Grants

NSF

With the support of the Macromolecular, Supramolecular and Nanochemistry program in the Division of Chemistry, Professor YuHuang Wang of the University of Maryland, College Park, is developing innovative chemical strategies of using programmable DNA templates and laser-based refinement to guide the precise placement and structural control of organic color-centers. Organic color centers are atomic-scale defects that can be engineered onto the surfaces of single-walled carbon nanotubes, which are tiny cylinders made entirely of carbon atoms. Each color center can emit photons—the elementary particles of light—one at a time, even at room temperature. These sources of “quantum light” are essential building blocks for future technologies in secure communication, bioimaging, and molecular sensing. The project will provide students with hands-on experience in quantum nanochemistry and incorporate nanoscience principles into teaching and educational initiatives with broader public. The interdisciplinary nature of the project, which combines chemistry, photophysics, and nanoscience, will provide unique training opportunities to cultivate the next generation of scientists and engineers. In this project, a DNA-programmed photochemical platform for the deterministic synthesis of organic color centers (OCCs) on single-walled carbon nanotubes will be developed. Spatially encoded DNA scaffolds will define reactive sites along the nanotube surface with nanometer precision, enabling the formation of isolated OCCs and OCC pairs with controlled spacing and orientation. This strategy could provide a level of control that is unattainable with currently existing methods. The prepared OCC pairs will then be refined through localized photothermal annealing to tune their atomic structure and coupling strength, guided by in situ hyperspectral imaging capable of resolving OCCs at the single defect limit. This approach will allow for fundamental studies of OCCs with controlled defect-defect interactions, offering a scalable synthetic pathway toward quantum materials with programmable optical properties. 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

This project will study the puzzling behavior of a type of star called a white dwarf. These are dense remnants of stars like our Sun. Some white dwarfs pulse with light, getting brighter and dimmer over time. But as they cool, these pulsations stop abruptly - and scientists don’t fully understand why. Recently, space telescopes like Kepler and TESS have discovered strange behavior in some of these stars, such as sudden outbursts and random changes in brightness. This project will use computer models to understand what causes these phenomena and why pulsations cease as white dwarfs cool. Alongside the research, the project will train two graduate students and involve undergraduates in hands-on astrophysics. Some of these students will explore real telescope data in the classroom and contribute to research projects. A study will track how these experiences affect students’ views of science and their academic paths. The investigator will conduct a comprehensive theoretical investigation into the cessation of pulsations and the origin of outbursts in cool DA (hydrogen-atmosphere) white dwarfs near the empirical red edge of the instability strip. The project combines large grids of evolutionary models generated using MESA, WDEC, and ISUEVO, with linear adiabatic and nonadiabatic pulsation calculations via GYRE and GNR1-based codes. The work will evaluate mode growth rates, explore sensitivity to convection prescriptions, and analyze amplitude coherence as a function of stellar mass and effective temperature. A key innovation of the project is the inclusion of nonlinear three-mode resonant coupling calculations to test whether these interactions can suppress observable pulsations or trigger episodic outbursts. The modeling will explore amplitude saturation, limit-cycle behavior, and energy deposition mechanisms that could reproduce observed features such as broadened power spectra and burst-like luminosity increases. The project also includes integration of white dwarf variability research into undergraduate astronomy coursework and a longitudinal study of student learning outcomes. 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

