Massachusetts Institute Of Technology

NIH Research Projects · FY 2025 · 2025-09

Project Summary: Atrial fibrillation (AF) is the most common arrhythmia, affecting ~9% of the US population >65 years old. AF patients have a 5-fold increased risk of stroke, a leading cause of death and disability that costs over $50 billion/year. Over 90% of stroke-causing blood clots in AF patients form in the left atrial appendage (LAA), and thus occlusion of the LAA (LAAO) represents a promising alternative to long-term blood-thinners. In theory, this one-time procedure will seal off the LAA to eliminate stroke risk associated with LAA thrombus and bleeding risk associated with indefinite systemic anticoagulation. In practice, LAAO is limited by the intrinsic disparity between prefabricated, one-size-fits-all medical devices and individual human patients. FDA-approved LAAO devices are metallic, round, and mass-produced in standard sizes, whereas human LAAs are composed of soft tissues in a limitless range of shapes and sizes. This inherent geometric and mechanical mismatch leads to incomplete LAA sealing, challenging deployment workflows, local tissue trauma, and failed stroke prevention. Ultimately, we do not expect these issues to be solved by iterative improvements to the same one- size-fits-all manufacturing paradigm. Instead, we propose to form fully-soft, personalized medical implants directly inside the patient’s body in a minimally-invasive approach. By delivering, forming, and stabilizing soft materials at the target tissue location, we provide atraumatic 3D implants that are custom made to fit each patient’s unique anatomy. This concept will simultaneously address the patient-device mismatch and device-anatomy alignment problems to achieve safer and more effective stroke prevention in a simplified clinical workflow. Our Catalyze project is focused on establishing a strong translational foundation while generating critical feasibility, safety, and efficacy data. In the R61 Phase, we develop design, regulatory and commercialization documentation, refine and verify the catheter and implant sub-systems, produce in-vitro and ex-vivo validation for the integrated prototype, and demonstrate feasibility of the full deployment workflow in a benchtop cardiovascular simulator. In the R33 Phase, we test and refine our prototype in iterative large animal pilot trials (terminal, conducted internally), formalize and characterize the prototype assembly process, and finally establish preclinical feasibility, safety, and efficacy in a large animal study at an independent test facility (non-GLP, conducted externally). Upon completion, we’ll have produced a functional product prototype that satisfies early-stage design constraints, fulfills key performance requirements, and enables safe and effective execution of our in-situ implant formation workflow in challenging preclinical models. This data will concretely establish the technical feasibility and clinical potential for our new technology, and the corresponding design documentation and regulatory plans will provide a solid foundation for product finalization, quality management, GMP manufacturing, GLP testing, and IDE submission. If realized, our approach for on-demand, in-situ formation of atraumatic and patient-specific cardiac implants would be a paradigm shift in device-based stroke prevention for the millions of patients living with atrial fibrillation.

NSF Awards · FY 2025 · 2025-09

This grant supports research that looks to advance the knowledge of how fluid-coupled granular media behave. Because granular media are ubiquitous in natural systems (such as soils in riverbeds and landslides) and infrastructure (such as concrete and ballast), this research will promote both the progress of science and engineering, as well as advance national prosperity. When a load is applied to a granular medium, such load is transmitted via a network of forces among grains that are in contact. This network of forces, or force chains, is the ultimate determinant of how granular media behave under external loading (e.g., compression and shear) and under fluid injection and withdrawal. Understanding the spatial structure and temporal evolution of force chains constitutes a fundamental goal of granular mechanics. However, the current knowledge of granular media is limited by the experimental observations on force chains, which are either on two-dimensional packs or on three-dimensional packs with limited grain shapes or loading conditions. The coupling between the solids and fluids in granular media adds yet additional complexity for observations and modeling. This award supports fundamental research looking to advance experimental techniques and the associated theory for fluid-coupled granular media, enabling the observation of the transmission of external loads on both the single-grain scale and the granular pack scale. The outcomes of this research intend to provide new knowledge of the organization of contact forces in fluid-coupled granular media at the grain scale, and help predict their behavior in natural systems like landslides and earthquakes, as well as engineering applications like construction materials, infrastructure and robotics. The outcomes of the research will be integrated into undergraduate and graduate courses and multiple well-organized outreach activities, such as the Simons STEM Scholars program, the Simons Summer Research Program, and Engineering Academy for grade 6-12 students, with an expectation to engage a broad group of students, thus positively impacting engineering education in the US. This research looks to advance the fundamental understanding of the mechanical behavior of granular media by developing innovative experimental and theoretical techniques that will enable accessing, quantitatively, the stress-tensor field, and associated force chains, in 3D granular packs of round and angular particles, under various load conditions and fluid-coupling scenarios. This research seeks to develop the experimental apparatus and associated theory for the tomographic reconstruction of stress tensors in fluid-coupled granular media under external loads in 3D, based on interference optical projection tomography. This new method intends to advance the understanding of the tensor nature of effective stress on the grain scale, which results from the normal and tangential contact forces between particles of various shapes and moduli, as well as elucidate the spatial structure and temporal evolution of force chains in 3D packs of angular and round particles under various stress conditions and fluid-coupling scenarios.. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The research objective of this program is to determine when and how “Brightest Cluster Galaxies” assembled. These types of galaxies are the most massive galaxies in the universe and host the most massive black holes. These galaxies stand out by their brightness and size when compared to other galaxies. This program will trace the evolution of Brightest Cluster Galaxies over almost 10 billion years and determine how they became the dominant galaxy in their environment. These goals will be achieved through the study of data obtained by telescopes operating at different wavelengths. This research program will form the basis of a doctoral thesis, and will support a highly successful, ongoing outreach program for enlisted veterans. This program will carry out the first evolutionary study of the brightest cluster galaxies (BCGs) in a carefully selected sample that controls for the mass evolution of the host cluster. This study will constrain when the BCG was first established, the dominant channels of growth over the past 10 Gyr, and when radio-mode feedback first began to quench large-scale cooling and suppress star formation in these massive galaxies. These goals will be achieved through a multiwavelength study of BCGs in a unique sample of more than 800 massive galaxy clusters lying along a common evolutionary path. Through the Warrior-Scholar Project, this program will offer STEM bootcamps to enlisted veterans at MIT. This program will provide enlisted veterans with the confidence and tools needed to successfully pursue a degree in STEM fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

