Syracuse University

NSF Awards · FY 2025 · 2025-07

Elastic deformations, which describe how materials stretch, compress, fold, and tear, are central to many applied sciences, including materials science, and engineering. Understanding these processes requires not only physical modeling but also sophisticated mathematical theory. This project develops new tools and refines existing methods to address longstanding challenges in the field. Specifically, the project analyzes the mathematical foundations of elastic deformations through the framework of Sobolev homeomorphisms. These mappings serve as natural models for nonlinear elasticity, though energy minimizers often fall outside this class. The research addresses this challenge by examining the limits of energy-minimizing homeomorphisms and focusing on the inner-variational equation. Key objectives include understanding the weak and strong closures of Sobolev homeomorphisms and developing Sobolev analogues of topological results such as the Jordan–Schönflies theorem. The project also advances a new theory of quasiregular values, providing a pointwise characterization of quasiregularity and uncovering new links to classical results. New topological arguments grow into decisive components of Geometric Function Theory and Nonlinear Elasticity. 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 · 2025-07

Non-Technical Abstract: Detecting single photons - the quanta of light- is the cornerstone of cutting-edge quantum technologies such as optical quantum computing, communication, and ultra-sensitive imaging. Superconducting nanowire single-photon detectors (SNSPDs) have emerged as the leading single photon detection technology owing to their near-unity quantum efficiency, higher count rates, extremely low dark counts, and high timing resolution. However, most state-of-the-art SNSPD detectors operate at very low temperatures (< 4 K), necessitating extensive cryo-cooling. Here, we propose utilizing high-temperature iron-based superconductors such as Fe(Te, Se), which is known to exhibit superconductivity up to 65 K at the monolayer limit, to advance single photon detection technology. This project aims to develop SNSPDs that operate at temperatures above liquid helium, significantly reducing the footprint and enhancing accessibility and scalability. The project's success could advance the quantum technology revolution due to its higher working temperature regime, which may have critical applications in biomedical research, deep space imaging, and optical-quantum computing. Developing next-generation high-temperature SNSPDs will advance quantum technologies (National Quantum Initiative Act 2018) and integrated quantum photonics (CHIPS and Science Act, 2022). This interdisciplinary project will enhance our science education initiatives and workforce development for the quantum age by providing hands-on quantum research experiences for students from K12 to undergraduate levels. Technical Abstract: The project consists of three aims. The first aim focuses on the optical and transport properties of few-layered Fe(Te,Se) flakes. Low-temperature spectroscopy and transport measurements will be conducted to characterize the influence of thickness, temperature, and substrate on the superconducting properties of nanometer-thin Fe(Te, Se) flakes. In the second aim, the nanofabrication and transport measurement of Fe(Te,Se) strips of varying widths (100 nm – 10μm) will be conducted to shed light on the microscopic mechanisms of photodetection in Fe(Te,Se). The third aim focuses on the optical characterization and single-photon detection of Fe(Te,Se) nanowires. The parameters of Fe(Te,Se) detectors, such as quantum efficiency, dark count, and count rates, will be quantified. This research project is integrated with quantum science education and workforce development. Students from K-12 to undergraduate levels will have the opportunity to gain research experience in the quantum technology laboratory. 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 · 2025-07

Computing systems in space enable essential technologies like GPS, satellite communications, and agricultural monitoring. However, these systems face harsh challenges, particularly radiation, which can severely degrade or destroy electronic components. Traditional radiation-hardened techniques that address this challenge are both costly and based on outdated technology, limiting performance and flexibility. At the same time, renewed interest in lunar and Martian exploration is driving demand for far more capable space-based computing. Fortunately, a promising approach called in-memory processing is being explored where memory directly performs computation. Using this method, memory can function like an accelerator suitable for enabling state-of-the-art image and signal processing and artificial intelligence (AI) approaches that would be otherwise impractical. Memory-based acceleration reduces the burden on and complements central processors for space computing systems. The RADIANT project investigates whether modern commercial memory devices, not originally designed for space, can function reliably and provide in-memory processing capabilities in radiation-rich environments through appropriately-designed error correction techniques. The research supports national priorities by advancing space computing capabilities, while also offering interdisciplinary education opportunities that span computer science, engineering, and physics. RADIANT has two main technical goals. First, it characterizes the behavior of commercial dynamic random-access memory (DRAM), the dominant technology for main memory in modern computers, under space-like conditions. The behavior of commercial DRAM in environments with elevated radiation and temperature shifts still remains relatively poorly understood. The study examines DRAM during both conventional use and in-memory processing to identify common fault modes and their dependence on memory architecture and access patterns. Second, the project develops fault tolerance techniques to protect DRAM for in-memory computing, which introduces unique challenges not addressed by traditional error correction methods. These include developing novel error correction codes that work for in-memory processing operations, as well as memory mapping strategies that account for weak or failure-prone regions. Together, these efforts aim to make advanced, low-cost memory technologies both viable and substantially more capable. RADIANT can provide the fundamental capabilities to allow supporting tensor-based algorithms, including the latest AI approaches such as large language and foundation models, in future space missions. 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 · 2025-07