Robotic hands with human-like dexterity are urgently needed to address multiple challenges facing our nation and society, including enhancing productivity in manufacturing and improving quality of life. According to Deloitte, by 2028 labor shortages could jeopardize more than $450 billion of U.S. GDP in the manufacturing sector. Meanwhile, over 400,000 Americans live with upper limb loss, and more than 20 million people struggle with daily activities due to limited mobility. While automation has the potential to alleviate these pressures, current robotic solutions have not been effective. Robotic hands have yet to gain widespread adoption in factories, and upper limb prosthetics face the highest rates of abandonment of any assistive device. To address these challenges, this project brings together a diverse team of university, industry, and government participants to develop, pilot, and create sustainable pathways for robotic and prosthetic hands that are bio-inspired, feature all-over sensing and intelligent control, and are customized to the needs of the end-user. This project has four specific goals for impact: (A) ease labor shortages in a manner that benefits both manufacturers and employees, (B) prepare new learners for a future of work that includes dexterous robotics, (C) ensure that small and medium manufacturers have access to dexterous robot hands for high mix / low volume applications, and (D) enable individuals with disabilities to have greater independence to meet their personal goals. Research thrusts to achieve these goals emphasize (1) bioinspired sensors, skeleton, and skin designed for customizability, reliability, and manufacturability, (2) bioinspired fine control with intrinsic muscles for dexterity in a lightweight and compact package, and (3) a software pipeline for custom robot hand design for best end-user experience, performance, and reliability. Research thrusts are accompanied by development efforts, customer outreach, and educational activities to ensure that impact goals can be met with a sustainable solution. A hand that is humanlike and dexterous can enable people to do dangerous work from a safe, remote location or to provide expert assistance anywhere in the world. A robust solution to robot dexterity will see application in homes, workplaces, farms, helping individuals to age gracefully in place, small business owners manage labor shortages and upscale jobs to improve quality of life. 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

This convergent and translational research project will develop a swarm of interlocking robotic tiles able to transport goods and equipment over difficult and uncontrolled terrain. This project addresses the growing impact of natural disasters, which cause billions in annual damages. A key challenge in recovery efforts is the difficulty in extricating debris from the disaster site and moving equipment into the affected areas. The envisioned system that the researchers will develop will enable the on-demand formation of an all-terrain conveyor system to mitigate these difficulties and make the work of first responders safer and more efficient while enabling municipalities to respond to and recover from disasters more quickly. The system will also alleviate challenges faced in vertical construction and construction in confined spaces, making these activities more efficient during day-to-day operations. The researchers draw inspiration from both fire ants and slime molds. Fire ants are often observed linking their bodies to form rafts in flooded conditions, showing how self-assembly behaviors help swarms adapt to difficult environments. Slime molds offer a compelling behavioral model for decentralized coordination of transport tasks, such as the ones the robot tiles will undertake in disaster scenarios. The work towards realizing a fully autonomous robotic tile swarm builds upon efforts during Phase 1 of the project and will involve maturing the algorithms and hardware to conform to user needs. The researchers will adhere to principles of human-centered design to identify how the system can best fit alongside existing means and methods and will employ standard design and engineering procedures to realize the hardware-algorithm system. The overall deliverable of this project will be a full-stack realization of a user-focused robotic self assembling system that operates based on network growth principles observed in nature. 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

Mitigating corrosion is a grand challenge that costs the United States over half a trillion dollars annually. Current corrosion control measures, which mainly rely on chemical coatings, often come with high cost and risks to human and environmental health. Microorganisms play key roles in corrosion, in which they can either accelerate or inhibit corrosion of metal surfaces. In this project, the researchers will develop a biological coating system that can be applied for corrosion control of civil infrastructure. This bio-inspired coating design takes advantage of naturally occurring microorganisms that strongly inhibit corrosion. By harnessing the power of microorganisms and microbial biofilms, the biological coating developed through this project will provide long-lasting protection against corrosion to many types of metal-based infrastructure, improving their resilience. To develop this biological anti-corrosion coating, the researchers hypothesize that both the chemistry and microbiology of the coating material need to be deliberately designed and fabricated. This biotechnology development also requires co-production with a convergent team of interdisciplinary academic researchers and experts from industry and government. To accomplish these goals, this Phase 2 project will (1) develop a scalable prototype of the microbial coating system through accelerated technology development and maturation through partnerships, and (2) build a sustainability plan including trust building with potential end-users of the biotechnology. Both objectives will be carried out through an iterative and collaborative approach between the academic, industry, and government project partners, including experts in environmental and civil engineering, mechanical engineering, synthetic biology, polymer chemistry, mathematics, and advanced manufacturing. 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

