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    MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16

    For the first time, MIT sent an organized engagement to the global Conference of the Parties for the Convention on Biological Diversity, which this year was held Oct. 21 to Nov. 1 in Cali, Colombia.The 10 delegates to COP16 included faculty, researchers, and students from the MIT Environmental Solutions Initiative (ESI), the Department of Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL), the Department of Urban Studies and Planning (DUSP), the Institute for Data, Systems, and Society (IDSS), and the Center for Sustainability Science and Strategy.In previous years, MIT faculty had participated sporadically in the discussions. This organized engagement, led by the ESI, is significant because it brought representatives from many of the groups working on biodiversity across the Institute; showcased the breadth of MIT’s research in more than 15 events including panels, roundtables, and keynote presentations across the Blue and Green Zones of the conference (with the Blue Zone representing the primary venue for the official negotiations and discussions and the Green Zone representing public events); and created an experiential learning opportunity for students who followed specific topics in the negotiations and throughout side events.The conference also gathered attendees from governments, nongovernmental organizations, businesses, other academic institutions, and practitioners focused on stopping global biodiversity loss and advancing the 23 goals of the Kunming-Montreal Global Biodiversity Framework (KMGBF), an international agreement adopted in 2022 to guide global efforts to protect and restore biodiversity through 2030.MIT’s involvement was particularly pronounced when addressing goals related to building coalitions of sub-national governments (targets 11, 12, 14); technology and AI for biodiversity conservation (targets 20 and 21); shaping equitable markets (targets 3, 11, and 19); and informing an action plan for Afro-descendant communities (targets 3, 10, and 22).Building coalitions of sub-national governmentsThe ESI’s Natural Climate Solutions (NCS) Program was able to support two separate coalitions of Latin American cities, namely the Coalition of Cities Against Illicit Economies in the Biogeographic Chocó Region and the Colombian Amazonian Cities coalition, who successfully signed declarations to advance specific targets of the KMGBF (the aforementioned targets 11, 12, 14).This was accomplished through roundtables and discussions where team members — including Marcela Angel, research program director at the MIT ESI; Angelica Mayolo, ESI Martin Luther King Fellow 2023-25; and Silvia Duque and Hannah Leung, MIT Master’s in City Planning students — presented a set of multi-scale actions including transnational strategies, recommendations to strengthen local and regional institutions, and community-based actions to promote the conservation of the Biogeographic Chocó as an ecological corridor.“There is an urgent need to deepen the relationship between academia and local governments of cities located in biodiversity hotspots,” said Angel. “Given the scale and unique conditions of Amazonian cities, pilot research projects present an opportunity to test and generate a proof of concept. These could generate catalytic information needed to scale up climate adaptation and conservation efforts in socially and ecologically sensitive contexts.”ESI’s research also provided key inputs for the creation of the Fund for the Biogeographic Chocó Region, a multi-donor fund launched within the framework of COP16 by a coalition composed of Colombia, Ecuador, Panamá, and Costa Rica. The fund aims to support biodiversity conservation, ecosystem restoration, climate change mitigation and adaptation, and sustainable development efforts across the region.Technology and AI for biodiversity conservationData, technology, and artificial intelligence are playing an increasing role in how we understand biodiversity and ecosystem change globally. Professor Sara Beery’s research group at MIT focuses on this intersection, developing AI methods that enable species and environmental monitoring at previously unprecedented spatial, temporal, and taxonomic scales.During the International Union of Biological Diversity Science-Policy Forum, the high-level COP16 segment focused on outlining recommendations from scientific and academic community, Beery spoke on a panel alongside María Cecilia Londoño, scientific information manager of the Humboldt Institute and co-chair of the Global Biodiversity Observations Network, and Josh Tewksbury, director of the Smithsonian Tropical Research Institute, among others, about how these technological advancements will help humanity achieve our biodiversity targets. The panel emphasized that AI innovation was needed, but with emphasis on direct human-AI partnership, AI capacity building, and the need for data and AI policy to ensure equity of access and benefit from these technologies.As a direct outcome of the session, for the first time, AI was emphasized in the statement on behalf of science and academia delivered by Hernando Garcia, director of the Humboldt Institute, and David Skorton, secretary general of the Smithsonian Institute, to the high-level segment of the COP16.That statement read, “To effectively address current and future challenges, urgent action is required in equity, governance, valuation, infrastructure, decolonization and policy frameworks around biodiversity data and artificial intelligence.”Beery also organized a panel at the GEOBON pavilion in the Blue Zone on Scaling Biodiversity Monitoring with AI, which brought together global leaders from AI research, infrastructure development, capacity and community building, and policy and regulation. The panel was initiated and experts selected from the participants at the recent Aspen Global Change Institute Workshop on Overcoming Barriers to Impact in AI for Biodiversity, co-organized by Beery.Shaping equitable marketsIn a side event co-hosted by the ESI with CAF-Development Bank of Latin America, researchers from ESI’s Natural Climate Solutions Program — including Marcela Angel; Angelica Mayolo; Jimena Muzio, ESI research associate; and Martin Perez Lara, ESI research affiliate and director for Forest Climate Solutions Impact and Monitoring at World Wide Fund for Nature of the U.S. — presented results of a study titled “Voluntary Carbon Markets for Social Impact: Comprehensive Assessment of the Role of Indigenous Peoples and Local Communities (IPLC) in Carbon Forestry Projects in Colombia.” The report highlighted the structural barriers that hinder effective participation of IPLC, and proposed a conceptual framework to assess IPLC engagement in voluntary carbon markets.Communicating these findings is important because the global carbon market has experienced a credibility crisis since 2023, influenced by critical assessments in academic literature, journalism questioning the quality of mitigation results, and persistent concerns about the engagement of private actors with IPLC. Nonetheless, carbon forestry projects have expanded rapidly in Indigenous, Afro-descendant, and local communities’ territories, and there is a need to assess the relationships between private actors and IPLC and to propose pathways for equitable participation. 

    Panelists pose at the equitable markets side event at the Latin American Pavilion in the Blue Zone.