The investigators explore how meltwater from surface channels called moulins (holes in the ice that funnel water downward) affects the hidden drainage system beneath Greenland’s glaciers. They will conduct a field study to see how water connects isolated pockets of space at the glacier’s base with larger drainage networks and how these connections influence seasonal changes in ice speed. The team will use tools like seismic sensors, radar, and measurements of ice movement to track how these systems evolve together. By observing changes in the number, size, and location of these underground cavities over time - linked to how much meltwater flows in - they will determine how the hydrological connections between these spaces affect how fast the ice is moving. This research builds on earlier discoveries showing that Greenland’s summer slowdowns (when glaciers move less) happen not because water channels grow larger, as seen in mountain glaciers like those in the Alps, but because isolated pockets under the ice merge into bigger drainage pathways. The study will focus on western Greenland’s Paakitsoq region. The investigators will create a Virtual Reality (VR) module showcasing fieldwork on the Greenland Ice Sheet in partnership with the Museum of the Earth (Ithaca, NY) and the Kangiata Illorsua-Icefjord Center (Ilulissat, Greenland). The investigators propose a field campaign focused on understanding how hydraulic connections between isolated cavities at the bed surface of the Greenland Ice Sheet and the broader distributed subglacial drainage system evolve, and how this "connectivity" affects the seasonal changes in ice velocity. The team will integrate ice dynamic, hydrologic, and geophysical (seismic and radar) methods to monitor the co-evolution of moulin-connected subglacial channels, well-connected regions of the distributed system, and hydraulically isolated bed cavities. By quantifying changes in cavity number, size, and spatial distribution over time - linked to observed meltwater inputs - the researchers will assess how bed cavity connectivity modulates ice motion. This work aligns with findings from the Greenland Ice Sheet (GrIS) observations, which show that summer slowdowns occur not due to conduit expansion (as seen on Alpine glaciers) but through increased connectivity within the distributed system as isolated bed cavities integrate into larger drainage pathways. The field campaign will focus on the Paakitsoq region of western GrIS, where supraglacial meltwater inputs are monitored to trace their subglacial impacts. Understanding these processes is critical for predicting how future meltwater increases will influence GrIS mass loss, particularly as seasonal connectivity changes modulate ice flow and stability. 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 · 2025-06

This CAREER project investigates how generative AI is reshaping the American workplace, focusing on its impacts on worker productivity, job satisfaction, and skill development. The proliferation of generative AI that can create text, images, audio, and video will affect a wide variety of jobs, including those that require years of education, extensive training, and creativity. As AI systems become increasingly integrated into everyday life, understanding their effects on the workforce is crucial for maintaining U.S. economic competitiveness. This project produces insights for decision makers and business leaders on effectively implementing AI technologies while supporting worker well-being. In addition, the research identifies potential challenges and opportunities in AI adoption, helping to guide workforce development programs, career counseling, and educational initiatives. This project investigates the views of workers and high school students toward generative AI, focusing on how these views influence their behavior as both workers and citizens. Three interconnected studies advance the literature in political economy and science and technology studies. Study 1 uses a two-wave panel survey of 1,500 workers to analyze how workers in different sectors of the economy, particularly knowledge workers, perceive the impacts of generative AI on job quality. Study 2 uses semi-structured interviews and an online deliberative workshop with 40 workers recruited through Study 1 to develop an in-depth understanding of workers’ perceptions of generative AI’s risks and opportunities. Building upon the previous two studies, Study 3 uses a two-wave panel study to understand how high school students navigate uncertainty around the future of work when deciding what additional schooling/training or career to pursue. The educational aspect of this project expands course offerings on AI and the future of work and creates a research collective that supports collaborations between students, postdocs, and faculty members. The public engagement component of this project involves organizing two pedagogy workshops that bring together career counselors, academics, and business leaders to produce educational resources, as well as disseminating research findings through public-facing reports, op-eds, and public events. 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 2026 · 2025-06

PROJECT SUMMARY/ABSTRACT: Efficient and effective protein quality control (PQC) is essential to proper cell function. Despite extensive research, mechanisms underlying PQC remain incompletely understood. Consequently, development of new therapies to treat conditions with dysregulated PQC such as proteinopathies and neurodegenerative disorders is impeded. This MIRA research program targets the Ubiquitin (Ub)-mediated PQC pathways, and specifically Ub-containing biomolecular condensates. These condensates are membraneless assemblies comprising Ub-binding shuttle proteins (e.g., UBQLNs, Rad23s) that preferentially condense with specific types of polyUb chains and PQC components; the condensates are involved in a wide range of physiological processes including stress response, proteasomal degradation, autophagy, and immune system activation. My lab’s work is grounded in the hypothesis that dysregulation of these condensates leads to Ub-containing inclusions characteristic of proteinopathies and neurodegenerative disorders, and specifically amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. We recently determined that ALS-linked UBQLN2 forms stress-induced biomolecular condensates in cells and that the full-length UBQLNs (1/2/4) all undergo phase separation in vitro to form condensates under physiological conditions. Important to the premise guiding our projects is the observation that interactions with polyUb chains (in length- and linkage- dependent manners) tune conditions for condensate assembly and disassembly. We predict that other PQC components further tune the assembly/disassembly and structure of these condensates. In this five-year MIRA program, my lab will use molecular biophysics and cell biology-based approaches to achieve a mechanistic understanding of how Ub-binding shuttle proteins (UBQLNs, Rad23s, DDIs) regulate function of biomolecular condensates in stress response and PQC. Our preliminary data from reconstitution experiments suggest that condensates drive distinct PQC outcomes (e.g., protecting substrates from degradation or driving substrate degradation). We surmise that these different outcomes stem from different conditions driving condensate formation and/or the varied molecular architectures of condensates composed of differing compositions of shuttle proteins and ubiquitinated substrates. Our projects will determine (1) the physiological functions of UBQLN condensate formation in cells under a myriad of cell stress conditions, (2) the molecular rules by which polyUb chains modulate condensation of shuttle proteins and PQC components (e.g., full proteasomes, deubiquitinases, ligases), and (3) the emergent functions of shuttle protein PQC condensates in regulating substrate degradation, protection from degradation, and substrate ubiquitination/deubiquitination. The results from these projects will uncover the role of condensates in mediating PQC under physiological and stress conditions.