PRIMES (Program for Research in Mathematics, Engineering and Science) will select talented high school students from across the U.S. via rigorous testing. Under the guidance of academic mentors, program participants will conduct year-long research projects, write papers, and make conference presentations. Groups of students will also participate in guided reading, online research forums, and a residential summer math camp. The program will create a pipeline of mathematical talent and support graduate students and undergraduates serving as mentors. Topics for student research projects will include ancient ALE Ricci flows and dynamical energy functionals, refractive outer billiards, fields of definition of abelian surfaces of maximal Picard rank, semisimplifications of representations of gl(n), Temperley-Lieb algebras and canonical bases, tournament and digraph inversions, machine learning for physical systems, sparse inference of earthquake dynamics, and Fresnel inversion and the NASA Cassini Mission. More details and information about the program may be found on the PRIMES website: https://math.mit.edu/research/highschool/primes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Section The glycan coat is an evolutionarily conserved feature of all cells that depends on cell identity and state. Human lectins read this glycan coat to influence immunity and tolerance. For most human lectins, we lack information on what cell types they bind. More profound knowledge of lectin action can yield novel biomarkers and tailored therapies for diseases ranging from inflammatory bowel disease to cancer. The proposed aims focus on developing new tools to address the current knowledge gaps. The goal of Aim 1 is to create a general strategy to assess the microbe binding selectivity of soluble human lectins. We anticipate this Aim will afford tools that provide insight into how lectins influence human microbial communities. We are especially interested in what host species lectins have evolved to recognize and how their recognition affects their microbial targets. In Aim 2, we shall devise a capture agent that can be used to assess the glycan targets of lectins. Our objective is to fill a gap in the tools available to identify physiological protein-glycan interaction partners. Aim 3 focuses on studying and engineering a lectin that can bind and kill bacteria. We aim to understand how this lectin exerts its antimicrobial activity and engineer new variant proteins that can target and eliminate pathogens. Significance This application aims to develop new strategies to identify what cells our carbohydrate-binding proteins prefer and why. We anticipate that this knowledge will yield new insights into the roles of these proteins in a wide range of areas relevant to human health.

NSF Awards · FY 2025 · 2025-09

The development of the Standard Model (SM) of particle physics is a major intellectual achievement. The validity of this model was further confirmed by the discovery of the Higgs boson at the Large Hadron Collider at CERN. However, the Standard Model leaves open many questions, including why matter dominates over anti-matter in the Universe (CP violation) and what are the properties of dark matter, among others. Most explanations require new phenomena, which we call Beyond the Standard Model Physics (BSM), and which the LHCb experiment at CERN has been designed to explore. This award provides facility operations, maintenance, and computing support to enable the participation of U.S. scientists in the LHCb experiment at CERN. The LHC is the premier High Energy Physics particle accelerator in the world and is currently operating at the CERN laboratory near Geneva Switzerland, one of the foremost facilities for answering these BSM questions. The LHCb experiment is one of four large experiments at the LHC and is designed to study in detail the decays of hadrons containing b or c quarks. The goal is to identify the existence of new physics beyond the Standard Model by examining the properties of hadrons containing these quarks. The new physics, or new forces, can be manifest by particles, as yet to be discovered, whose presence would modify decay rates and CP violating asymmetries of hadrons containing the b and c quarks, allowing new phenomena to be observed indirectly. U.S. groups play a leading role in the physics analysis, hardware development, and computing of LHCb. This award will support the NSF-supported groups' share of common items necessary for the experiment, maintenance and operations support for U.S.-delivered components, co-location of an LHCb Tier-2 computing facility, and R&D to optimize the operation of the experiment. The broader impacts of this award cover many areas, from student research experiences for graduate and undergraduate students, to very active QuarkNet Centers and Masterclass programs for high school teachers and students. A steady stream of undergraduates has been working in the participating university laboratories, where graduate students also have direct engagement in both instrumentation development as well as data analysis. Undergraduate and graduate students will be direct participants in the testing and maintenance of detector components under U.S. responsibility. Early career researchers will be integral participants in this exciting program of research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

