Florida Atlantic University

NSF Awards · FY 2026 · 2026-07

Amine-modified materials are porous structures chemically modified to promote certain reactions. They improve air quality by removing noxious gases and harmful organic vapors. They also remove heavy metals and per- and polyfluoroalkyl substances (PFAS) known as “forever chemicals.” However, amine-modified materials encounter hot air during their synthesis and operation. Exposure to hot air triggers unwanted reactions that damage the material and shortens its lifetime. This project will carry out a series of experiments to identify the molecular-level events that lead to degradation of amine-modified materials. The results will lead to longer-lasting, more reliable materials for cleaner air and water. The project will support the professional development of engineers and scientists. It will engage middle- and high-school students in hand-on learning activities. It will also equip science teachers with classroom materials to connect the research to real-world challenges. Project outcomes will bolster U.S. energy security and advanced manufacturing by providing important materials for power generation and fossil fuel purification. This project will elucidate fundamental chemical principles governing oxidative degradation in immobilized amines by systematically probing molecular-level support-amine interactions. Precisely engineered surface modification of porous supports will be integrated with advanced spectroscopic techniques, high-resolution mass spectrometry, and complementary structural characterization tools to delineate the roles of transition metals, heteroatoms, surface hydroxyl density, and amine aggregation in dictating thermo-oxidative stability. The project will decouple the intertwined effects of support chemistry, amine structure, and local microenvironment on degradation pathways and kinetics and byproduct formation. The outcomes will establish a predictive mechanistic framework linking sorbent physicochemical properties to amine stability and oxidation pathways. These transformative findings will be translated into rational design strategies to suppress deleterious oxidation reactions, extend sorbent lifetime, and minimize harmful byproduct emissions. While the primary focus is on amine-modified mesoporous silica sorbents for carbon dioxide capture, the resulting framework will be readily transferable to amine-functionalized metal-organic frameworks, carbonaceous materials, covalent organic frameworks, and membrane platforms used in various separation and purification 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 Awards · FY 2026 · 2026-05

This project aims to develop the cryptographic foundations for secure communication in the post-quantum era. Most current public-key cryptographic systems, which underpin the security of modern digital infrastructure, rely on the hardness of problems such as integer factorization and the discrete logarithm problem. These problems can be solved efficiently by quantum algorithms (using Shor’s algorithm), making today’s cryptographic systems vulnerable to future large-scale quantum computers. Post-quantum cryptography seeks to replace these vulnerable systems with new cryptographic primitives based on mathematical problems believed to remain hard even against quantum adversaries. While recent standardization efforts have primarily focused on basic primitives such as encryption and digital signatures, many emerging applications, including decentralized systems and privacy-preserving protocols, require more advanced cryptographic functionalities. This project addresses this gap by designing and analyzing post-quantum cryptographic protocols with advanced features. The research focuses on algebraic structures arising from lattices, error-correcting codes, and group actions, including isogeny-based cryptography. Key objectives include the construction of protocols supporting advanced functionalities such as blind signatures, threshold signatures, multisignatures, and verifiable random functions, together with rigorous security proofs based on well-defined computational assumptions. The central methodological tools include zero-knowledge proofs and group action frameworks. The project will also investigate improvements in efficiency, security, and scalability of the protocols. Expected outcomes include new provably secure cryptographic schemes, conceptual advances in the use of algebraic methods for post-quantum cryptography, and contributions to the training of students through research mentoring and outreach activities. 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 · 2026-04