NSF Awards · FY 2025 · 2025-06

This Research Experiences for Undergraduates (REU) site award to Syracuse University, located in Syracuse, NY, supports the training of 10 students for 10 weeks during the summers of 2025-2027. In this program, funded by the Division of Chemistry, students gain valuable research experience, develop professional skills and confidence as they progress towards careers in STEM related fields. Participants also learn methods and techniques through hands-on experience, practice science communication through one-on-one discussions, group meetings and presentations, and gain new insights on chemistry education and career possibilities. The REU site is committed to motivating students to continue research and to explore the opportunities that chemistry offers. In this REU program, students conduct research side-by-side with faculty and student mentors, through projects that include organic and inorganic synthesis, spectroscopy and other physical measurements, computational methods, preparation and characterization of materials, and biochemical studies of proteins and DNA. Students additionally benefit from the highly collaborative environment provided by the chemical community at Syracuse University, state-of-the-art facilities, and opportunities to communicate and disseminate their accomplishments in written and oral forms. This Site is supported in part by funds provided to the National Science Foundation by the Semiconductor Research Corporation. 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 · 2025-06

This award will support 11 PhD students attending the Consortium for the Science of Sociotechnical Systems (CSST) Summer Research Institute. Many of humanity's most pressing problems require research teams that can bring together both social and technical expertise. For instance, improving cybersecurity and privacy requires deep technical knowledge of encryption and trust models, as well as philosophical and anthropological understandings of values like safety and autonomy. The researchers, data scientists, and designers who will solve these "socio-technical" problems need need training in interdisciplinary thinking and collaboration. However, researchers who span boundaries too often are trained at the margins of their fields and lack models of success, mentorship, or support in their home institutions and fields. The CSST Summer Research Institute provides this support by bringing together senior Ph.D. students, post-docs, industry researchers, and early career faculty with experienced boundary-spanning researchers, providing a critical intellectual and professional support system that enables boundary-spanning researchers to succeed in both their careers and the social problems they tackle. The central function of the institute is to sustain and develop a densely connected research community of scholars. An initial cohort of approximately 10 mentors are recruited each fall, with additional mentors recruited as needed to support the particular needs of mentees in the spring. The call for participants is released in early spring each year. Approximately 30 participants (senior Ph.D. students, post-docs, industry researchers, and early career faculty) are chosen by a review committee comprised of mentors, organizers, and other senior reviewers as necessary to conduct a well-informed review of the submissions; these reviewers will make their decisions based on materials submitted by applicants in response to the Call for Participation. Disciplinary, methodological, institutional, and topical breath will all be considered in final acceptance decisions. Participants will be invited to join informal social activities outside of the institute's formal sessions and participate in a Slack workspace intended to support cohort and community beyond the conclusion of the in-person event. 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 · 2025-04

Non-technical Summary The Interactive Biomaterials Research Experiences for Undergraduates (REU) Site will advance scientific progress by providing students nationwide with hands-on experience in cutting-edge biomaterials research. The students will receive training to pursue impactful careers in science and engineering. Through this program, students will engage in collaborative research projects and gain technical expertise while building essential skills in teamwork, networking, and effective communication with scientific and public audiences. The program prioritizes actively recruiting students with limited research opportunities to ensure engagement in STEM education. Participants will receive mentorship from faculty, graduate students, and peers, fostering a supportive environment that empowers them to succeed. A key focus is introducing students to STEM careers and inspiring students to pursue advanced education. Best practices and lessons learned from this REU Site are widely disseminated through online platforms and educational publications, enabling replication and expansion of similar initiatives to further promote excellence in biomaterials research. Technical Summary Modern biomaterials are increasingly designed to be stimulus-responsive, adapting their properties in controlled ways to respond to environmental stimuli such as thermal, chemical, or mechanical changes. These materials interact with biological environments at multiple scales—atomic, molecular, cellular, microscopic, and macroscopic—where these interactions ultimately govern their performance. The research projects offered through this REU Site will advance our understanding of these fundamental interactions and cover a wide range of cutting-edge topics. Examples include shape memory and stimulus-responsive polymers, nanoparticle-based drug delivery systems, the collective behavior of bacterial biofilms, cell-biomaterial interactions, stem cell research, biocompatible soft robots, 3D printing of microfluidic devices, and computational modeling of biomaterials. These projects will be hypothesis-driven and foster collaborations across laboratories, departments, and institutions, leveraging the expertise of faculty mentors. Equipped with state-of-the-art facilities, analytical tools, and computational resources, these mentors will provide students with exceptional training in advanced research methods. By participating in these projects, students will gain hands-on experience, develop technical expertise, and deepen their understanding of the complexity of biomaterials. They will also learn to harness the unique properties of these materials for applications in advanced technologies, preparing them for graduate studies and careers in academia, industry, and government. This REU Site will emphasize interdisciplinary collaboration and hypothesis-driven inquiry, integrating both into its student training and research. The program will prepare the next generation of scientists and contribute to advancements in biomaterials science by addressing fundamental challenges and fostering innovation. 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 · 2025-04