When magmas remain underground, without erupting, those systems are called plutons. Part of what determines whether those magmas will erupt from plutons is how closely integrated the melt and the crystals are (also called how “mushy” the system is). This collaborative US-Swiss team will integrate field data, laboratory experiments, and computational numerical analysis to develop a model for understanding the physics of plutons and how crystals and melt interact within them. This project supports a team in the US, and a team in Switzerland. The field work, led by the Swiss part of this team, will occur in Adamello, Italy; Spirit Mountain, USA; and the Famatinian arc, Argentina). The Swiss team will look at the geochemistry and microtextures of the rock, and compare them with the experiments and numerical models created by the US team. Developing models to examine how melt and crystals separate in mushes is critical for understanding what leads to volcanic eruptions. The international collaborative nature of this work will provide unique training for the graduate students and postdoctoral scholars involved. Undergraduate Research Experience programs at Brown and MIT will engage even more students in the project. This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland. While developments in geochemistry, geochronology and petrology over the past decades have highlighted the importance of mushy magma reservoirs as a fundamental element of crustal magmatic distilleries, our understanding of the physics underpinning the evolution of these systems lags behind. The challenges with these multiphase systems are in part caused by their complexity and the wide range of temporal and spatial scales involved and in part because bridging laboratory experiments, modeling and field sample analyses across scales is difficult and requires a complex multidisciplinary effort. This project supports a multidisciplinary approach, combining new laboratory experiments, granular mechanics models and field samples analyses. Their objectives are twofold: (1) the development of a unified framework for melt-crystal separation in magmas from dilute suspension to crystal mushes tested and validated against experiments and crystal-scale simulations and (2) the application of this new model to field examples complemented with geochemical and petrographical analyses to link processes with their expression in the rock record and define textural signatures associated with each process. This US-Switzerland collaboration is designed to address these challenges and bring a new light on the multiphase dynamics of magmas undergoing phase separation. The models developed here will contribute to granular mechanics and multiphase fluid dynamics within and beyond Earth Sciences and provide a new perspective on the dynamics of magma reservoirs in general. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Representation theory is a study of symmetries of space, such as our 3-dimensional space, or, more generally, a space with any (even infinite number) of dimensions. In this theory, symmetries are represented by linear transformations of this space, or, more explicitly, by matrices. Thus, a representation of a given symmetry structure is basically a collection of matrices which satisfy a certain natural system of nonlinear equations. The equations are determined by the exact type of symmetry structure we are representing - a group, a Lie algebra, or an associative algebra. Representations of a given structure themselves form a quite intricate and rich structure, which encodes relations (or mappings) between different representations. This higher-level structure is called the category of representations. For some type of structures, for example groups, Lie algebras, and quantum groups, representations can be multiplied; in this case the corresponding categories are tensor categories (as multiplication of representations is similar to multiplication of tensors). It turns out that the notion of a tensor category is very interesting in its own right, and that many tensor categories don't arise as categories of representations. This project will study ordinary and tensor categories, some of which arise as representation categories and some of which don't, and connections between them. In particular, the PI will study non-integer rank generalizations of representation categories proposed by P. Deligne. Roughly speaking, this is a generalization in which the number of elements of a set or rows of a matrix is allowed to be non-integer. This setting becomes meaningful and useful when the invariants one is interested in turn out to be polynomials of the number of elements or rows, which is often true. The project also involves the study of quantizations of singular symplectic varieties, for instance symplectic resolutions. These are non-commutative algebras that appear in certain kinds of quantum field theories of recent interest as algebras of quantum observables. Finally, the project will continue tthe study of the analytic Langlands correspondence, which was initiated by the PI with E. Frenkel and D. Kazhdan. This is a new subject that unifies several topics of current interest in algebra, number theory, geometry, and quantum physics. The project also provides research training opportunities for graduate students and the PI will supervise the work of high school students in MIT PRIMES. In more detail, the PI plans to: 1) Continue to develop Lie theory in tensor categories in positive characteristic, in particular the Verlinde category Ver(p); study and classify simple and linearly reductive Lie algebras in this category, compute their cohomology and study representations; compute the semisimplification of the category of tilting modules for a reductive group in small characteristic, and use it to compute the dimensions of tilting modules modulo a prime p; compute the cohomology of higher Verlinde categories Ver(p^n); classify exact factorizations of fusion categories, in particular twisted Deligne products; classify fiber functors and module categories over the representation category of the small quantum group; continue to develop the theory of actions of finite dimensional Hopf algebras on division algebras, and in particular, fields; and classify unipotent tensor categories. 2) Continue to develop the ideas of P. Deligne, and extend representation theories of various classical structures (containing the symmetric group S_n or classical Lie groups GL(n), O(n), or Sp(n)) to non-integer values of the parameter n; compute reducibility loci and obtain various character formulas and signature formulas in these representation theories, and answer various other representation theoretic questions; study similar questions in the recently introduced Delannoy and arboreal tensor categories. 3) Study signatures of representations of quantum groups and Hecke algebras for |q|=1 and of Cherednik algebras; work on a discrete analog of the monodromy theorem for the Casimir connection; work on the representation theory of deformed double current algebras, representations of cyclotomic Cherednik algebras, representations of Cherednik algebras in positive characteristic, direct and inverse image functors for Cherednik algebras, short star-products on quantizations, centers of quantum affine algebras when the level parameter is a root of unity. 4) Continue to work with E. Frenkel and D. Kazhdan on the analytic Langlands correspondence and explore applications of separation of variables. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