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    The research presentation and subsequent panel with representatives of the association for Carbon Project Developers in Colombia Asocarbono, Fondo Acción, and CAF further discussed recommendations for all actors in the value chain of carbon certificates — including those focused on promoting equitable benefit-sharing and safeguarding compliance, increased accountability, enhanced governance structures, strengthened institutionality, and regulatory frameworks  — necessary to create an inclusive and transparent market.Informing an action plan for Afro-descendant communitiesThe Afro-Interamerican Forum on Climate Change (AIFCC), an international network working to highlight the critical role of Afro-descendant peoples in global climate action, was also present at COP16.At the Afro Summit, Mayolo presented key recommendations prepared collectively by the members of AIFCC to the technical secretariat of the Convention on Biological Diversity (CBD). The recommendations emphasize:creating financial tools for conservation and supporting Afro-descendant land rights;including a credit guarantee fund for countries that recognize Afro-descendant collective land titling and research on their contributions to biodiversity conservation;calling for increased representation of Afro-descendant communities in international policy forums;capacity-building for local governments; andstrategies for inclusive growth in green business and energy transition.These actions aim to promote inclusive and sustainable development for Afro-descendant populations.“Attending COP16 with a large group from MIT contributing knowledge and informed perspectives at 15 separate events was a privilege and honor,” says MIT ESI Director John E. Fernández. “This demonstrates the value of the ESI as a powerful research and convening body at MIT. Science is telling us unequivocally that climate change and biodiversity loss are the two greatest challenges that we face as a species and a planet. MIT has the capacity, expertise, and passion to address not only the former, but also the latter, and the ESI is committed to facilitating the very best contributions across the institute for the critical years that are ahead of us.”A fuller overview of the conference is available via The MIT Environmental Solutions Initiative’s Primer of COP16. More

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    Advancing urban tree monitoring with AI-powered digital twins

    The Irish philosopher George Berkely, best known for his theory of immaterialism, once famously mused, “If a tree falls in a forest and no one is around to hear it, does it make a sound?”What about AI-generated trees? They probably wouldn’t make a sound, but they will be critical nonetheless for applications such as adaptation of urban flora to climate change. To that end, the novel “Tree-D Fusion” system developed by researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Google, and Purdue University merges AI and tree-growth models with Google’s Auto Arborist data to create accurate 3D models of existing urban trees. The project has produced the first-ever large-scale database of 600,000 environmentally aware, simulation-ready tree models across North America.“We’re bridging decades of forestry science with modern AI capabilities,” says Sara Beery, MIT electrical engineering and computer science (EECS) assistant professor, MIT CSAIL principal investigator, and a co-author on a new paper about Tree-D Fusion. “This allows us to not just identify trees in cities, but to predict how they’ll grow and impact their surroundings over time. We’re not ignoring the past 30 years of work in understanding how to build these 3D synthetic models; instead, we’re using AI to make this existing knowledge more useful across a broader set of individual trees in cities around North America, and eventually the globe.”Tree-D Fusion builds on previous urban forest monitoring efforts that used Google Street View data, but branches it forward by generating complete 3D models from single images. While earlier attempts at tree modeling were limited to specific neighborhoods, or struggled with accuracy at scale, Tree-D Fusion can create detailed models that include typically hidden features, such as the back side of trees that aren’t visible in street-view photos.The technology’s practical applications extend far beyond mere observation. City planners could use Tree-D Fusion to one day peer into the future, anticipating where growing branches might tangle with power lines, or identifying neighborhoods where strategic tree placement could maximize cooling effects and air quality improvements. These predictive capabilities, the team says, could change urban forest management from reactive maintenance to proactive planning.A tree grows in Brooklyn (and many other places)The researchers took a hybrid approach to their method, using deep learning to create a 3D envelope of each tree’s shape, then using traditional procedural models to simulate realistic branch and leaf patterns based on the tree’s genus. This combo helped the model predict how trees would grow under different environmental conditions and climate scenarios, such as different possible local temperatures and varying access to groundwater.Now, as cities worldwide grapple with rising temperatures, this research offers a new window into the future of urban forests. In a collaboration with MIT’s Senseable City Lab, the Purdue University and Google team is embarking on a global study that re-imagines trees as living climate shields. Their digital modeling system captures the intricate dance of shade patterns throughout the seasons, revealing how strategic urban forestry could hopefully change sweltering city blocks into more naturally cooled neighborhoods.“Every time a street mapping vehicle passes through a city now, we’re not just taking snapshots — we’re watching these urban forests evolve in real-time,” says Beery. “This continuous monitoring creates a living digital forest that mirrors its physical counterpart, offering cities a powerful lens to observe how environmental stresses shape tree health and growth patterns across their urban landscape.”AI-based tree modeling has emerged as an ally in the quest for environmental justice: By mapping urban tree canopy in unprecedented detail, a sister project from the Google AI for Nature team has helped uncover disparities in green space access across different socioeconomic areas. “We’re not just studying urban forests — we’re trying to cultivate more equity,” says Beery. The team is now working closely with ecologists and tree health experts to refine these models, ensuring that as cities expand their green canopies, the benefits branch out to all residents equally.It’s a breezeWhile Tree-D fusion marks some major “growth” in the field, trees can be uniquely challenging for computer vision systems. Unlike the rigid structures of buildings or vehicles that current 3D modeling techniques handle well, trees are nature’s shape-shifters — swaying in the wind, interweaving branches with neighbors, and constantly changing their form as they grow. The Tree-D fusion models are “simulation-ready” in that they can estimate the shape of the trees in the future, depending on the environmental conditions.“What makes this work exciting is how it pushes us to rethink fundamental assumptions in computer vision,” says Beery. “While 3D scene understanding techniques like photogrammetry or NeRF [neural radiance fields] excel at capturing static objects, trees demand new approaches that can account for their dynamic nature, where even a gentle breeze can dramatically alter their structure from moment to moment.”The team’s approach of creating rough structural envelopes that approximate each tree’s form has proven remarkably effective, but certain issues remain unsolved. Perhaps the most vexing is the “entangled tree problem;” when neighboring trees grow into each other, their intertwined branches create a puzzle that no current AI system can fully unravel.The scientists see their dataset as a springboard for future innovations in computer vision, and they’re already exploring applications beyond street view imagery, looking to extend their approach to platforms like iNaturalist and wildlife camera traps.“This marks just the beginning for Tree-D Fusion,” says Jae Joong Lee, a Purdue University PhD student who developed, implemented and deployed the Tree-D-Fusion algorithm. “Together with my collaborators, I envision expanding the platform’s capabilities to a planetary scale. Our goal is to use AI-driven insights in service of natural ecosystems — supporting biodiversity, promoting global sustainability, and ultimately, benefiting the health of our entire planet.”Beery and Lee’s co-authors are Jonathan Huang, Scaled Foundations head of AI (formerly of Google); and four others from Purdue University: PhD students Jae Joong Lee and Bosheng Li, Professor and Dean’s Chair of Remote Sensing Songlin Fei, Assistant Professor Raymond Yeh, and Professor and Associate Head of Computer Science Bedrich Benes. Their work is based on efforts supported by the United States Department of Agriculture’s (USDA) Natural Resources Conservation Service and is directly supported by the USDA’s National Institute of Food and Agriculture. The researchers presented their findings at the European Conference on Computer Vision this month.  More