Computer systems make use of "memory" to hold data in the short term and "storage" to hold data in the long term. Both memory and storage have experienced technological advances driven by the rise of data-intensive applications such as data analytics and machine learning and improvements in hardware. However, the performance of the combined hardware devices and software systems that manage device access is limited by the information available to and from systems and storage devices. This research project aims to bridge the information gap between software systems and hardware devices by embedding implicit hints in its communication channel that exists between systems and devices. The project's novelties are (1) the idea of implicit hints on performance to be passed over the channel , and (2) its practical application for hardware-software optimizations. The project's broader significance and importance are (1) the improved sustainability and performance of computer systems and (2) the enhancement of workforce development and education pipeline for computer systems. More specifically, this project focuses the memory and storage stack whose interfaces are narrow. The key insight is that for both memory and storage, translation layers exists both above and below the interfaces (physical memory address and logical block addresses, respectively) that allow hints to be passed while maintaining backward compatibility. The research objectives are achieved through three planned thrusts. First, it architects a flash memory-based solid-state drive that supports differentiated performance by balancing its various internal techniques and implementing the address remap command through learned indexing. Second, the project rethinks file system policies for implicit differentiation by revisiting block allocation, page cache, and file defragmentation. Lastly, the project creates a holistic memory management scheme for far memory by considering their interconnect topology and device performance characteristics. The resulting techniques will also drive innovative classroom lessons in computer systems for advancing our technological work force. 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 2026 · 2025-03

Nearly 20 million adults (38%) aged 65 and older have limitations with one or more self-care activities (e.g., dressing, getting out of bed) and one in ten older adults are living with Alzheimer’s Disease and Related Dementias (ADRD). Together these two overlapping groups of “high-need” older adults typically rely on a variety of long-term care (LTC) sources to assist with daily activities, including family and unpaid care, paid care in the home, residential care such as assisted living and nursing home care. Inadequate care may lead to adverse consequences in daily self-care and avoidable health care utilization. Unanticipated changes in the LTC landscape may have profound effects on access to and use of LTC and contribute to further adverse consequences for high-need older adults, particularly for those living with ADRD. This project will draw upon two complementary longitudinal, nationally representative surveys of older adults–the Health and Retirement Study (HRS) and the National Health and Aging Trends Study (NHATS)– linked to geographic data and Medicare claims. Using statistical approaches that strengthen our ability to draw causal inferences, we will: 1) Evaluate the short-term impact of a rapidly shifting long-term care landscape on the type and amount of LTC use, comparing high-need older adults with and without ADRD and identify arrangements more likely to be “stable” with lower risks of change. 2) Determine whether care trajectories are disrupted in response to unanticipated shifts in the long-term care landscape, comparing high-need older adults with and without ADRD. 3) Assess the impact of changes in the long-term care environment on adverse consequences related to care gaps among highneed older adults with and without ADRD. We will estimate the effect of changes in the long-term care environment on self-reports of unmet need (using NHATS) and claimsbased measures of avoidable hospitalizations and emergency department visits (using HRS) for those with and without ADRD. Detailed geographic data will allow us to take into account local conditions while identifying more “vulnerable” care arrangements with higher risks of adverse consequences. The results of this project will provide a comprehensive understanding of how resilient formal and informal care systems are to unanticipated changes in the long-term care landscape in the short and longer term. This study aligns with NIA’s priority to understand community support for dementia care, in particular the determinants of availability LTC, LTC utilization and how the effects of community level factors including infrastructure and risk environment.

NSF Awards · FY 2025 · 2025-03

Microorganisms live in some of the harshest environments on Earth, from glaciers to arid deserts to the geothermal springs that are the focus of this work. Previous work in geothermal environments has led to the discovery of major groups of bacteria and archaea that have unique adaptations to cope with harsh environmental conditions. Single-celled microbial eukaryotes (e.g. protists) remain underexplored in geothermal springs despite evidence that they can be diverse and abundant in these extreme habitats. This research project will document the biodiversity of microbial eukaryotes across geographically and geochemically diverse spring systems and describe new species of microbial eukaryotes. Findings from this research will enable more accurate estimates of species diversity and expand our understanding of the diversity of eukaryotes. Broad interest in geothermal systems will also be leveraged to increase participation by undergraduate researchers, train the next generation of protistologists, and broaden public understanding of the microbial eukaryotes. The biodiversity of microbial eukaryotes in geothermal springs remains poorly understood as most lineages are only known from environmental sequencing. Single-cell technologies and new culturing approaches coupled with bioinformatics pipelines enables description of the diversity of protists in these extreme environments. This research focuses on two major clades of eukaryotes –Amoebozoa and Heterolobosea – that collectively represent a substantial portion of amoeba diversity and can be abundant in high temperature and low pH environments. Combining single-cell profiling, culturing, and microscopy-based analyses, this project will infer species boundaries, describe new species, and improve reconstructions of the tree of life. Gene families will be analyzed to shed light on putative adaptations that allow survival in extreme environments. Integration of project data will be coordinated with public biodiversity databases and strain collections to enhance access to microbial resources. A summer training workshop will aid in training early career protistologists in the characterization of unknown protist lineages, with modules focused on biodiversity, species discovery, and systematics. A microbial diversity workshop for high school science teachers will provide a foundation on the tree of life and the phylogenetic diversity of eukaryotes. 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 · 2025-03

This award provides funds for participant travel support to the 50th Annual New York State Regional Graduate Mathematics Conference (ANYSRGMC) which will be held at Syracuse University on March 28 and 29, 2025. In addition, the grant also provides funds for the 51st and 52nd editions of the conference which are planned for March or April of 2026 and 2027. The ANYSRGMC is the longest running graduate mathematics conference in the country and is organized primarily by graduate students. The conference presents an opportunity for graduate students in New York State and surrounding regions to come together, share current research, and interact with other graduate students in a similar phase of their academic career. Opportunities to speak at conferences are an essential part of training future mathematicians. Unlike other graduate student mathematics conferences in the region, at the ANYSRGMC graduate students in all areas of mathematics have an opportunity to present their research. In many cases this is the first time a graduate student will speak at a conference, giving them a valuable opportunity to learn how to structure and deliver a talk. In addition, given the broad range of topics covered, graduate students are exposed to areas of mathematics that they are less familiar with, potentially broadening their research horizons. NSF funding increases access to this conference, giving graduate students with fewer financial resources an opportunity to travel to the conference. The majority of the ANYSRGMC consists of 30-minute graduate student talks given in parallel sessions. There are also two invited guest speakers who give keynote addresses. The two speakers are typically prominent mathematicians in two distinct areas of mathematics who can speak to the diverse interests of the graduate student participants. In addition to hearing interesting mathematics, students can meet and learn from successful mathematicians outside of their home universities. Breaks between the talks give graduate students a chance to interact with each other, potentially leading to new collaborations. The website for the conference is at https://mgo.syr.edu/conferences/upcoming/ 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 · 2025-01