When many particles interact, they can form collective states of matter, the most common of which are the solid, liquid and gaseous state. The present project will search for new states of matter at ultralow temperatures, using gases of atoms with freely tunable interactions as the starting point. At these low temperatures, quantum mechanics takes center stage, and the intrinsic uncertainty in where each particle is – the Heisenberg uncertainty – strongly affects the behavior of the collection of particles. They commonly form a quantum liquid, but they may enter a superfluid state, where atoms flow without any friction. Understanding such superfluid states is crucial for the understanding of yet another “super” state, namely superconductors, which carry electricity without any heat. The atoms in the experiment will be imaged with single-atom resolution, enabling an unprecedented view into the microscopic origins of various phases of matter. In particular, the research aims to find evidence for a state that is at the same time a superfluid and a solid. These experiments will enhance our understanding of collective phenomena and states of matter. The work will provide excellent training for graduate and undergraduate students on lasers and optics, computer control, vacuum assemblies, high magnetic fields, radiofrequency and microwave electronics, thereby combining research with education objectives. The PI and the team will use ultracold sodium and lithium atoms trapped in two and three dimensions to investigate the thermodynamics of quantum gases. Sodium is a boson, a particle with integer spin, while lithium-6 with its half-integer spin is a fermion. Mixtures of bosons and fermions realize an important ingredient of the standard model of physics. Fermi-Fermi mixtures can mimic the behavior of electrons in high-temperature superconductors or the dilute neutron matter in the crust of neutron stars. The PI will embed impurities of one species into a host bath of the other, and thereby study the fate of impurities in a quantum bath, expecting the formation of polarons, dressed quasi-particles. For the first time, these polarons will be able to be imaged with single-atom resolution. The experiments address long-standing questions on the ground state of fermionic superfluids in the presence of spin imbalance and of Bose-Fermi mixtures, on the existence and nature of boson-induced pairing, and on the role of dimensionality. The research will lead to a better understanding of superfluidity and superconductivity. Precision measurements of thermodynamics and interparticle correlations enable the validation of novel theoretical tools. These can then be employed with confidence in other strongly interacting Fermi systems, relevant to diverse fields of physics: From studies of high-temperature superconductors in condensed matter physics, to the Coulomb gas governing chemistry, to the quark-gluon plasma of the early universe and the behavior of neutron matter in nuclear physics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Language is fundamental to human experience. For example, language allows humans to build deep social connections, teach each other new knowledge and skills – including accumulating knowledge across generations – and represent complex concepts in compact ways. This expands humans’ ability for complex reasoning. In recent years, advances in artificial intelligence (AI) have led to the emergence of large language models (LLMs), such as ChatGPT, which are transforming society. This project supports a workshop at a premier conference for interdisciplinary approaches to language science. The workshop brings together invited and contributed speakers who create a scientific dialogue on language and thought in minds and machines, including the relationship between language and complex cognition in both human minds and AI systems. Other benefits to society include innovative educational opportunities, including mentoring, that support workforce development for AI and other language technology sectors. It has long been proposed that language is critical for reasoning – that humans use words and linguistic structures for thinking. Others have contested this claim and instead proposed that language is primarily a communication system, not a thinking tool. Many specific questions arise from this ancient philosophical question, including (1) whether language and thought are supported by the same or distinct cognitive and brain systems, (2) if complex thought is possible without language, and (3) does knowledge of a particular language change how we think about the world? Given the rise of LLMs and other AI systems, both in cognitive science research and society at large, there is a critical need to understand whether, and if so how, these models can inform research on human language and cognition. This workshop brings together researchers across diverse fields, such as computer science, psychology, linguistics, philosophy, and anthropology to address these questions. Through interactive discussions and presentations, attendees explore the role of language in broader cognition, including how language science can inform research on AI models and how AI models can advance a scientific understanding of the language-thought relationship in humans. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Nontechnical description: Bismuth is both an element and a material that has attracted tremendous interest from scientific researchers throughout history. For example, it was the first metal whose Fermi surface was experimentally identified and its study has led to the discovery of quantum (e.g. Shubnikov-de Haas) oscillations. It is also deemed a ‘magic element’ by chemists as it has rare chemical properties allowing it to form compounds with a diverse range of nuclei. A few years ago, the PI’s group made the discovery that ultralow contact resistance can be made to transition metal dichalcogenide (TMD, e.g. MoS2) devices when Bi is deposited on them. Initial structural analysis revealed that Bi formed epitaxial structures on TMD, which was understood as a particular semi-metallic phase of Bi at the time the work was published. Nevertheless, further recent studies indicated that previous understanding might be mistaken, which motivated this research to solve key mysteries and advance scientific knowledge. The findings will lead to discoveries of new 2D forms of materials and enable low power, high-performance devices for both conventional and quantum computing. The project will provide lab experience to undergraduate students and outreach to high school and other students. Technical description: This project will systematically investigate the phase and structures that Bi forms at the 2D material interface under various controlled conditions and will characterize the electrical and optical properties of the resulting structures. A layer-by-layer characterization will be carried out to examine the interfacial properties for one layer and multiple layers, to identify if any transitions occur as layer thickness increases. The unexpected and unexplored phenomena of Bi phase formation on a 2D substrate have revealed a knowledge gap in the 2D research field. Together with the particularly interesting outcomes – low contact resistance, much better thermal & chemical stability, and unusually high doping – these studies will not only provide a deeper understanding of the interfacial phenomena, but will also inspire other investigations of materials formation on 2D templates, and may have significant impact into technologically important areas such as electrical contact formation on 2D devices, high temperature quantum spin Hall materials, etc. The study of novel material phases and their formation will open new research directions, enabling new technologies for a wide range of applications, including energy, catalysis and biomedical. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With this award, Professors Marc Hillmyer of the University of Minnesota, Janani Sampath of the University of Florida, and Zachary Smith and Bradley Olsen of the Massachusetts Institute of Technology are studying new polymer materials that can be used for the development of food packaging. Single-use food packaging represents one of the largest contributors to plastic waste in our landfills and our environments, and this project will combine innovative chemistry, high-throughput experimentation, and data science to develop innovation pipelines that will yield replacements for current packaging materials that have improved performance and a more sustainable end-of-life. This work will help to secure our food supply while simultaneously protecting our health and environment through the continued development of a robust chemicals industry. A key aspect of the innovation pipeline to be developed is human resources, so the project will focus on broad training for current and future scientists to build capacity in artificial intelligence (AI) and data science. Efforts will focus on introducing data science into general chemistry at the university and community college levels, reaching a broad range of future workers. These will also be transformed into a continuing education course designed to help workers transition to the economy of the future. With this award, Professors Marc Hillmyer of the University of Minnesota, Janani Sampath of the University of Florida, and Zachary Smith and Bradley Olsen of the Massachusetts Institute of Technology are studying poly(glycolic acid) (PGA)-based barrier materials that can be incorporated into multi-layer flexible packaging materials that are processable, degradable, and have good barrier performance. Currently, PGA is the leading candidate material for barrier packaging due to its high barrier properties and degradability, but it suffers from synthetic challenges and limits to its processability. The goal of this project is to develop a data-driven workflow that combines advances in synthesis with property prediction to discover new PGA materials that can overcome these limitations and yield new sustainable barrier materials. Specific aims of the project include 1) Synthesis of PGA with controlled architectures and the AI-guided design of molecular architectures for chemically similar polymers; 2) Establishing quantitative relationships between molecular structure, polymer processing, and material properties in PGA-based systems; and 3) Leveraging genetic algorithms to design and optimize packaging materials with tunable properties tailored to specific applications. Successful completion of proposal goals will enable the synthesis of sustainable polymers for a wide range of packaging applications while contributing to workforce training through curriculum development for community colleges and industry partners in polymer informatics. This Molecular Foundations for Sustainability: Sustainable Polymers Enabled by Emerging Data Analytics (MFS-SPEED) award is co-funded by the NSF through the Division of Chemistry (CHE), the Directorate for Mathematical and Physical Sciences (MPS), the Division of Chemical, Bioengineering, Environmental and Transport Systems (CBET), the Directorate for Engineering (ENG), and the Division of Innovation and Technology Ecosystems (ITE) in the Directorate for Technology, Innovation, and Partnerships (TIP). Additional MFS-SPEED funding is provided by Procter & Gamble, PepsiCo, Dow, BASF, and IBM. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The increasing global demand for metals is being driven by the transition to renewable energy technologies (like solar and wind) and energy storage solutions (like batteries). Mineral deposits that are acidic and sulfur rich are called “high-sulfidation epithermal deposits.” They are formed from magmatic-hydrothermal fluids and are important sources of critical and precious metals such as copper, antimony, arsenic, gold, and silver. Despite their economic significance, the geological and geochemical controls on whether these deposits are silver-rich or silver-poor are not well understood. Because silver is often recovered as a by-product in these deposits, we need to improve our ability to predict where high-grade silver zones will occur. This is essential for progressing from exploration to economic viability and meeting growing industrial demand for silver in solar panels and batteries. This team will use geochemical and age information to evaluate different models for the origin of silver-rich deposits and the timing of silver mineralization in the newly discovered world-class Filo Del Sol deposit in the San Juan province, Argentina. Their findings at Filo Del Sol have the potential to benefit mineral exploration strategies in the U.S. and globally. In addition, students will learn technical skills needed for employment in the mining sector and it will also raise awareness for professional career paths in mineral resources. Previous studies of high-sulfidation epithermal deposits have primarily focused on the physicochemical conditions responsible for Au and Cu enrichment, while relatively few have explored the origins and timing of silver enrichment in these deposits. This project addresses this knowledge gap by investigating the nature and spatiotemporal distribution of Ag-rich ore mineralogy at Filo Del Sol, Argentina. The main objectives are to (1) characterize the elemental and isotopic compositions of both silver-rich and silver-poor ore mineral assemblages and their associated hydrothermal alteration minerals, and (2) determine the relative and absolute timing of silver enrichment within the deposit. In addition to conventional methods, this study will be the first to apply in-situ sulfur isotope and trace element chemistry, collected simultaneously from sulfides, sulfosalts, and sulfates, alongside in-situ 40Ar/39Ar geochronology of alunite and other potassium-bearing minerals, in high-sulfidation epithermal deposits. Ultimately, this project aims to constrain the timing and physicochemical conditions of the hydrothermal fluids responsible for Ag enrichment in this deposit. These findings will have applicability to the numerous other high-sulfidation epithermal deposits in the U.S. and globally. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Geoscientific computational models are used to predict a wide range of natural processes such as weather, water supply, air pollution, eruptions, floods, and tsunamis. Progress in geo-modeling is held back by the need for geoscientists to also acquire expertise in computer science. The project will introduce a novel modeling workflow to overcome this hurdle. This project supports the development and community adoption of a symbolic equation-based modeling system. This system separates automates the numerical processing optimization so geoscientists can focus on the equations that describe natural processes. This system also advances the use of artificial intelligence in geosciences for simplifying model reduction and parameterization. The proposed work consists of three thrusts involving 1) community organization, 2) model development, and 3) de-centralized model management and education. A series of workshops at major international geoscientific meetings domestically and abroad will help define project priorities. Models will be documented on a dedicated website, run by a decentralized governance system and supported with interactive educational experiences to transition to a user-supported network for long-term growth. Geoscientific computational models simulate natural processes such as weather, water supply, and air pollution; for analyzing risks of volcanoes, floods, and tsunamis. The proposed project will introduce a new process of geoscientific model development, where model components and their interrelationships are specified as a system of equations that a compiler automatically transforms into a computer model. By separating the model design (the equations) from model implementation (the code compiler), geoscientists can focus on building equation systems that represent their areas of expertise, greatly increasing the participation in geoscientific modeling. This system will also provide an ideal base for integrating AI model reduction and parameterization into the geosciences. Project activities are divided into three thrusts. Thrust 1 will convene a series of workshops to create a shared roadmap for model development at major international geoscientific meetings domestically and abroad. Thrust 2 will expand on the types of systems that can be studied with equation-based models by implementing model components and capabilities as prioritized by project members and workshop participants. Model capabilities will be documented on a dedicated website. Thrust 3 will implement a decentralized governance system and interactive educational experiences to transition to a user-supported network of equation-based modelers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