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    Nanoscale transistors could enable more efficient electronics

    Silicon transistors, which are used to amplify and switch signals, are a critical component in most electronic devices, from smartphones to automobiles. But silicon semiconductor technology is held back by a fundamental physical limit that prevents transistors from operating below a certain voltage.This limit, known as “Boltzmann tyranny,” hinders the energy efficiency of computers and other electronics, especially with the rapid development of artificial intelligence technologies that demand faster computation.In an effort to overcome this fundamental limit of silicon, MIT researchers fabricated a different type of three-dimensional transistor using a unique set of ultrathin semiconductor materials.Their devices, featuring vertical nanowires only a few nanometers wide, can deliver performance comparable to state-of-the-art silicon transistors while operating efficiently at much lower voltages than conventional devices.“This is a technology with the potential to replace silicon, so you could use it with all the functions that silicon currently has, but with much better energy efficiency,” says Yanjie Shao, an MIT postdoc and lead author of a paper on the new transistors.The transistors leverage quantum mechanical properties to simultaneously achieve low-voltage operation and high performance within an area of just a few square nanometers. Their extremely small size would enable more of these 3D transistors to be packed onto a computer chip, resulting in fast, powerful electronics that are also more energy-efficient.“With conventional physics, there is only so far you can go. The work of Yanjie shows that we can do better than that, but we have to use different physics. There are many challenges yet to be overcome for this approach to be commercial in the future, but conceptually, it really is a breakthrough,” says senior author Jesús del Alamo, the Donner Professor of Engineering in the MIT Department of Electrical Engineering and Computer Science (EECS).They are joined on the paper by Ju Li, the Tokyo Electric Power Company Professor in Nuclear Engineering and professor of materials science and engineering at MIT; EECS graduate student Hao Tang; MIT postdoc Baoming Wang; and professors Marco Pala and David Esseni of the University of Udine in Italy. The research appears today in Nature Electronics.Surpassing siliconIn electronic devices, silicon transistors often operate as switches. Applying a voltage to the transistor causes electrons to move over an energy barrier from one side to the other, switching the transistor from “off” to “on.” By switching, transistors represent binary digits to perform computation.A transistor’s switching slope reflects the sharpness of the “off” to “on” transition. The steeper the slope, the less voltage is needed to turn on the transistor and the greater its energy efficiency.But because of how electrons move across an energy barrier, Boltzmann tyranny requires a certain minimum voltage to switch the transistor at room temperature.To overcome the physical limit of silicon, the MIT researchers used a different set of semiconductor materials — gallium antimonide and indium arsenide — and designed their devices to leverage a unique phenomenon in quantum mechanics called quantum tunneling.Quantum tunneling is the ability of electrons to penetrate barriers. The researchers fabricated tunneling transistors, which leverage this property to encourage electrons to push through the energy barrier rather than going over it.“Now, you can turn the device on and off very easily,” Shao says.But while tunneling transistors can enable sharp switching slopes, they typically operate with low current, which hampers the performance of an electronic device. Higher current is necessary to create powerful transistor switches for demanding applications.Fine-grained fabricationUsing tools at MIT.nano, MIT’s state-of-the-art facility for nanoscale research, the engineers were able to carefully control the 3D geometry of their transistors, creating vertical nanowire heterostructures with a diameter of only 6 nanometers. They believe these are the smallest 3D transistors reported to date.Such precise engineering enabled them to achieve a sharp switching slope and high current simultaneously. This is possible because of a phenomenon called quantum confinement.Quantum confinement occurs when an electron is confined to a space that is so small that it can’t move around. When this happens, the effective mass of the electron and the properties of the material change, enabling stronger tunneling of the electron through a barrier.Because the transistors are so small, the researchers can engineer a very strong quantum confinement effect while also fabricating an extremely thin barrier.“We have a lot of flexibility to design these material heterostructures so we can achieve a very thin tunneling barrier, which enables us to get very high current,” Shao says.Precisely fabricating devices that were small enough to accomplish this was a major challenge.“We are really into single-nanometer dimensions with this work. Very few groups in the world can make good transistors in that range. Yanjie is extraordinarily capable to craft such well-functioning transistors that are so extremely small,” says del Alamo.When the researchers tested their devices, the sharpness of the switching slope was below the fundamental limit that can be achieved with conventional silicon transistors. Their devices also performed about 20 times better than similar tunneling transistors.“This is the first time we have been able to achieve such sharp switching steepness with this design,” Shao adds.The researchers are now striving to enhance their fabrication methods to make transistors more uniform across an entire chip. With such small devices, even a 1-nanometer variance can change the behavior of the electrons and affect device operation. They are also exploring vertical fin-shaped structures, in addition to vertical nanowire transistors, which could potentially improve the uniformity of devices on a chip.“This work definitively steps in the right direction, significantly improving the broken-gap tunnel field effect transistor (TFET) performance. It demonstrates steep-slope together with a record drive-current. It highlights the importance of small dimensions, extreme confinement, and low-defectivity materials and interfaces in the fabricated broken-gap TFET. These features have been realized through a well-mastered and nanometer-size-controlled process,” says Aryan Afzalian, a principal member of the technical staff at the nanoelectronics research organization imec, who was not involved with this work.This research is funded, in part, by Intel Corporation. More