Artificial intelligence (AI) is increasingly a part of everyday life for functional purposes (like interpreting x-rays or recommending entertainment), and also for companionship (like chatting or even just sitting together). Companionship is a positive state of close connection with someone or something that unfolds over time and is valued for itself. Companionship is important to human life because it enhances well-being---for instance through reduced loneliness, enhanced emotional resilience, and finding elevated meaning in life. Evidence shows that people can see AI agents as mindful entities, and scientists and technologists often assume that creating more human-like, seemingly mindful AI, is necessary to foster companionship benefits. However, there are no scientific studies demonstrating that seeing a machine as a “someone” actually enables or enhances companionship benefits. Without a full understanding of the link between machine-mind perception and companionship outcomes, we may be developing and using technologies that carry unnecessary risks to privacy and may even diminish well-being. This project determines how to best measure the notion of mind perception, companionship, and well-being in human-AI relations. A series of studies then assesses the assumed link between perceiving AI systems as mindful entities and their efficacy as companions across different kinds of AI applications. By answering the fundamental question of whether mind perception plays a role in AI-companionship benefits, the work will ultimately help technologists make better decisions about AI design, public health officials make better decisions about AI policies, and everyday users make better decisions about whether and how they want to interact with AI companions. To accomplish the desired outcomes, the project pursues three objectives: 1) Develop and validate measurements for AI mind perception, companionship, and relational benefits; 2) build a data-driven model of relationships between those variables; and 3) test the model in short- and long-term human-AI relations. Objective 1 will be achieved by analyzing public conversations about AI companions, generating and evaluating self-report measurement tools, validating existing measurements for use in human-AI contexts, and exploring behavioral indicators of mind perception, companionship, and well-being. Objective 2 will be achieved through studies designed to identify direct or indirect relationships between mind perception, companionship, and well-being—experiments test the causal influence of mind perception on companionship experiences and subjective well-being. Objective 3 will be achieved by longitudinally testing the identified causal effects (via real-time surveys of experience) over short-term and long-term companionship interactions. This work advances the science of social-psychological processes and AI companionship. It comes at a time when companionship, as a key component in fulfilled human life, is increasingly addressed by social AI. This project lays the evidential groundwork to determine whether and how current theories of human mind perception apply to AI companionship. The research advances understanding of whether or not we must see someone in the machine for them to meaningfully contribute to human well-being. 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 2024 · 2024-12

The groundbreaking discovery of gravitational waves by NSF’s Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) provided a first glimpse of the profound potential that the rapidly growing field of gravitational wave astrophysics holds for the rest of the century. In 2023, the LIGO observatories reached their design sensitivities, able to detect binary neutron stars 500 million light years away. Unprecedented advances in Quantum-Enhanced Metrology over the last 2 decades have made this increased sensitivity possible. This award will establish a Quantum-Enhanced Metrology testbed at Syracuse University to test novel techniques and materials that will further advance the quantum improvement of gravitational wave detectors. In parallel, this award will inspire the next generation of scientists and non-scientists through various outreach projects and education opportunities related to the quantum world. The primary objective of this award is developing the technology needed to achieve 10 dB effective squeezing improvement to gravitational-wave interferometers. The goal of the LIGO observatories is 10 dB of effective squeezing, which currently operates 5-6 dB below the shot noise limit and a benchmark number for the next-generation observatory Cosmic Explorer. High levels of squeezing improvement are required for future detectors to reach their design sensitivities and to enable their science goals. The first stage of this award includes constructing a squeezed light source at Syracuse University. We will then use this testbed to investigate the integration issues of quantum-enhanced interferometers by coupling this squeezed vacuum state to a coupled arm cavity and signal-extraction cavity. This quantum optics and gravitational wave-focused research is associated with an education plan to excite and inform high school teachers, students, and the public about gravitational waves, quantum light, and experimental 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 2024 · 2024-12

A significant gap exists between the state of quantum science and its practical uses in industry. Part of the gap results from the lack of the advanced technical workforce needed to implement quantum technologies. The people best poised to enter the new quantum technological workforce are incumbent photonics technicians. Their current qualifications provide a foundation on which to build the new quantum-related competencies. This project aims to produce a freely available curriculum that will enable photonics technicians to acquire new quantum-related competencies. This curriculum will contain a three-course sequence with freely accessible textbooks, lab manuals, and interactive online content. Availability of the courses via an open-access educational platform will reduce geographical barriers between colleges, students, and industry. The proposed platform can also promote the high-tech quantum workforce by increasing access to education in quantum technologies. The proposed quantum technology curriculum is expected to help U.S. businesses maintain global leadership in advanced laser and quantum technologies. This project will pioneer the introduction of quantum science into advanced technological education. It will do so by developing, testing, and disseminating a three-course hybrid curriculum in quantum-enabled technologies. The project will begin with an assessment of the industry demand for quantum-related skills, continue with curriculum and course development, and end with establishment of a sustainable learning platform. The three courses will be designed to meet the highest level of Quality Matters certification. The curriculum will be promoted by academic and industry collaborators and validated through data collected via the learning platform in real-time as students interact with the course material. The open-access learning platform will make the entire educational content accessible and transferrable to other institutions. Through these efforts, this project will contribute to the new quantum STEM workforce development needed to propel quantum technology forward. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the nation's economy. 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 2026 · 2024-12