The SequestStar vision is to develop an economically viable biomanufacturing process that captures carbon dioxide from the atmosphere. The SequestStar process uses specialized microalgae to strip carbon dioxide from the air and calcium from brine (concentrated salt water) to form calcium carbonate. Precipitated calcium carbonate (PCC) is an economically valuable product used in multiple industries including pharmaceuticals, food and beverage, paper, plastics, and building materials. SequestStar will support these industries by providing alternative sources for PCC. In addition, the SequestStar microalgae create compounds that are valuable for human health, enhancing the economic viability of the process and public well-being. This project also will contribute to national water security by using waste brine produced by desalination drinking water plants – transforming the waste streams of these plants into a source of economically valuable products. Using SequestStar PCC in concrete for coral and oyster habitat restoration could provide new materials needed to help counteract ecosystem degradation and species extinction. This Convergence Accelerator program will significantly advance the SequestStar technology down the path toward commercialization. The SequestStar process is inspired by whiting events in lakes during which precipitated calcium carbonate (PCC) forms when the pH of the water rises in response to microalgal growth. By mimicking the geochemistry of whiting events using industrial bioreactors and brine from desalination plants, SequestStar will create PCC and microalgal products that support human health. Using solar energy to drive the process, the SequestStar technology will be designed so that these products are economically viable. As part of this effort, the SequestStar team will create an Input-to-Product pilot system, test industrial scale components, simultaneously optimize microalgal bioproducts and PCC production, conduct market research, and techno-economic analyses, and develop a Front-End Engineering Design of an industrial-scale facility. Advances in fundamental knowledge and innovations will occur related to photosynthetic carbon assimilation and geochemistry within high-pH fluids and control of calcium carbonate precipitation using brine. Notably, the integration of life cycle analysis concurrent with design of the biomanufacturing process will enable design decisions, providing a model for development of new biomanufacturing processes. 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

Modern AI & robotics systems, such as general-purpose humanoid robots, must make intelligent decisions in real time, in unstructured environments. At the heart of these capabilities lies a fundamental problem: How can we compute optimal actions when such robotic systems are governed by highly complex dynamics (nonlinear, even discontinuous)? Traditional optimal control tools, while powerful, often fall short—they can be slow, unreliable, or rely on overly simplified assumptions about the real physics. This project aims to advance a promising category of methods known as Sampling-Based Optimal Control, which has recently gained popularity due to its flexibility (can easily handle complex systems), scalability (can leverage massively parallel computation on GPUs), and empirical success in solving complex robotic planning and control problems. However, these methods currently lack a solid theoretical foundation and systematic design principles. This project will fill that gap by developing new mathematical frameworks to understand, analyze, and improve these method—eventually leading to more reliable, efficient, and intelligent decision-making methods for real-world robotic and autonomous systems. By bridging theory and practice, this work supports NSF’s mission to promote transformative research in AI & robotics, and has the potential to impact a wide range of fields where autonomous systems must operate reliably and effectively in the real world. Optimal control for complex nonlinear and contact‑rich systems is notoriously nonconvex and often discontinuous, rendering classical optimization tools computationally burdensome and prone to suboptimal local minima. Sampling‑Based Optimal Control (SBOC) has emerged as an attractive alternative because its stochastic trajectory rollouts handle severe nonlinearity, discontinuities, and intricate cost landscapes while exploiting GPU‑based parallelism; it now underpins path planning, robotic control, and model‑based RL. Yet SBOC remains largely empirical: there is a lack of principled guidance on parameter tuning, sampling schedules, and, crucially, theoretical guarantees of convergence or sub‑optimality. This project closes these gaps through three coordinated thrusts. Thrust 1 develops asymptotic and finite‑time convergence theories that characterize when SBOC attains global optima and how performance scales with algorithmic and system parameters. Thrust 2 translates these insights into new, more efficient algorithms via automated hyper‑parameter optimization and a diffusion‑style annealing strategy that accelerates exploration while preserving convergence. Thrust 3 couples the resulting controllers with learned value functions, nominal policies, and dynamics models, yielding a powerful subroutine for model‑based reinforcement learning that unites the strengths of control and learning. The framework will be validated on demanding robotic benchmarks, including humanoid whole‑body locomotion and dexterous manipulation through extensive real hardware experiments. 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