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    Translating MIT research into real-world results

    Inventive solutions to some of the world’s most critical problems are being discovered in labs, classrooms, and centers across MIT every day. Many of these solutions move from the lab to the commercial world with the help of over 85 Institute resources that comprise MIT’s robust innovation and entrepreneurship (I&E) ecosystem. The Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) draws on MIT’s wealth of I&E knowledge and experience to help researchers commercialize their breakthrough technologies through the J-WAFS Solutions grant program. By collaborating with I&E programs on campus, J-WAFS prepares MIT researchers for the commercial world, where their novel innovations aim to improve productivity, accessibility, and sustainability of water and food systems, creating economic, environmental, and societal benefits along the way.The J-WAFS Solutions program launched in 2015 with support from Community Jameel, an international organization that advances science and learning for communities to thrive. Since 2015, J-WAFS Solutions has supported 19 projects with one-year grants of up to $150,000, with some projects receiving renewal grants for a second year of support. Solutions projects all address challenges related to water or food. Modeled after the esteemed grant program of MIT’s Deshpande Center for Technological Innovation, and initially administered by Deshpande Center staff, the J-WAFS Solutions program follows a similar approach by supporting projects that have already completed the basic research and proof-of-concept phases. With technologies that are one to three years away from commercialization, grantees work on identifying their potential markets and learn to focus on how their technology can meet the needs of future customers.“Ingenuity thrives at MIT, driving inventions that can be translated into real-world applications for widespread adoption, implantation, and use,” says J-WAFS Director Professor John H. Lienhard V. “But successful commercialization of MIT technology requires engineers to focus on many challenges beyond making the technology work. MIT’s I&E network offers a variety of programs that help researchers develop technology readiness, investigate markets, conduct customer discovery, and initiate product design and development,” Lienhard adds. “With this strong I&E framework, many J-WAFS Solutions teams have established startup companies by the completion of the grant. J-WAFS-supported technologies have had powerful, positive effects on human welfare. Together, the J-WAFS Solutions program and MIT’s I&E ecosystem demonstrate how academic research can evolve into business innovations that make a better world,” Lienhard says.Creating I&E collaborationsIn addition to support for furthering research, J-WAFS Solutions grants allow faculty, students, postdocs, and research staff to learn the fundamentals of how to transform their work into commercial products and companies. As part of the grant requirements, researchers must interact with mentors through MIT Venture Mentoring Service (VMS). VMS connects MIT entrepreneurs with teams of carefully selected professionals who provide free and confidential mentorship, guidance, and other services to help advance ideas into for-profit, for-benefit, or nonprofit ventures. Since 2000, VMS has mentored over 4,600 MIT entrepreneurs across all industries, through a dynamic and accomplished group of nearly 200 mentors who volunteer their time so that others may succeed. The mentors provide impartial and unbiased advice to members of the MIT community, including MIT alumni in the Boston area. J-WAFS Solutions teams have been guided by 21 mentors from numerous companies and nonprofits. Mentors often attend project events and progress meetings throughout the grant period.“Working with VMS has provided me and my organization with a valuable sounding board for a range of topics, big and small,” says Eric Verploegen PhD ’08, former research engineer in MIT’s D-Lab and founder of J-WAFS spinout CoolVeg. Along with professors Leon Glicksman and Daniel Frey, Verploegen received a J-WAFS Solutions grant in 2021 to commercialize cold-storage chambers that use evaporative cooling to help farmers preserve fruits and vegetables in rural off-grid communities. Verploegen started CoolVeg in 2022 to increase access and adoption of open-source, evaporative cooling technologies through collaborations with businesses, research institutions, nongovernmental organizations, and government agencies. “Working as a solo founder at my nonprofit venture, it is always great to have avenues to get feedback on communications approaches, overall strategy, and operational issues that my mentors have experience with,” Verploegen says. Three years after the initial Solutions grant, one of the VMS mentors assigned to the evaporative cooling team still acts as a mentor to Verploegen today.Another Solutions grant requirement is for teams to participate in the Spark program — a free, three-week course that provides an entry point for researchers to explore the potential value of their innovation. Spark is part of the National Science Foundation’s (NSF) Innovation Corps (I-Corps), which is an “immersive, entrepreneurial training program that facilitates the transformation of invention to impact.” In 2018, MIT received an award from the NSF, establishing the New England Regional Innovation Corps Node (NE I-Corps) to deliver I-Corps training to participants across New England. Trainings are open to researchers, engineers, scientists, and others who want to engage in a customer discovery process for their technology. Offered regularly throughout the year, the Spark course helps participants identify markets and explore customer needs in order to understand how their technologies can be positioned competitively in their target markets. They learn to assess barriers to adoption, as well as potential regulatory issues or other challenges to commercialization. NE-I-Corps reports that since its start, over 1,200 researchers from MIT have completed the program and have gone on to launch 175 ventures, raising over $3.3 billion in funding from grants and investors, and creating over 1,800 jobs.Constantinos Katsimpouras, a research scientist in the Department of Chemical Engineering, went through the NE I-Corps Spark program to better understand the customer base for a technology he developed with professors Gregory Stephanopoulos and Anthony Sinskey. The group received a J-WAFS Solutions grant in 2021 for their microbial platform that converts food waste from the dairy industry into valuable products. “As a scientist with no prior experience in entrepreneurship, the program introduced me to important concepts and tools for conducting customer interviews and adopting a new mindset,” notes Katsimpouras. “Most importantly, it encouraged me to get out of the building and engage in interviews with potential customers and stakeholders, providing me with invaluable insights and a deeper understanding of my industry,” he adds. These interviews also helped connect the team with companies willing to provide resources to test and improve their technology — a critical step to the scale-up of any lab invention.In the case of Professor Cem Tasan’s research group in the Department of Materials Science and Engineering, the I-Corps program led them to the J-WAFS Solutions grant, instead of the other way around. Tasan is currently working with postdoc Onur Guvenc on a J-WAFS Solutions project to manufacture formable sheet metal by consolidating steel scrap without melting, thereby reducing water use compared to traditional steel processing. Before applying for the Solutions grant, Guvenc took part in NE I-Corps. Like Katsimpouras, Guvenc benefited from the interaction with industry. “This program required me to step out of the lab and engage with potential customers, allowing me to learn about their immediate challenges and test my initial assumptions about the market,” Guvenc recalls. “My interviews with industry professionals also made me aware of the connection between water consumption and steelmaking processes, which ultimately led to the J-WAFS 2023 Solutions Grant,” says Guvenc.After completing the Spark program, participants may be eligible to apply for the Fusion program, which provides microgrants of up to $1,500 to conduct further customer discovery. The Fusion program is self-paced, requiring teams to conduct 12 additional customer interviews and craft a final presentation summarizing their key learnings. Professor Patrick Doyle’s J-WAFS Solutions team completed the Spark and Fusion programs at MIT. Most recently, their team was accepted to join the NSF I-Corps National program with a $50,000 award. The intensive program requires teams to complete an additional 100 customer discovery interviews over seven weeks. Located in the Department of Chemical Engineering, the Doyle lab is working on a sustainable microparticle hydrogel system to rapidly remove micropollutants from water. The team’s focus has expanded to higher value purifications in amino acid and biopharmaceutical manufacturing applications. Devashish Gokhale PhD ’24 worked with Doyle on much of the underlying science.