PROJECT SUMMARY Fatigue is highly prevalent in the stroke population, and it is often reported as one of the most debilitating post- stroke symptoms. Unfortunately, post-stroke fatigue is not effectively managed, primarily because little evidence exists supporting post-stroke fatigue treatment. Transcranial direct current stimulation (tDCS) is a type of neuromodulation that has been shown to improve treatment response in persons with aphasia (PWA) and is a promising treatment approach for reducing post-stroke fatigue. Considering the potential impact of fatigue on aphasia recovery, there is an urgent and critical need to assess interventions that can alleviate the consequences of post-stroke fatigue, boost cognition and language, and maximize the brain’s neuroplasticity. Studies have shown that tDCS applied to dorsolateral prefrontal cortex (DLPFC) can improve attention and language comprehension after stroke. However, it remains unknown if tDCS administered to DLPFC can simultaneously enhance attention task performance, improve language comprehension, and reduce post-stroke fatigue. The long-term goal of this research is to increase the effectiveness of speech and language treatments for aphasia by accounting for individual and cognitive factors that could negatively affect recovery. This project will advance the NIDCD’s mission by directly addressing one of these factors to improve stroke and aphasia rehabilitation. The proposed project is a critical step towards advancing the clinical science of aphasia treatment through two specific aims: 1) to conduct a rigorous clinical trial implementing neuromodulation in combination with behavioral attention-focused language treatment to improve attention, language, and fatigue outcomes for PWA, and 2) to comprehensively identify mechanistic interrelationships among post-stroke fatigue, cognitive deficits, and language deficits in PWA. Using a 2x2 factorial design, participants will first be randomized to tDCS condition (active or sham) and then randomized to a behavioral sentence comprehension condition (+attention or - attention). Participants will undergo 10 sessions of treatment and outcome measures will be administered at 3 time points (baseline, post-training, 3-month follow-up). Attention performance will be measured using sustained, alerting, orienting, and executive attention tasks. Sentence comprehension will be measured using a treatment- based and a functional sentence comprehension task. Fatigue will be measured using an aphasia-adapted version of the Fatigue Severity Scale, a commonly used fatigue measurement tool. We will address our study aims by comparing performance on these tasks across all combinations of treatment (+/- tDCS; +/- attention- focused language treatment). At the conclusion of this clinical trial, we expect to provide evidence that active anodal tDCS to DLPFC in combination with behavioral attention-focused language treatment can enhance attention ability, improve sentence comprehension, and reduce post-stroke fatigue. We also expect to show that language and attention deficits are associated with clinically significant fatigue and that clinically significant fatigue is associated with poorer treatment outcomes.

NSF Awards · FY 2024 · 2024-11

This REU Site award to Syracuse University, located in Syracuse, NY, will support training 10 students for 10 weeks each during the summers of 2025-2027. It is anticipated that a total of 30 students, primarily from schools with limited research opportunities or who are from groups traditionally underrepresented in STEM fields, will participate. This program will focus on recruiting domestic students from minority-serving institutions, primarily undergraduate institutions, and community colleges. Students will learn how laboratory research is conducted, and many will present the results of their work at scientific conferences. Assessment of this program will be done through an online tool. Students should apply to the REU site using NSF ETAP (Education and Training Application: https://etap.nsf.gov). Research within this REU program will focus on using Microscopy to understand Form and Function Across Biological Scales (MicroFFABS). Each student project will incorporate microscopy into innovative biological research. All REU participants will gain exposure to microscopy methods (e.g., fluorescence, super-resolution, etc.) using state-of-the-art instrumentation with applications to questions that cross multiple scales of biological research. Potential projects with mentors in the Biology and Physics departments include investigating molecular and cellular mechanisms underpinning neurodevelopment; identifying the connections between form, function, and environment in animals that interface with and attach to surfaces; examining mechanisms driving plant responses to climate change; elucidating mechanisms of protein quality control to understand the assembly and disassembly of biomolecular condensates; and understanding how cells self-organize and develop. Students will participate in a broad range of professional development workshops including the responsible and ethical conduct of research, as well as training in advanced microscopy techniques and post-processing practices and interpretation. Students will be expected to present their work in a campus-wide poster session at the conclusion of their research experience. Online applications are evaluated and program directors of the REU program make a final ranking of the finalists. Offers will be extended via email to the top-ranked candidates until the 10 positions are filled. 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 2024 · 2024-10