This grant supports a two and half day interdisciplinary Convergence Workshop on the Mechanics of BioNetworks, MechNet’26, which will take place at the University of Colorado Boulder, 11-13 May 2026, bringing together approximately 40 senior speakers and a broad group of about 30 early-career researchers in biophysics, mechanobiology, and mechanics. The grant provides funding for travel awards for researchers, including Ph.D. students and postdoctoral fellows, to facilitate participation and participation. The workshop will feature keynote lectures, invited talks, flash presentations, poster sessions, and structured breakout discussions centered on the unifying concept of networks. These activities are designed to foster sustained cross-disciplinary interaction and to identify shared challenges and opportunities at the interface of biology, mechanics, and physics. The specific objectives of this workshop are: 1) to advance the scientific foundations of network mechanics and shape a coherent research agenda for multiscale, adaptive, and living networks, and 2) to promote interdisciplinary collaborations, professional networking, and career development for early-career scientists. MechNet’26 focuses on the unifying concept of networks to bridge the gap between biophysics, mechanobiology, and mechanics. By bringing together leading theorists, experimentalists, and computational scientists, the workshop will identify unifying principles, critical open problems, and promising methodological directions in the mechanics, dynamics, and adaptation of biological and soft-matter networks. The intellectual merit lies in advancing these scientific foundations and fostering integration across disciplines to guide future NSF investments in convergence science, most notably between active matter physics, mechanics, and mechanobiology. The workshop will have broad impacts on workforce development, interdisciplinary education, and community building by engaging and broadening participation to generate momentum in the field. Primary outcomes will include a community-informed white paper with actionable recommendations, a peer-reviewed review and perspective article, and a potential special journal issue to consolidate emerging results and strengthen this community. 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.

City of Seattle — Neighborhood Matching Fund

A two and one half hour presentation and facilitated conversation on the subject of White Privilege will be held on Thursday, January 26, 2017 from 6:00-8:30 pm at the Mount Baker Community Club, 2811 Mt. Rainier Drive South. The goal is to help participants become more comfortable with talking about racism while exploring mutual solutions in working for greater social justice and equality.

Mount Baker Community Club

The Mount Baker Community Club will host a three-hour facilitated workshop about race on Sunday, November 18, 2-5pm, at the Mount Baker Community Club, 2811 Mt. Rainier Dr. S. Free and open to public, the workshop will lay the foundation for talking about race, particularly with children. 30-50 participants are expected.

Cambridge Forum, Inc.

Conversations on Creativity

Lower Eastside Tenement Museum

Renovation of Upper (3) Floors of its 103 Orchard Street buildingto increase exhibit, education, and administrative spaces, roof repalcement, elevator extension to upper floors, providing wheelchair accessibility to the new exhibit, education, and adminis

OPM

Convert a firehouse into a borough town hall

DSS

Convert airport hanger to a community center/emergency shelter

OPM

Convert Former WFD HQ into a Community & Recreational Space

DSS

Convert old Bethany Airport Hangar into recreation building and emergency shelter

NSF

Mata de Platano Field Station and Nature Reserve (MPFS) is a crucial center for biological research, education, and outreach in Puerto Rico's northern karst region. This project aims to enhance MPFS’s sustainability and resilience by converting its current electrical system to a self-sustaining solar energy network and implementing a rainwater collection system. These upgrades will ensure uninterrupted access to essential resources, allowing researchers to conduct long-term studies without disruption. Frequent power outages across the island, intensified by natural events like Hurricane Maria, have highlighted the need for a reliable energy source and water supply. The station’s remote location in Arecibo further emphasizes this necessity, as municipal water services depend on electricity. Implementing sustainable infrastructure will not only benefit scientific research but also serve as a model for similar facilities in other ecologically significant regions. Enhancements to MPFS will strengthen its role as a hub for biological research, particularly within the numerous ecosystems that support Anolis lizards, migratory birds, and a large bat populations. By securing stable energy and water supplies, researchers will be better equipped to study the environmental dynamics of the karst region and its role in ecosystem restoration and conservation efforts. This project significantly advances scientific and technological understanding by integrating renewable energy with field research. Reliable electricity is essential for preserving biological samples, conducting experiments, and facilitating data collection. The installation of solar panels and an energy management system will introduce cutting-edge engineering solutions, improving energy efficiency while reducing the station’s carbon footprint. Additionally, the rainwater collection system will provide an independent water source, incorporating innovative filtration and storage techniques to ensure quality and sustainability. These developments will create interdisciplinary collaboration opportunities among engineers, environmental scientists, and biologists, promoting research at the intersection of sustainable technology and ecosystem conservation. Beyond direct research applications, the project has broad societal impacts: it will serve as an educational platform for students and community members to learn about renewable energy, water conservation, and species preservation. The successful implementation of sustainable infrastructure at MPFS can inspire other research facilities to adopt similar measures, reducing environmental impact on a global scale. By demonstrating the feasibility and benefits of integrating renewable energy and water sustainability in research stations, this project will contribute to policy discussions and encourage industry advancements in clean technology. Overall, enhancing MPFS’s infrastructure will support long-term ecological research, foster innovation in sustainability, and strengthen the field station’s capacity to train future scientists and environmental enthusiasts. 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.