“Our platform technology could potentially be used for selective separations in very diverse market segments, ranging from individual consumers to large industries and government bodies with varied use-cases,” Gokhale explains. He goes on to say, “The I-Corps Spark program added significant value by providing me with an effective framework to approach this problem … I was assigned a mentor who provided critical feedback, teaching me how to formulate effective questions and identify promising opportunities.” Gokhale says that by the end of Spark, the team was able to identify the best target markets for their products. He also says that the program provided valuable seminars on topics like intellectual property, which was helpful in subsequent discussions the team had with MIT’s Technology Licensing Office.Another member of Doyle’s team, Arjav Shah, a recent PhD from MIT’s Department of Chemical Engineering and a current MBA candidate at the MIT Sloan School of Management, is spearheading the team’s commercialization plans. Shah attended Fusion last fall and hopes to lead efforts to incorporate a startup company called hydroGel.  “I admire the hypothesis-driven approach of the I-Corps program,” says Shah. “It has enabled us to identify our customers’ biggest pain points, which will hopefully lead us to finding a product-market fit.” He adds “based on our learnings from the program, we have been able to pivot to impact-driven, higher-value applications in the food processing and biopharmaceutical industries.” Postdoc Luca Mazzaferro will lead the technical team at hydroGel alongside Shah.In a different project, Qinmin Zheng, a postdoc in the Department of Civil and Environmental Engineering, is working with Professor Andrew Whittle and Lecturer Fábio Duarte. Zheng plans to take the Fusion course this fall to advance their J-WAFS Solutions project that aims to commercialize a novel sensor to quantify the relative abundance of major algal species and provide early detection of harmful algal blooms. After completing Spark, Zheng says he’s “excited to participate in the Fusion program, and potentially the National I-Corps program, to further explore market opportunities and minimize risks in our future product development.”Economic and societal benefitsCommercializing technologies developed at MIT is one of the ways J-WAFS helps ensure that MIT research advances will have real-world impacts in water and food systems. Since its inception, the J-WAFS Solutions program has awarded 28 grants (including renewals), which have supported 19 projects that address a wide range of global water and food challenges. The program has distributed over $4 million to 24 professors, 11 research staff, 15 postdocs, and 30 students across MIT. Nearly half of all J-WAFS Solutions projects have resulted in spinout companies or commercialized products, including eight companies to date plus two open-source technologies.Nona Technologies is an example of a J-WAFS spinout that is helping the world by developing new approaches to produce freshwater for drinking. Desalination — the process of removing salts from seawater — typically requires a large-scale technology called reverse osmosis. But Nona created a desalination device that can work in remote off-grid locations. By separating salt and bacteria from water using electric current through a process called ion concentration polarization (ICP), their technology also reduces overall energy consumption. The novel method was developed by Jongyoon Han, professor of electrical engineering and biological engineering, and research scientist Junghyo Yoon. Along with Bruce Crawford, a Sloan MBA alum, Han and Yoon created Nona Technologies to bring their lightweight, energy-efficient desalination technology to the market.“My feeling early on was that once you have technology, commercialization will take care of itself,” admits Crawford. The team completed both the Spark and Fusion programs and quickly realized that much more work would be required. “Even in our first 24 interviews, we learned that the two first markets we envisioned would not be viable in the near term, and we also got our first hints at the beachhead we ultimately selected,” says Crawford. Nona Technologies has since won MIT’s $100K Entrepreneurship Competition, received media attention from outlets like Newsweek and Fortune, and hired a team that continues to further the technology for deployment in resource-limited areas where clean drinking water may be scarce. Food-borne diseases sicken millions of people worldwide each year, but J-WAFS researchers are addressing this issue by integrating molecular engineering, nanotechnology, and artificial intelligence to revolutionize food pathogen testing. Professors Tim Swager and Alexander Klibanov, of the Department of Chemistry, were awarded one of the first J-WAFS Solutions grants for their sensor that targets food safety pathogens. The sensor uses specialized droplets that behave like a dynamic lens, changing in the presence of target bacteria in order to detect dangerous bacterial contamination in food. In 2018, Swager launched Xibus Systems Inc. to bring the sensor to market and advance food safety for greater public health, sustainability, and economic security.“Our involvement with the J-WAFS Solutions Program has been vital,” says Swager. “It has provided us with a bridge between the academic world and the business world and allowed us to perform more detailed work to create a usable application,” he adds. In 2022, Xibus developed a product called XiSafe, which enables the detection of contaminants like salmonella and listeria faster and with higher sensitivity than other food testing products. The innovation could save food processors billions of dollars worldwide and prevent thousands of food-borne fatalities annually.J-WAFS Solutions companies have raised nearly $66 million in venture capital and other funding. Just this past June, J-WAFS spinout SiTration announced that it raised an $11.8 million seed round. Jeffrey Grossman, a professor in MIT’s Department of Materials Science and Engineering, was another early J-WAFS Solutions grantee for his work on low-cost energy-efficient filters for desalination. The project enabled the development of nanoporous membranes and resulted in two spinout companies, Via Separations and SiTration. SiTration was co-founded by Brendan Smith PhD ’18, who was a part of the original J-WAFS team. Smith is CEO of the company and has overseen the advancement of the membrane technology, which has gone on to reduce cost and resource consumption in industrial wastewater treatment, advanced manufacturing, and resource extraction of materials such as lithium, cobalt, and nickel from recycled electric vehicle batteries. The company also recently announced that it is working with the mining company Rio Tinto to handle harmful wastewater generated at mines.But it’s not just J-WAFS spinout companies that are producing real-world results. Products like the ECC Vial — a portable, low-cost method for E. coli detection in water — have been brought to the market and helped thousands of people. The test kit was developed by MIT D-Lab Lecturer Susan Murcott and Professor Jeffrey Ravel of the MIT History Section. The duo received a J-WAFS Solutions grant in 2018 to promote safely managed drinking water and improved public health in Nepal, where it is difficult to identify which wells are contaminated by E. coli. By the end of their grant period, the team had manufactured approximately 3,200 units, of which 2,350 were distributed — enough to help 12,000 people in Nepal. The researchers also trained local Nepalese on best manufacturing practices.“It’s very important, in my life experience, to follow your dream and to serve others,” says Murcott. Economic success is important to the health of any venture, whether it’s a company or a product, but equally important is the social impact — a philosophy that J-WAFS research strives to uphold. “Do something because it’s worth doing and because it changes people’s lives and saves lives,” Murcott adds.As J-WAFS prepares to celebrate its 10th anniversary this year, we look forward to continued collaboration with MIT’s many I&E programs to advance knowledge and develop solutions that will have tangible effects on the world’s water and food systems.Learn more about the J-WAFS Solutions program and about innovation and entrepreneurship at MIT. More