Insect herbivores such as aphids play outsized roles in both natural and agricultural ecosystems. Consequently, understanding factors that control aphid abundance is critical for managing many ecosystems in the future. Rising temperatures can directly impact aphid development, growth, and survival and shift how these insect herbivores interact with plants and other organisms in their environment. Biotic interactions such as those that influence food resources or vulnerability to predators may be especially important in determining whether aphids and other insect herbivores are able to persist and adapt to rapid climate change. This project will study the effects of warming and biotic interactions on aphids to improve understanding of factors that affect herbivore abundance under current and future climate scenarios. Aphids are sensitive to the direct effects of warming temperatures, but their abundance also depends on complex interactions with microbes, plants, and other insects as well as genetic differences between aphid populations. Through a series of field experiments in a well-studied Rocky Mountain ecosystem, this project will test how interactions among these factors can lead to unexpected patterns in aphid abundance. Findings from this work will be used to create models that predict how aphid populations are likely to respond to rapid climate change, which can inform insect monitoring, conservation, and management. Results from this work will also be incorporated into educational materials for K-12 students with the goal of advancing quantitative skills in climate change education. The PIs will also recruit scholars from underrepresented and underserved communities to work on this project and foster their professional development through interdisciplinary, team-based science. Data from this work will be integrated in a graphical modeling interface and educational modules to support dissemination of project results to interested stakeholders. Interactions between species within multi-trophic networks can facilitate or constrain how organisms respond to rapid climate change. However, biotic interactions can shift with rising temperatures, altering eco-evolutionary dynamics and network stability in ways that are challenging to predict. Characterizing physiological and eco-evolutionary mechanisms that drive the population dynamics of keystone species within interaction networks is critical for predicting how these systems will respond or adapt to novel environments. Insect herbivores are keystone species in many ecosystems, and ecologists have long sought to understand biotic and abiotic factors that govern insect herbivore dynamics. The proposed research will integrate long-term field observations and manipulative experiments with agent-based models to develop a mechanistic understanding of temperature responses in a well-studied subalpine plant-aphid system. This work will provide a robust understanding of temperature effects on aphid population dynamics by (1) integrating the direct effects of temperature on aphid development with indirect effects driven by shifts in above- and belowground interactions, (2) assessing local adaptation within plant-aphid interactions across a temperature gradient; and (3) using these mechanistic relationships in a hierarchical modeling framework to forecast aphid dynamics under variable climate 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 2024 · 2024-10

The goal of this research is to create artificial intelligence (AI)-enhanced digital tools to amplify freelance workers ability to work in online labor markets. This research is important because online freelancing -- in which professionals work on a collection of individual tasks, outside of traditional workplaces -- is rapidly becoming a significant component of modern labor markets. Online freelancers need to market themselves, find well-paying and skill-enhancing jobs, and be able to perform and get credit for quality work. However, online labor markets make it hard to do this at times because of their design: their policies are often more friendly to employers than to freelancers, while their algorithms for matching people with jobs and prices are often opaque to workers. The key idea of this project is that AI-enhanced digital tools may be able to help workers better-manage their profiles, workload, and task performance. To that end, the project team will work with online freelancers to develop and evaluate a number of prototypes that counter these problems. If successful, the research will both improve the specific problems of online freelancing work as well as provide an example of how AI-enabled tools, designed wisely, can complement rather than replace people in jobs. To achieve this goal, the research effort leverages human-centered design principles. Working with a carefully selected and steadily updated sample of online freelancers, data will be gathered through interviews and focus groups to identify and advance the functionality and needs of AI-enabled tools to support these workers. In doing this, the research effort leverages the investigators' ongoing work in building similar tools for crowd workers and insights from an ongoing panel study of online freelance workers. Over three years and through multiple design, deployment, and feedback cycles, the research team will collaborate with organizations dedicated to supporting online workers. Together, they will enhance the AI-enabled tools' functionality and design to address the needs of these workers. 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 2024 · 2024-10

Wireless communication services and associated applications rely on the use of radio frequency (RF) spectrum resources for their operation. Due to the rapid growth in the use of these services, spectrum management agencies and wireless service providers need to migrate from current spectrum use practices to more dynamic spectrum assignment and sharing mechanisms. This project addresses these challenges by focusing on the design and validation of a distributed and data-driven next-generation architecture for dynamic spectrum management among decentralized and heterogeneous wireless systems. Aspects of the distributed spectrum architecture are expected to influence future technical standards. The outcomes of the project will be made available to the wireless/networking industry through mechanisms such as the bi-annual WINLAB industrial advisory meeting. The project integrates activities related to the use and design of spectrum deconfliction protocols and the execution of measurements to design and use spectrum consumption models into the annual WINLAB summer internship program which involves about 30 to 40 undergraduate students each year. Distributed dynamic spectrum management aims to overcome the limitations of centralized control such as limited scalability and single point of failure, while still achieving high levels of spectrum efficiency. The distributed data-driven spectrum management (D3SM) architecture that serves as the baseline for this project uses an Internet-based control plane that facilitates the operation of dynamic spectrum sharing algorithms between peer networks. This control plane for spectrum coordination supports the exchange of and processing of fine-grained meta-data about the local wireless environment in the form of standardized radio frequency spectrum usage descriptors known as “spectrum consumption models (SCMs)” which have recently been standardized. Such spectrum usage data can be used to realize a flexible range of distributed algorithms and dynamic interactions for spectrum coordination. It is noted that a suitably designed distributed spectrum management framework can also accommodate some level of hierarchically organized centralized coordination where appropriate. The project is based on a multi-stage evaluation methodology that starts with architectural design of D3SM with the required protocols and algorithms, followed by simulation and indoor testbed emulation of a number of use case scenarios including spectrum sharing between cellular operators, coexistence of WiFi and 5G, and interference management for passive wireless devices such as those used for weather forecasting and radio astronomy. These studies are expected to lead to an experimentally validated set of protocols and algorithms for distributed and partially centralized spectrum management methods. 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 2024 · 2024-10

Forest regeneration is crucial for addressing climate change, but challenges such as scarce seed availability and time-intensive seedling cultivation hinder many projects. To reduce costs and increase the effectiveness of seeding, a convergent team comprised of experts from material science, engineering design, bio- and soil mechanics, soft robotics, plant science, and forest ecology will advance novel bio-inspired, biodegradable, self-burying seed carriers for aerial seeding. Autonomous seed carrier burial at optimal depths provides protection from herbivores and insulation against harsh environments, thereby enhancing germination rates and safeguarding seeds during critical early stages of growth. This research will expand forest restoration efforts, offering economic benefits and promoting ecological resilience. To advance forest regeneration practices through interdisciplinary efforts, this project: (1) addresses the challenge of low germination and seedling establishment rates in aerial seeding by developing self-burying seed carriers; (2) explores the rational design of seed carriers to accommodate the unique requirements of different tree species and environments, aiming to create a library of designs applicable across diverse ecosystems; (3) seeks to understand and optimize the self-burying process of seed carriers by establishing a new modeling framework to improve the efficiency and effectiveness of the proposed seeding techniques; and (4) emphasizes the importance of fostering biodiversity in forest ecosystems, resulting in new ecological field test protocols and an evaluation pipeline that is enabled by engineering and guided by forest ecology. 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 2024 · 2024-10