Amblyopia is a prevalent form of visual disability that arises during infancy and early childhood when inputs to the visual cortex from the two eyes are poorly balanced (for example, by misalignment of the eyes, asymmetric refraction, or blocked vision of one eye). Characteristics of amblyopia are poor visual acuity in one eye, and an attendant loss of depth perception. The need for improved treatments for amblyopia is widely acknowledged. Animal studies over the past 50 years have uncovered the pathophysiology of amblyopia. It is well documented that temporary monocular deprivation alters the strength of synapses in primary visual cortex that renders cortical neurons unresponsive to stimulation of the deprived eye. However, much less is known about the mechanisms that serve recovery from amblyopia. We recently discovered that temporary local anesthesia of the retina sets in motion changes in the brain that enable complete recovery from the effect of early life monocular deprivation. Our objectives are to uncover the mechanism for how this recovery occurs, and to determine if this knowledge can be translated into new and better treatments for amblyopia.

NSF Awards · FY 2025 · 2025-09

Demonstrating practical quantum advantage for problems relevant to science, engineering, and society is a central challenge in quantum information science. To address this challenge, the Open Stack Rydberg Atom Quantum Computing Laboratory (ORAQL) project will combine next-generation neutral atom logical quantum processing technology and a cross-disciplinary stack. The stack includes a digital twin model, comprising the virtual laboratory component of the project, that will be shared with the community to foster broad national participation in discoveries using ORAQL at the forefront of quantum algorithm development. ORAQL will additionally advance education and workforce development with a specific focus on the neutral atom quantum computing architecture, including digital twin technology as a cutting-edge virtual tool. ORAQL targets next-generation neutral atom logical quantum processor cores capable of circuit depths of 1-100 megaquops (1 megaquop = million quops or quantum operations) on as many as 400 logical qubits, to be developed within a cross-disciplinary stack consisting of intermediate representation libraries for hardware controls, quantum circuit compilers, tools for quantum error correction (QEC) including decoders, and the ability to explore a broad range of quantum algorithms at the highest level. Included in the cross-disciplinary stack will be a digital twin that accurately models system performance, identifies failure mechanisms, and validates improvements, connecting all levels of the stack from quantum algorithm resource estimation down through the QEC and compilation layers to the quantum processor. Parallel hardware demonstrator efforts target validation of technology drivers: advanced logical qubit performance, fast qubit readout, scalable photonic control, dual-species qubit encoding, and photonic interconnects. Theory efforts will develop new approaches to QEC, improve resource requirements for practical quantum algorithms, decoding and optimize circuit compilation. Education and workforce development efforts include workshops and hackathons, quantum hardware experience kits, and K-12 professional development around ORAQL-specific classroom modules. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Precise spatiotemporal regulation of gene expression is fundamental to biological function. Polycomb- group proteins (PcGs) are critical regulators that establish and maintain repression of developmental genes. Polycomb proteins are conserved across multicellular eukaryotes and are essential in mammals, in which their deletion causes embryonic lethality or developmental defects. However, how the Polycomb system drives repression of target genes and how cell type-specific Polycomb genes are selectively derepressed during development remain unknown. PcGs form two distinct complexes, Polycomb repressive complex 1 and 2 (PRC1 and PRC2), which modify chromatin and mediate 3D interactions between Polycomb-bound regions. PcG binding and histone modifications alone are insufficient to explain Polycomb repression, suggesting a functional role for 3D chromatin interactions. In particular, long-range looping interactions between distal Polycomb loci appear to be functionally important, as they are observed in both flies and mammals and disappear during differentiation. Yet, the dynamics of these interactions, including whether they are frequent enough to drive gene silencing, and how they contribute to changes in gene expression during development remain unclear. The proposed research will examine the dynamics and function of long-range Polycomb interactions in gene repression by combining cutting-edge super-resolution live-cell imaging, genomics, polymer simulations, and perturbations. Existing methods relying on cellular fixation cannot capture the inherently dynamic nature of these processes. I will therefore directly visualize Polycomb loops, target genes, and nascent transcription. Aim 1 will address whether the interactions are stable and frequent enough to confer function, determine chromatin organizing principles that drive loop formation, and directly test the impact of abolishing Polycomb looping on gene expression. In Aim 2, I will determine whether changes in long-range Polycomb looping dynamics correspond to gene activation by simultaneous imaging of Polycomb target genes and nascent transcription. These studies will be complemented with genomics approaches to address genome-wide features that correlate with selective derepression of developmental genes. Together, the proposed research will define the functional relationship between distal Polycomb interactions and transcriptional regulation, revealing whether long-range 3D chromatin interactions represent a key mechanism of Polycomb-mediated gene repression. These studies will inform our understanding of how cells are able to precisely control gene expression during development and provide a basis for future studies to correct disrupted Polycomb regulation in disease. The proposed research is designed to provide the necessary conceptual and technical training to achieve my goal of becoming an independent PI at a research institution. Research training will be conducted in parallel with career development training to develop necessary skills to establish and lead a research lab, including training in the responsible conduct of research, scientific communication, leadership, and lab management.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Despite their central role in protein synthesis, the rates of ribosomal initiation kinetics on different mRNAs and across various tissues remain largely unknown. Understanding the cellular regulation of initiation kinetics and its dysregulation in diseases can significantly enhance our fundamental knowledge of cellular biology and improve modern therapeutics. However, the lack of methods to directly measure initiation across cell types, combined with the vast mRNA sequence space and the complex, cell-specific interactions it supports, results in an intractable complexity. This hinders our ability to answer several central questions, including: 1) How to predict transaltion initiation rates from mRNA sequence? 2) How do initiation rates of individual mRNAs vary between cell types? 3) To what extent does initiation rate determine protein levels in cells? 4) What are the initiation rates at alternative and small ORFs translation initiation sites, and what is the protein encoding capacity of the genome? This proposal outlines a five-year research plan to address these challenges and questions by developing a measurement system that will measure the kinetic parameters that control translation initiation. These paramters will be measured using a cell-free system reconstituted from cell-specific proteomes, which will be titrated with large mRNA libraries, and followed by ribosome footprinting and sequencing-based quantification of ribosomes locked on start codons. This functional genomics platform, termed MIT-seq, was recently developed by us for bacteria and this proposal will adapt to human cells. It will be benchmarked using mRNA libraries includes the entire human transcriptiome and compared to other, massively parallel reporter assays and existing data from the litrature (Aim 1). Subsequently, we will measure the initiation affinities unprecedently large (1010) mRNA libraries to explore variations in initiation kinetics between differentiated cells, such as kidney cells and neurons (Aim 2). Finally, we will examine shifting landscapes and dysregulation of intiation kinetics and their functional consequences between healthy and diseased cells using Fragile X Syndrome, a disease caused by altered levels of the translation initiation regulator FMR1 protein, as a model (Aim 3). To achieve these aims, the candidate will leverage his unique expertise in the molecular biology of translation initiation developed during his PhD studies and the assays developed during his current postdoctoral fellowship at MIT. To transition from bacterial systems to the molecular biology of human cells, the candidate has assembled an outstanding advisory team, including relevant experts who have agreed to mentor, collaborate, and provide resources for the project's success during its training phase (K99). Upon establishing Aim 1, the candidate will pursue an independent career (R00) focusing on Aims 2 and 3, while working towards the long- term goal of developing functional genomics tools and understanding the design principles, mechanisms, and evolution of mRNA translation initiation across tissues and organisms.