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    Elaine Liu: Charging ahead

    MIT senior Elaine Siyu Liu doesn’t own an electric car, or any car. But she sees the impact of electric vehicles (EVs) and renewables on the grid as two pieces of an energy puzzle she wants to solve.The U.S. Department of Energy reports that the number of public and private EV charging ports nearly doubled in the past three years, and many more are in the works. Users expect to plug in at their convenience, charge up, and drive away. But what if the grid can’t handle it?Electricity demand, long stagnant in the United States, has spiked due to EVs, data centers that drive artificial intelligence, and industry. Grid planners forecast an increase of 2.6 percent to 4.7 percent in electricity demand over the next five years, according to data reported to federal regulators. Everyone from EV charging-station operators to utility-system operators needs help navigating a system in flux.That’s where Liu’s work comes in.Liu, who is studying mathematics and electrical engineering and computer science (EECS), is interested in distribution — how to get electricity from a centralized location to consumers. “I see power systems as a good venue for theoretical research as an application tool,” she says. “I’m interested in it because I’m familiar with the optimization and probability techniques used to map this level of problem.”Liu grew up in Beijing, then after middle school moved with her parents to Canada and enrolled in a prep school in Oakville, Ontario, 30 miles outside Toronto.Liu stumbled upon an opportunity to take part in a regional math competition and eventually started a math club, but at the time, the school’s culture surrounding math surprised her. Being exposed to what seemed to be some students’ aversion to math, she says, “I don’t think my feelings about math changed. I think my feelings about how people feel about math changed.”Liu brought her passion for math to MIT. The summer after her sophomore year, she took on the first of the two Undergraduate Research Opportunity Program projects she completed with electric power system expert Marija Ilić, a joint adjunct professor in EECS and a senior research scientist at the MIT Laboratory for Information and Decision Systems.Predicting the gridSince 2022, with the help of funding from the MIT Energy Initiative (MITEI), Liu has been working with Ilić on identifying ways in which the grid is challenged.One factor is the addition of renewables to the energy pipeline. A gap in wind or sun might cause a lag in power generation. If this lag occurs during peak demand, it could mean trouble for a grid already taxed by extreme weather and other unforeseen events.If you think of the grid as a network of dozens of interconnected parts, once an element in the network fails — say, a tree downs a transmission line — the electricity that used to go through that line needs to be rerouted. This may overload other lines, creating what’s known as a cascade failure.“This all happens really quickly and has very large downstream effects,” Liu says. “Millions of people will have instant blackouts.”Even if the system can handle a single downed line, Liu notes that “the nuance is that there are now a lot of renewables, and renewables are less predictable. You can’t predict a gap in wind or sun. When such things happen, there’s suddenly not enough generation and too much demand. So the same kind of failure would happen, but on a larger and more uncontrollable scale.”Renewables’ varying output has the added complication of causing voltage fluctuations. “We plug in our devices expecting a voltage of 110, but because of oscillations, you will never get exactly 110,” Liu says. “So even when you can deliver enough electricity, if you can’t deliver it at the specific voltage level that is required, that’s a problem.”Liu and Ilić are building a model to predict how and when the grid might fail. Lacking access to privatized data, Liu runs her models with European industry data and test cases made available to universities. “I have a fake power grid that I run my experiments on,” she says. “You can take the same tool and run it on the real power grid.”Liu’s model predicts cascade failures as they evolve. Supply from a wind generator, for example, might drop precipitously over the course of an hour. The model analyzes which substations and which households will be affected. “After we know we need to do something, this prediction tool can enable system operators to strategically intervene ahead of time,” Liu says.Dictating price and powerLast year, Liu turned her attention to EVs, which provide a different kind of challenge than renewables.In 2022, S&P Global reported that lawmakers argued that the U.S. Federal Energy Regulatory Commission’s (FERC) wholesale power rate structure was unfair for EV charging station operators.In addition to operators paying by the kilowatt-hour, some also pay more for electricity during peak demand hours. Only a few EVs charging up during those hours could result in higher costs for the operator even if their overall energy use is low.Anticipating how much power EVs will need is more complex than predicting energy needed for, say, heating and cooling. Unlike buildings, EVs move around, making it difficult to predict energy consumption at any given time. “If users don’t like the price at one charging station or how long the line is, they’ll go somewhere else,” Liu says. “Where to allocate EV chargers is a problem that a lot of people are dealing with right now.”One approach would be for FERC to dictate to EV users when and where to charge and what price they’ll pay. To Liu, this isn’t an attractive option. “No one likes to be told what to do,” she says.Liu is looking at optimizing a market-based solution that would be acceptable to top-level energy producers — wind and solar farms and nuclear plants — all the way down to the municipal aggregators that secure electricity at competitive rates and oversee distribution to the consumer.Analyzing the location, movement, and behavior patterns of all the EVs driven daily in Boston and other major energy hubs, she notes, could help demand aggregators determine where to place EV chargers and how much to charge consumers, akin to Walmart deciding how much to mark up wholesale eggs in different markets.Last year, Liu presented the work at MITEI’s annual research conference. This spring, Liu and Ilić are submitting a paper on the market optimization analysis to a journal of the Institute of Electrical and Electronics Engineers.Liu has come to terms with her early introduction to attitudes toward STEM that struck her as markedly different from those in China. She says, “I think the (prep) school had a very strong ‘math is for nerds’ vibe, especially for girls. There was a ‘why are you giving yourself more work?’ kind of mentality. But over time, I just learned to disregard that.”After graduation, Liu, the only undergraduate researcher in Ilić’s MIT Electric Energy Systems Group, plans to apply to fellowships and graduate programs in EECS, applied math, and operations research.Based on her analysis, Liu says that the market could effectively determine the price and availability of charging stations. Offering incentives for EV owners to charge during the day instead of at night when demand is high could help avoid grid overload and prevent extra costs to operators. “People would still retain the ability to go to a different charging station if they chose to,” she says. “I’m arguing that this works.” More