NIAMS - National Institute of Arthritis and Musculoskeletal and Skin Diseases

Summary The goal of this grant is to understand the regulation of SHH-driven hair follicle neogenesis (HFN) in adult wounds. While much research focuses on wound healing, scarring, particularly from burns, trauma, and surgeries, remains largely overlooked. Scarring affects over 50% of the U.S. population, with 50 to 80 million new scars formed annually, resulting in significant cosmetic, psychological, and social burdens. Yet, no effective anti-scarring therapy currently exists. We previously developed a model in which large wounds in mice can lead to efficient hair follicle regeneration, opening the door to understanding the molecular mechanisms of HFN. Our lab has identified Sonic Hedgehog (SHH) as a critical factor in determining whether wounds heal with hair follicle regeneration or fibrosis and how SHH interacts with WNT and BMP signaling pathways for successful HFN. These findings raise new possibilities about the roles of SHH in the unresolved issue of wound scar remodeling: Can SHH remodel existing scars? If so, how long after wounding is it effective? And can this approach be applied to human scars? Furthermore, a longstanding question is how a developmental signal like SHH can be induced after wounding and what prerequisites are necessary for this signal to occur. This project aims to investigate the effect of SHH on old scars long after healing (Aim1), explore one of the upstream mechanisms we’ve identified as essential for SHH induction in large wounds (e.g., angiogenesis) (Aim 2), and examine how SHH signaling can similarly induce HFN using human fibroblasts (Aim 3).

NSF

This project is in asymptotic geometric analysis and affine convex geometry. One main emphasis of the research is on high dimensional objects and phenomena. This leads to applications in areas as physics, biology and medicine, computer science, optimization and economics and material science. Indeed, many objects appearing in these areas exhibit the property of being convex, including crystals, organs, high dimensional data clouds. How can one reconstruct or gain substantial knowledge of such convex objects when one only has partial information? This is one classical problem in convexity, called geometric tomography, and its research finds applications in medicine and biology where convex shapes occur naturally. In addition to the research activities, the PI will continue giving lectures to the scientific community, as well as to the general public and training graduate students and postdocs. Important features of the proposed project are the study of high dimensional objects and phenomena and their links with other areas of mathematics and mathematical sciences, such as probability, statistics and information theory. Of particular interest are the affine invariant functionals on convex bodies in high dimensions. Among the most important such functionals are affine surface area and p-affine surface area. Their corresponding affine isoperimetric inequalities, established by the PI and collaborators for all p, are stronger than their Euclidean counterparts and related to the famous Mahler conjecture which is still open in dimensions four and higher. It was shown by the PI that p-affine surface areas are directly related to entropies of cone measures of convex bodies which establishes a link between convex geometry and information theory. This link will be further explored, also in the context of log concave functions which are a natural extension of convex bodies in the realm of functions. Moreover, affine surface area appears naturally in questions on approximation of convex bodies by polytopes, a further main topic of study. The goal is to establish optimal dependence on all the relevant parameters involved in the approximation, like e.g., dimension, the number of vertices of the approximating polytopes. These issues will be considered in Euclidean, spherical and hyperbolic space. The PI and her collaborators extended the notions of affine surface area recently to a functional setting and to spherical and hyperbolic space. To establish the corresponding inequalities in those spaces is a further topic of study. 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.

LGBTQ Allyship

COO: Community Partnerships

White Center Food Bank

COO: Community Partnerships

Cham Refugees Community

COO: Community Partnerships

Contacto Consulting

COO: Community Partnerships

Potlatch Fund

COO: Community Partnerships