As our climate changes, animals and plants are increasingly exposed to dehydration. Remarkably, a common strategy that has evolved to help organisms across all kingdoms of life deal with desiccation is through the synthesis of a special class of proteins known as intrinsically disordered proteins. Despite their importance in protecting animals and plants from drying out, how these proteins work is unresolved. This project will combine experiments that span individual molecules to whole organisms to understand how disordered proteins provide protection from dehydration across all kingdoms of life. As part of this study, this project will recruit students from rural communities via remote-learning and include them in cutting edge, interdisciplinary research which will facilitate their integration into the US STEM workforce. Proteomes across all kingdoms of life contain a significant fraction of sequences that are intrinsically disordered and do not adopt a stable three-dimensional structure. Instead, these sequences exist in an ensemble of rapidly interconverting conformations that can be highly sensitive to changes in the cellular environment in which they function. Interestingly, many of these disordered proteins are implicated in mediating resistance to environmental stresses, including desiccation, in which the physical-chemical composition of the cell changes dramatically. The goal of this project is to gain a holistic understanding of how disordered proteins and the cellular environment come together to provide protection to the cell during extreme desiccation. Towards this goal, the project will employ a multilevel, interdisciplinary, and integrated approach. Starting at the molecular level, in vitro and computational experiments will be performed that will provide insight into how desiccation-protective disordered proteins function in conjunction with well defined and controllable environments. This information will be integrated with high throughput, sequencing-based studies of disordered protein-mediated desiccation protection performed in yeast (cellular level), and a multicellular animal model (the roundworm, Caenorhabditis elegans, organismal level). 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 2024 · 2024-09

Project Summary The placenta performs important functions to ensure proper development of the fetus, including oxygen and nutrients exchange, waste product removal and hormone secretion. It also acts as a barrier to protect the fetus from harmful substances and pathogens that might be present in the maternal circulation. Despite its short lifespan, the placenta plays a critical role in the survival and growth of the fetus. Implantation failure and inadequate placental development can lead to pregnancy complications, such as preeclampsia, miscarriage, and fetal growth restriction. However, our understanding of human placenta development is quite limited due to scarcity of fetal tissues, ethical restrictions and lack of practical experimental tools. Our preliminary studies show that human trophoblast stem cells (hTSCs) possess an intrinsic self- organization property. When a colony of hTSCs starts to cluster, they spontaneously form an organoid with cavities resembling trophoblastic lacunae, and can continuously develop into a multicellular tissue resembling first-trimester placental villi under a neuregulin 1 (NRG1) stimulation. In this proposed research, we will undertake an exploratory, high-risk but high-reward study to generate a microfluidic human placenta model. Specifically, we will derive hTSCs from human induced pluripotent stem cells (hiPSCs) through a naïve pluripotency stage. We will then use these hTSCs to generate microfluidic placenta organoids. The role of YAP signaling in regulating spontaneous syncytiotrophoblast (STB) differentiation will be examined. We will further induce the development of placental villus-like tissue by modulating timing and concentration of NRG1, and examine morphologies and cell composition of the resultant placenta organoids. Important, we will conduct single-cell RNA sequencing (scRNA-seq) analysis on the resultant placental villus-like tissue at different times and perform transcriptome-wide comparisons with published in vivo human placenta scRNA-seq datasets. This hTSC- derived human placenta organoid system will offer the first-of-its-kind experimental platform for studying previously elusive stages of human placental development. This research, if successful, will lead to innovative technologies and methodologies for controllable, reproducible, and scalable manufacturing of in vitro stem cell-derived tissues with molecular and cellular characteristics consistent with the early/mid-gestation placenta. This platform can also serve as a screening tool to investigate the potential negative effects of pathogens, drugs or toxic substances on human placental development, which will accelerate research efforts towards early diagnosis, prevention and treatment of pregnancy complications associated with insufficient or abnormal placentation.

NSF Awards · FY 2024 · 2024-09

The groundbreaking discovery by the NSF’s Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) provided a first glimpse of the profound potential that the rapidly growing field of Gravitational-Wave Astrophysics holds for the rest of the century. This year, advanced LIGO reached its design sensitivity of 160+ Mpc, resulting in multiple observed black hole mergers per week. Reducing the time the LIGO detectors must spend acquiring an observation-ready state directly translates to additional observation time and astrophysical detections. This award supports the development of a sensor and actuator subsystem that will improve the duty cycle and sensitivity of LIGO detectors by mitigating the suspension resonant modes. The award will also support graduate students working on gravitational-wave detector instrumentation. The violin modes of the LIGO test mass suspensions cause operational issues when they are excited and limit the detector sensitivity in the narrow bands of their resonances. The modes can be excited by external events like earthquakes and can prolong interferometer downtime after lock losses. This award will support the design, construction, and characterization of an active suspension fiber damping system suitable for LIGO and future ground-based gravitational-wave detectors. A dedicated shadow sensor for measuring fiber displacement and an accompanying electrostatic actuator will be prototyped and developed at Syracuse University. In parallel, a compact sensor and actuator will be developed for integration into the test mass fiber guards. This project will also inform the suspension design for future gravitational-wave detectors. 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.