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    Titanic robots make farming more sustainable

    There’s a lot riding on farmers’ ability to fight weeds, which can strangle crops and destroy yields. To protect crops, farmers have two options: They can spray herbicides that pollute the environment and harm human health, or they can hire more workers.

    Unfortunately, both choices are becoming less tenable. Herbicide resistance is a growing problem in crops around the world, while widespread labor shortages have hit the agricultural sector particularly hard.

    Now the startup FarmWise, co-founded by Sebastien Boyer SM ’16, is giving farmers a third option. The company has developed autonomous weeding robots that use artificial intelligence to cut out weeds while leaving crops untouched.

    The company’s first robot, fittingly called the Titan — picture a large tractor that makes use of a trailer in lieu of a driver’s seat — uses machine vision to distinguish weeds from crops including leafy greens, cauliflower, artichokes, and tomatoes while snipping weeds with sub-inch precision.

    About 15 Titans have been roaming the fields of 30 large farms in California and Arizona for the last few years, providing weeding as a service while being directed by an iPad. Last month, the company unveiled its newest robot, Vulcan, which is more lightweight and pulled by a tractor.

    “We have growing population, and we can’t expand the land or water we have, so we need to drastically increase the efficiency of the farming industry,” Boyer says. “I think AI and data are going to be major players in that journey.”

    Finding a road to impact

    Boyer came to MIT in 2014 and earned masters’ degrees in technology and policy as well as electrical engineering and computer science over the next two years.

    “What stood out is the passion that my classmates had for what they did — the drive and passion people had to change the world,” Boyer says.

    As part of his graduate work, Boyer researched machine learning and machine vision techniques, and he soon began exploring ways to apply those technologies to environmental problems. He received a small amount of funding from MIT Sandbox to further develop the idea.

    “That helped me make the decision to not take a real job,” Boyer recalls.

    Following graduation, he and FarmWise co-founder Thomas Palomares, a graduate of Stanford University whom Boyer met in his home country of France, began going to farmers’ markets, introducing themselves to small farmers and asking for tours of their farms. About one in three farmers were happy to show them around. From there they’d ask for referrals to larger farmers and service providers in the industry.

    “We realized agriculture is a large contributor of both emissions and, more broadly, to the negative impact of human activities on the environment,” Boyer says. “It also hasn’t been as disrupted by software, cloud computing, AI, and robotics as other industries. That combination really excites us.”

    Through their conversations, the founders learned herbicides are becoming less effective as weeds develop genetic resistance. The only alternative is to hire more workers, which itself was becoming more difficult for farmers.

    “Labor is extremely tight,” says Boyer, adding that bending over and weeding for 10 hours a day is one of the hardest jobs out there. “The labor supply is shrinking if not collapsing in the U.S., and it’s a worldwide trend. That has real environmental implications because of the tradeoff [between labor and herbicides].”

    The problem is especially acute for farmers of specialty crops, including many fruits, vegetables, and nuts, which grow on smaller farms than corn and soybean and each require slightly different growing practices, limiting the effectiveness of many technical and chemical solutions.

    “We don’t harvest corn by hand today, but we still harvest lettuces and nuts and apples by hand,” Boyer says.

    The Titan was built to complement field workers’ efforts to grow and maintain crops. An operator directs it using an iPad, walking alongside the machine and inspecting progress. Both the Titan and Vulcan are powered by an AI that directs hundreds of tiny blades to snip out weeds around each crop. The Vulcan is controlled directly from the tractor cab, where the operator has a touchscreen interface Boyer compares to those found in a Tesla.

    With more than 15,000 commercial hours under its belt, FarmWise hopes the data it collects can be used for more than just weeding in the near future.