NSF Awards · FY 2025 · 2025-08

This project seeks to better understand what chemical species result from the oxidation of non-methane volatile organic compounds. Model-informed chamber studies will be conducted during which the reactivity of organic peroxy radicals will be carefully controlled and monitored. A better understanding of volatile organic compound oxidation in the atmosphere will lead to better predictions of the formation of secondary atmospheric species such as ozone, formaldehyde, and secondary organic aerosol, species that contribute to degraded air quality. The major scientific objectives of the project are: (1) To better understand the formation mechanism and yields of these key secondary species, across the range of organic peroxy radicals (RO2) conditions found in the atmosphere; and (2) To understand the extent to which these secondary species are accurately predicted using state-of-the-art chemical mechanisms or approximated from measurements of extreme RO2 conditions, in which RO2 reacts only with NO or only with HO2, simplifying the product distributions considerably. Chamber experiments will cover a number of model volatile organic compounds (isoprene, monoterpenes, aromatics, and others), across the full range of RO2 conditions found in the global atmosphere, a much wider range than previously studied. The project will support the training of both graduate and undergraduate students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The human brain comprises a remarkable variety of cell types that collectively support sensation, cognition, and behavior. This diversity arises not from differences in genetic code, but from how DNA is physically organized and regulated in each cell. Understanding the 3D structure of the genome – and how it controls which genes are active in different brain cells – is essential for advancing neuroscience, regenerative medicine, and genome engineering. This project will use AI to investigate how chromatin accessibility, spatial DNA structure, and gene activity work together to establish cell identity in the human brain. The team will build new AI tools to reconstruct the three-dimensional organization of chromosomes from single-cell experiments and to simulate how changes in genome structure affect gene expression. These efforts will create a detailed map of chromatin structure across brain cell types and provide computational models to explain how genetic information is interpreted differently in different cells. The results will support basic research on brain development and disease, and will help guide future interventions based on genome editing. The project will also generate community resources such as open-source software and public data releases, and will provide training opportunities for early-career researchers. This research brings together computational biophysics, machine learning, and genomics to develop a unified generative framework for modeling chromatin structure and function. The first aim focuses on developing ChromoGen2, a scalable, high-resolution architecture for single-cell 3D genome structure prediction using only DNA sequence and chromatin accessibility data. By incorporating architectural innovations that address long-standing computational constraints in structural genomics, ChromoGen2 enables full-chromosome inference at 5-kilobase resolution. This capability will support the construction of the first high-resolution atlas of single-cell 3D genome structures across 188 human brain cell types, offering an unprecedented view of spatial genome organization in the brain. The second aim is to develop CRAFT, a multimodal DNA language model that integrates DNA sequence, chromatin accessibility, 3D structure, and gene expression into a unified generative framework. Unlike existing models, which are limited to fixed input-output mappings, CRAFT will support flexible, bidirectional inference and cross-modal prediction, allowing any modality to be reconstructed from others. This will enable causal testing of regulatory hypotheses, such as how 3D structure influences expression, and lay the groundwork for rational sequence design in regulatory genomics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-08

Imaging cytometry provides biomedically important morphological features of cells or tissues via high- speed acquisition hardware and fast image processing algorithms. Imaging cytometry has found applications ranging from rare cellular event detection to drug screening. Despite significant advances in faster and more multiplexed imaging sensors, the imaging cytometry’s throughput is often limited by the speed of electronic hardware. In order to improve throughput further, images can be acquired in an “optically compressed” form such that more information can be transferred beyond the existing electronic hardware bottleneck. We and other groups, have previously demonstrated sparsity-exploiting compressive imaging with random under-sampling 4. Recent advances in machine learning, however, suggest that superior optimized compressive imaging schemes may be derived by treating the front-end optics as part of the down-stream image processing pipeline in a neural network algorithm 5. Along similar lines, in the Wadduwage Lab we are currently developing a general learning- based microscopy technology, called differentiable microscopy (δμ). In δμ, we consider the front-end optics and the decompression algorithm as a differentiable auto-encoder, with the assumption that we can find a lower dimensional feature space, specialized for a class of images. This lower dimensional signal can be acquired with lower bandwidth detectors with the front-end optics working as an image compressor. A promising approach to implement optical compression for δμ, is through the use of optical diffractive networks (ODNs). ODNs have been demonstrated for: non-compressive imaging, all-optical image classification, and hybrid optical and electronic image classification. Most current ODN demonstrations, however, are for terahertz wavelength applications while most biomedical imaging tasks require visible light. For ODN to operate efficiently with visible light, optimal wavefront manipulation will require lithography with precision substantially better than visible wavelength. Implosion Fabrication (ImpFab), a low-cost, on-demand facile 3D fabrication technology with tens of nanometer resolution has recently been invented in the Boyden Lab. As a first demonstration of δμ relevant for biomedical applications, we will design and construct high throughput image cytometers with quantitative phase contrast that are powered by visible ODNs fabricated with ImpFab. We expect approximately two orders of magnitude voxel throughput improvement over the state-of-the-art.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to an infection. Majority of sepsis is bacterial, and is typically accompanied by bacteremia, i.e., the presence of bacteria in blood at 1-104 CFU/mL. Each year, sepsis kills over 10 million people globally, and is the most expensive condition treated in US hospitals costing over $60 billion annually. It is a medical emergency requiring early recognition and immediate treatment, but the lack of rapid and actionable tests leads to delays in recognition and treatment of sepsis, non-optimal treatment, and overuse of broad-spectrum antibiotics resulting in emergence of drug- resistant pathogens. We propose an integrated “DIMS-Raman” platform to rapidly isolate and analyze bacterial cells from blood samples by machine learning-enabled Raman spectroscopy within approximately 1-2 h to provide actionable information to guide treatment in a timely manner. The proposed system combines a novel yet simple fluidic platform called Density-shift Immunocapture Separation (DIMS) that enables direct separation of microbial cells from whole blood, with Raman spectroscopy – an analytical technique that generates molecular fingerprints of targets from the inelastic scattering of light in a sample – combined with machine learning-based spectral analysis and classification. We envision that target cells isolated by DIMS are concentrated into micro/nanoliter volumes for direct microscopic observation and Raman spectroscopy at the single cell level, enabling culture-free enumeration, and machine learning-enabled identification of bacterial strains and assessment of antibiotic resistance. Our preliminary study using DIMS was able to isolate, concentrate by 10,000x, and image salmonella (~30 CFU/mL) at the single cell level from blood within 3 h. Bacterial cells have unique Raman signatures, which, using machine learning based spectral analysis have enabled differentiation of the 30 most common sepsis related pathogens (including methicillin resistant and susceptible S. aureus) with a 99% classification accuracy using just 10 cells. Moreover, our work demonstrated applications in heterogeneous mixtures of bacteria species and blood cells in liquid droplets with 92% accuracy. In addition, we further demonstrated antibiotic co-incubation free susceptibility testing across the four major anti-tuberculosis drugs with 98% accuracy. The proposed work aims to develop an integrated DIMS-Raman platform for sepsis by demonstrating integrated isolation, concentration, detection, and Raman analysis at the single cell level of the most common sepsis-causing bacteria with a sensitivity of 1 CFU/mL from whole blood within 1-2 h. If successful, the proposed work could eventually lead to a platform capable of returning pathogen type, concentration, and antibiotic susceptibility of clinically-relevant pathogens from blood without relying on culture, thus transforming sepsis detection and informing appropriate antibiotic treatment in a timely manner, saving human lives and reducing the cost of care.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract Pancreatic ductal adenocarcinoma (PDAC) is a devastating and lethal disease associated with peripheral tissue wasting that is seen in most patients. This progressive wasting condition affecting skeletal muscle as well as fat and other tissues is referred to as cancer cachexia. PDAC patients with cancer cachexia have lower median survival than patients without cancer cachexia. There are currently no approved treatments for this disorder, including nutritional interventions. The Vander Heiden lab in a previous publication identified that the autochthonous mouse model of PDAC driven by KRAS activation with p53 deletion in the acinar cells of the pancreas was sufficient to drive cancer cachexia-induced muscle atrophy. These mice exhibited pancreatic enzyme insufficiency that was identified by the abundance of amino acids and fatty acids within the stools of cachexic KPC mice, indicating a lack of nutrient absorption. One of the key questions unanswered in the cancer cachexia field is whether the process of cancer cachexia serves to supply nutrients to the tumor to help it grow or it functions to help preserve the host. It is unknown where amino acids released from protein degradation in the muscle are going and what their purpose is. One of the organs in the body that requires an abundance of amino acids is the liver, as amino acids can be used to fuel gluconeogenesis. The rate-limiting enzyme for gluconeogenesis is phosphoenolpyruvate carboxykinase (PEPCK), which is upregulated in cancer cachexia by the IL6/JAK/STAT pathway in the liver. Therefore, we hypothesize that IL6/JAK/STAT signaling induces PEPCK and gluconeogenesis in the liver to promote cancer cachexia in primary and metastatic PDAC tumors. I will test this hypothesis in aim 1 by determining the contribution of PEPCK and gluconeogenesis in the liver to cancer cachexia and vice versa. Then in aim 2, I will study the role of IL6/JAK/STAT signaling on gluconeogenesis and metabolism in the livers of cachexic mice. Then in aim 3, I will determine whether cancer metastasis accelerates cachexia through promoting gluconeogenesis. The outcomes of this study will improve our understanding of whole-body metabolism and has therapeutic potential to facilitate the development of drug targets for cancer cachexia and/or PDAC.

