine. |
| Courtney Young | Gene therapy | Worked on changing patient DNA to restore production of necessary proteins. | Genetic medicine research; safety, efficacy, and approval require separate evidence. |
| Julia Joung | Genomics | Worked on genome-scale screening. | Discovery and screening platform with applications that still require biological validation. |
| Tongchao Liu | Energy storage | Developed lithium batteries designed to be rechargeable more times than earlier versions. | Battery research; durability claims should not be read as proof of mass-market deployment. |
| Catherine De Wolf | Construction and climate technology | Applied AI to reduce emissions and material waste in construction. | Software and industrial application; real-world impact depends on adoption across projects. |
| Yayuan Liu | Carbon capture | Developed modular carbon-capture devices that do not depend on heat. | Hardware and chemical-process research; efficiency and lifecycle performance require project-level assessment. |
| Peter Godart | Materials and manufacturing | Created a water-based chemical process for separating aluminum. | Industrial-process innovation whose commercial value depends on scale and economics. |
| Shivani Torres | Mining and climate technology | Led development of a robot that uses jet-engine heat to pulverize rock. | Industrial robotics and materials processing; deployment and energy performance remain key questions. |
| Young Suk Jo | Alternative fuels | Developed systems using ammonia as fuel for trucks and ships. | Transport-fuel technology; ammonia is not automatically emissions-free because lifecycle emissions depend on production and use. |
| Stafford Sheehan | Carbon utilization | Converted existing carbon dioxide into a commercially useful product. | Chemical process; usefulness depends on energy inputs, scale, and market economics. |
| Sivaranjani Seetharaman | Electricity systems | Built models to evaluate how power systems respond to sharply increasing demand. | Grid-planning and analysis tool rather than a power-generation technology. |
| Quansan Yang | Semiconductors | Worked on computer chips designed to be more environmentally friendly. | Hardware and materials research; environmental benefits depend on manufacturing and lifecycle data. |
| Alhussein Fawzi | AI and computing | Used game-playing AI to accelerate fundamental computational tasks. | Algorithmic research with potential scientific and engineering applications. |
| Sharon Li | Machine-learning safety | Developed an early out-of-distribution-detection algorithm for deep neural networks. | Reliability method; it addresses a class of failures but does not prove that AI systems are safe. |
| Lerrel Pinto | Robotics and machine learning | Created a large robotics dataset by having robots generate and label their own training data; the official description qualified it as the world’s largest at the time. | Data and training infrastructure; the “largest” claim is time-specific. |
| Irene Solaiman | AI policy and software | Developed a new approach to releasing GPT-2, an earlier predecessor to ChatGPT. | Model-release and governance work, not the creation of ChatGPT. |
| Renee Zhao | Robotics | Developed miniature robots capable of more flexible movements. | Prototype robotics research with possible applications across small-scale machines. |
| Daniel Omeiza | Autonomous driving | Worked on explainability for self-driving systems. | Safety and interpretability research; explanation quality does not alone guarantee autonomous-driving safety. |
| Connor Coley | AI and chemistry | Developed open-source AI software for discovering and synthesizing molecules. | Scientific software and computational chemistry platform. |
| Sasha Luccioni | AI and climate | Developed methods for estimating and measuring the carbon footprint of AI language models. | Measurement and accountability work; results vary with model, hardware, energy mix, and accounting method. |
| Victoria Webster-Wood | Robotics and biomaterials | Built robots from biological materials to make robotics more environmentally sustainable. | Early-stage biohybrid robotics research. |
| Bharath Kannan | Quantum computing | Developed methods intended to reduce error rates in quantum computing. | Quantum-computing research; error reduction is not equivalent to fault-tolerant quantum computing. |
| Forrest Meyen | Space | Worked to make space exploration more affordable and support the space-mining industry. | Space technology and commercialization effort; the broader industry remains developing. |
| Awais Ahmed | Earth observation | Used hyperspectral orbital imaging to capture information across more than 150 wavelengths. | Satellite-imaging technology with uses in analysis of Earth and its resources. |
| Richard Zhang | Computer vision and generative AI | Developed visual-similarity algorithms underlying image-generating AI models. | Foundational computer-vision work; this does not mean he invented generative AI as a whole. |
| Yatish Turakhia | Computational genomics | Helped develop UShER, software used to track COVID-19 variants. | Public-health surveillance software, not a vaccine, diagnostic, or treatment. |
| Monique McClain | Aerospace manufacturing | Developed a route for producing propellants through 3D printing. | Manufacturing and propulsion research; aerospace qualification is a separate step. |
| Nicole Black | Biomedical materials | 3D-printed a material intended to function like a healthy eardrum. | Medical-material prototype or research platform; clinical use requires testing and approval. |
| David Mackanic | Batteries and materials | Developed batteries that can bend and flex. | Flexible energy-storage research with potential uses in wearable or unconventional devices. |
The major technology themes of the 2023 cohort
AI reliability, measurement, and scientific use
The AI-related honorees were not focused only on making models larger or more capable. The list included out-of-distribution detection, explainability for self-driving systems, molecular discovery, medical-image interpretation, game-playing systems for computation, image-generation foundations, robotics data, and measurement of language-model carbon emissions.