    “It’s all about precision,” Boyer says. “We’re going to better understand what the plant needs and make smarter decisions for each one. That will bring us to a point where we can use the same amount of land, much less water, almost no chemicals, much less fertilizer, and still produce more food than we’re producing today. That’s the mission. That’s what excites me.”

    Weeding out farming challenges

    A customer recently told Boyer that without the Titan, he would have to switch all of his organic crops back to conventional because he couldn’t find enough workers.

    “That’s happening with a lot of customers,” Boyer says. “They have no choice but to rely on herbicides. Acres are staying organic because of our product, and conventional farms are reducing their use of herbicides.”

    Now FarmWise is expanding its database to support weeding for six to 12 new crops each year, and Boyer says adding new crops is getting easier and easier for its system.

    As early partners have sought to expand their deployments, Boyer says the only thing limiting the company’s growth is how fast it can build new robots. FarmWise’s new machines will begin being deployed later this year.

    Although the hulking Titan robots are the face of the company today, the founders hope to leverage the data they’ve collected to further improve farming operations.

    “The mission of the company is to turn AI into a tool that is as reliable and dependable as GPS is now in the farming industry,” Boyer says. “Twenty-five years ago, GPS was a very complicated technology. You had to connect to satellites and do some crazy computation to define your position. But a few companies brought GPS to a new level of reliability and simplicity. Today, every farmer in the world uses GPS. We think AI can have an even deeper impact than GPS has had on the farming industry, and we want to be the company that makes it available and easy to use for every farmer in the world.” More

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    Computing for the health of the planet

    The health of the planet is one of the most important challenges facing humankind today. From climate change to unsafe levels of air and water pollution to coastal and agricultural land erosion, a number of serious challenges threaten human and ecosystem health.

    Ensuring the health and safety of our planet necessitates approaches that connect scientific, engineering, social, economic, and political aspects. New computational methods can play a critical role by providing data-driven models and solutions for cleaner air, usable water, resilient food, efficient transportation systems, better-preserved biodiversity, and sustainable sources of energy.

    The MIT Schwarzman College of Computing is committed to hiring multiple new faculty in computing for climate and the environment, as part of MIT’s plan to recruit 20 climate-focused faculty under its climate action plan. This year the college undertook searches with several departments in the schools of Engineering and Science for shared faculty in computing for health of the planet, one of the six strategic areas of inquiry identified in an MIT-wide planning process to help focus shared hiring efforts. The college also undertook searches for core computing faculty in the Department of Electrical Engineering and Computer Science (EECS).

    The searches are part of an ongoing effort by the MIT Schwarzman College of Computing to hire 50 new faculty — 25 shared with other academic departments and 25 in computer science and artificial intelligence and decision-making. The goal is to build capacity at MIT to help more deeply infuse computing and other disciplines in departments.

    Four interdisciplinary scholars were hired in these searches. They will join the MIT faculty in the coming year to engage in research and teaching that will advance physical understanding of low-carbon energy solutions, Earth-climate modeling, biodiversity monitoring and conservation, and agricultural management through high-performance computing, transformational numerical methods, and machine-learning techniques.

    “By coordinating hiring efforts with multiple departments and schools, we were able to attract a cohort of exceptional scholars in this area to MIT. Each of them is developing and using advanced computational methods and tools to help find solutions for a range of climate and environmental issues,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Warren Ellis Professor of Electrical Engineering and Computer Science. “They will also help strengthen cross-departmental ties in computing across an important, critical area for MIT and the world.”

    “These strategic hires in the area of computing for climate and the environment are an incredible opportunity for the college to deepen its academic offerings and create new opportunity for collaboration across MIT,” says Anantha P. Chandrakasan, dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “The college plays a pivotal role in MIT’s overarching effort to hire climate-focused faculty — introducing the critical role of computing to address the health of the planet through innovative research and curriculum.”

    The four new faculty members are:

    Sara Beery will join MIT as an assistant professor in the Faculty of Artificial Intelligence and Decision-Making in EECS in September 2023. Beery received her PhD in computing and mathematical sciences at Caltech in 2022, where she was advised by Pietro Perona. Her research focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities, tackling real-world challenges including strong spatiotemporal correlations, imperfect data quality, fine-grained categories, and long-tailed distributions. She partners with nongovernmental organizations and government agencies to deploy her methods in the wild worldwide and works toward increasing the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity building and education.

    Priya Donti will join MIT as an assistant professor in the faculties of Electrical Engineering and Artificial Intelligence and Decision-Making in EECS in academic year 2023-24. Donti recently finished her PhD in the Computer Science Department and the Department of Engineering and Public Policy at Carnegie Mellon University, co-advised by Zico Kolter and Inês Azevedo. Her work focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, her research explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning models. Donti is also co-founder and chair of Climate Change AI, a nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning that is currently running through the Cornell Tech Runway Startup Postdoc Program.

    Ericmoore Jossou will join MIT as an assistant professor in a shared position between the Department of Nuclear Science and Engineering and the faculty of electrical engineering in EECS in July 2023. He is currently an assistant scientist at the Brookhaven National Laboratory, a U.S. Department of Energy-affiliated lab that conducts research in nuclear and high energy physics, energy science and technology, environmental and bioscience, nanoscience, and national security. His research at MIT will focus on understanding the processing-structure-properties correlation of materials for nuclear energy applications through advanced experiments, multiscale simulations, and data science. Jossou obtained his PhD in mechanical engineering in 2019 from the University of Saskatchewan.

    Sherrie Wang will join MIT as an assistant professor in a shared position between the Department of Mechanical Engineering and the Institute for Data, Systems, and Society in academic year 2023-24. Wang is currently a Ciriacy-Wantrup Postdoctoral Fellow at the University of California at Berkeley, hosted by Solomon Hsiang and the Global Policy Lab. She develops machine learning for Earth observation data. Her primary application areas are improving agricultural management and forecasting climate phenomena. She obtained her PhD in computational and mathematical engineering from Stanford University in 2021, where she was advised by David Lobell. More