NIH Research Projects · FY 2026 · 2025-08

LOCAL AND GLOBAL SELECTIVE FORCE WITHIN MICROBIOMES The human microbiome harbors a large capacity for within-person adaptive mutations. Commensal bacterial strains can stably colonize a person for decades, and during this time billions of bacterial mutations are generated daily. Adaptive mutations emerging during colonization might be driven by selective forces that are new to urban industrialized societies, vary across individuals, or vary across times within an individual. These changes could alter the impact of strains on the immune system, the metabolism of particular nutrients or drugs, and the stability of the microbiome to invasions or perturbations. Despite this potential, still little is known about the extent of evolution within human microbiomes or its interplay with ecological forces. This knowledge gap emerges from limitations of traditional approaches; metagenomics does not provide the resolution needed to accurately identify de novo mutations, and model animal microbiomes have relatively limited potential for adaptation due to their shorter lifespans, smaller microbial population sizes, and constrained environmental complexity. To overcome these limitations, my lab studies in vivo evolution using high-throughput culture-dependent methods. Using this approach to we have discovered evidence that, even in the absence of antibiotic treatment, adaptive de novo mutations reach high frequency within healthy people. However, it is unknown if such adaptation is common across species or capable of spreading person-to-person. This proposal outlines a long-term strategy to develop the intuition, rules, and exceptions regarding ongoing adaptation and selective forces within human microbiomes. First, we will use a culture-dependent genomic approach to characterize within-person evolution over a dozen species in human microbiomes, including residents of the skin, vagina, and large intestine. We will characterize niche traits that predict the balance of neutral and adaptive forces across species, as well as elucidate the role of person-specific selective forces in evolution and initial engraftment of migrating strains. Second, we will characterize across-person evolution using PHLAME, a computational platform for phylogenomics we developed that leverages rapidly accruing public metagenomic data. We will identify bacterial strains with recent success within and across human environments. We expect to uncover principles underlying adaptive evolution of commensals within and across humans and to lay the groundwork for a microbiome framework that integrates both evolutionary and ecological forces, which will pave the way towards more successful microbiome-targeted therapies.

NSF Awards · FY 2025 · 2025-08

This award will partially cover the costs of an international meeting “Physics Meets Genomes Conference and Summer School” to be held at Institut d'Études Scientifiques in Cargèse, Corsica, France, during June 2025. The award will provide funding to support international travel of speakers, students, and junior scientists from the USA, as well as the work to develop the School and Conference. The School and Conference will bring together experts from France, the USA and other leading international researchers to foster knowledge dissemination, intellectual exchange, and training a new generation of students and early career researchers in the Physics of Living Systems. Recent years have seen an explosion of interest in understanding 3D genome architecture and dynamics in living cells and their implications for biological function. This has been made possible by the advent of technologies that provide unprecedented information regarding the spatial organization of genomes, their variations between cell types and species, and their temporal dynamics. This, in turn, has led to a flowering of theories, combining concepts from molecular biophysics, polymer science, and machine learning to create quantitatively accurate frameworks for confronting hypothesized mechanisms with experimental observations. The summer school for graduate students will provide hands on instruction from the basics of chromosome structure and function through more complicated aspects of research being explored in the field today. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.