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That mix suggests a 2023 technology landscape increasingly concerned with whether AI can be trusted, understood, measured, and applied to science and medicine. It is an interpretation of the projects represented on the official list, not an official statement that the cohort had one shared agenda.
Climate innovation across industry
Climate work appeared at several layers of the industrial system: carbon capture, carbon utilization, lower-waste construction, aluminum processing, sustainable chips, alternative fuels, electricity-grid modeling, and lower-impact robotics. The spread matters because it shows decarbonization as an infrastructure, manufacturing, software, and materials problem—not only a renewable-energy problem.
Biology as an engineering platform
Several honorees treated biology as something that can be programmed, screened, redesigned, or used to manufacture useful structures. Their work included RNA vaccines, engineered proteins, living medicines, gene correction, genome-scale screening, biological robot materials, and computational genomics.
These projects also illustrate why biotechnology should not be treated as a single maturity category. A screening method, a gene-therapy approach, a living medicine, and a bioengineered material face different validation, safety, manufacturing, and regulatory paths.
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Physical systems still mattered
Although generative AI dominated much of the technology conversation in 2023, the global cohort also included flexible batteries, 3D-printed aerospace propellant, eardrum-like materials, tiny medical devices, hyperspectral satellites, ammonia-fueled transport, quantum hardware, and biologically based robots.
The list therefore was not an AI-only awards program. It recognized innovations in physical systems that may take longer to commercialize but could affect energy, health, transportation, manufacturing, and space exploration.
Who appeared at the 2023 TR35 Festival?
The TR35 Festival 2023 was held online on Wednesday, December 6, 2023. Its agenda focused on the path from idea to implementation, including what makes an innovator, accelerating ideas, failure, scaling impact, and the work required beyond the original idea.
Ten members of the global cohort were highlighted as speakers:
- Lerrel Pinto
- Sharon Li
- Anna Blakney
- Richard Zhang
- Sivaranjani Seetharaman
- Renee Zhao
- Nicole Black
- David Mackanic
- Young Suk Jo
- Yatish Turakhia
The speaker list should not be mistaken for the complete set of 35 honorees.
How are Innovators Under 35 candidates selected?
The program’s current description says that more than 500 people are nominated each year. Editors select the most promising 100 semifinalists, whose work is evaluated by judges with expertise in areas such as AI, biotechnology, software, energy, and materials. Editors then select the final 35.
This is an editorial recognition process involving expert judging, not a conventional peer-reviewed scientific ranking. The published general methodology should not automatically be presented as a detailed, 2023-specific statistical procedure. It also means the nominee pool is not necessarily a representative sample of every young innovator worldwide.
Global versus regional lists
The global 2023 list is distinct from regional editions. A person recognized in a regional program may be considered for the global list, but winning or appearing on a regional 2023 list does not automatically mean that person was one of the 35 global honorees.
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What the recognition does—and does not—mean
Some entries describe software or methods that may be shared relatively quickly, while others involve medical devices, batteries, industrial processes, biological therapies, or space systems that require years of validation, manufacturing, regulation, or infrastructure development. The cohort intentionally mixes these stages.
Inclusion means MIT Technology Review judged the work promising and consequential enough for recognition. It does not independently establish:
- clinical efficacy or regulatory approval;
- commercial success or mass adoption;
- technical superiority over competing approaches;
- long-term safety;
- that a prototype will become a viable product; or
- that every honoree remains under 35 in 2026.
For example, Tetsuhiro Harimoto’s bacteria-based work should not be called a cancer cure; Young Suk Jo’s ammonia systems should not automatically be labeled emissions-free; and Yatish Turakhia’s UShER work should not be described as a COVID-19 vaccine or treatment.
Why the 2023 list matters
Viewed retrospectively, the cohort captures several priorities of technology in 2023. Generative AI was entering the mainstream, but researchers were also working on model reliability, release practices, interpretability, and environmental measurement. Climate innovation was expanding into construction, semiconductors, industrial chemistry, mining, shipping, and grid planning. Biotechnology was becoming more programmable and computational, while physical innovations in batteries, satellites, robotics, and medical materials remained central.
The strongest common thread is not one specific technology. It is the attempt to turn difficult research problems into usable systems: more interpretable AI, more efficient industrial processes, programmable biology, adaptable machines, and tools for managing complex infrastructure.
For the official descriptions, program history, and event context, see the Innovators Under 35 About page, the program’s selection overview, and the 2023 festival agenda.
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