Summary Per- and poly-fluoroalkyl substances (PFAS), commonly referred to as 'forever chemicals' are pervasive environmental contaminants that present a significant risk to human health and the environment. In recent years, there has been increasing focus on investigating their toxicity and pathogenicity; however, our understanding of their toxicity remains in its early stages. Previous research has demonstrated that PFAS molecules preferentially bind to proteins in a manner correlated with the length of their carbon chains. Additionally, PFAS exposure has been shown to interfere with global and genome-wide DNA methylation. Despite these findings, significant knowledge gaps remain in our understanding of the interaction between PFAS and nucleic acids. This project aims to investigate the binding properties of commonly encountered PFAS molecules with nucleic acids of diverse nucleobase compositions by employing a series of optical and thermodynamic analysis methods. The conformational changes in nucleic acids following interaction with PFAS molecules will be investigated using circular dichroism (CD) and UV-vis spectroscopy, hydrodynamic viscosity testing, Atomic Force Microscopy (AFM) and Transmission Electron Microscopy (TEM). The binding affinity will be examined by measuring the melting temperature (Tm), binding enthalpy (ΔH), and equilibrium association constant (Ka). The stoichiometry (n) and driving force of each interaction will be assessed by analyzing Gibbs free energy (ΔG), entropy change (TΔS), and changes in constant pressure heat capacity (ΔCp) via Isothermal Titration Calorimetry (ITC). Investigating the interaction between PFAS and nucleic acids will enhance our understanding of the binding preferences of different base pairs or sequences with PFAS molecules of varying carbon-chain lengths and functional groups, as well as the impact of PFAS on the ecosystem and human health. Furthermore, this research will provide essential insights into potential therapeutic strategies, support the development of advanced biosensors for PFAS detection, and guide future material design.

NSF Awards · FY 2026 · 2026-01

Distributed intelligence with large amounts of local measurement data hinges on the design of devices that are capable of sensing, processing, and exchanging local information. Reliable decision-making in a collective manner is, however, a challenging task in resource-constrained scenarios, where devices are limited by communication costs and/or processing power. This project aims to develop a new framework for designing efficient decentralized algorithms such that the average proportion of wrong decisions in the network is bounded by a prescribed target threshold. This line of research has implications for a broad range of real-world applications, including environmental monitoring using battery-powered mobile sensors, coordination of unmanned aerial vehicles for target tracking, and multimedia wireless sensor networks in surveillance. The project will also provide mentoring and training of future algorithm designers. This project investigates the structural properties of optimal decision rules under the false discovery rate (FDR) control, which provides guidance for new co-design of summary statistics and aggregation mechanisms, thereby enabling efficient decentralized processing in resource-constrained environments. The research program will explore three main thrusts: (i) develop communication-efficient algorithms (measured in bits) for multi-hop networks with provable FDR control; (ii) characterize computation-efficient approximations of the optimal decision rule in both the finite-sample and asymptotic regimes; and (iii) develop distributed feature selection with FDR control when all the features are shared among devices, focusing on privacy, robustness, and computation efficiency. 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 · 2025-10

In today's interconnected digital landscape, where technology plays an increasingly crucial role in our lives, the realms of public safety and law enforcement have undergone a profound transformation. This digital convergence has opened new avenues for advanced analytics, providing valuable insights into various aspects of society, including a holistic understanding of crime dynamics. However, traditional crime analytics methods fall short in keeping up with the complexities of modern criminal activities. These methods are limited by their isolation and reliance on similar types of data and resources, making it difficult to adapt to our fast-moving, interconnected society. In response, our project presents a novel and comprehensive approach that transcends these barriers. By ensuring the protection of data and optimizing the efficiency of crime analytics processes, this project captures valuable information from diverse data sources, thereby facilitating a more robust understanding of crime patterns. The developed technologies from this research can be applied to many other fields such as healthcare, finance, and environmental monitoring. The project will integrate research with education and outreach to different groups including unrepresentative and minority students. The focus of this project is to enhance AI-driven crime analytics through the development of a federated meta-learning framework. This framework will facilitate efficient, private, and secure model training using multi-modal data. The initial research thrust focuses on creating a novel data labeling and rebalancing algorithm to promote fair model training across interconnected nodes, thereby advancing fairness in AI systems, while the integration of meta-learning during local model training tailors a proactive approach to alleviating computational burdens on individual devices, promoting practical efficiency. Building upon these foundations, the second research thrust emphasizes the handling of multi-modal data, showcasing the project's capability to navigate complexities within interdependent networks and effectively integrate diverse data sources. Finally, the third research thrust tailors distributed differential privacy mechanisms and introduces an adversarial agent classification technique, underscoring the proposal's dedication towards robust and secure model training. 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 · 2025-10

This project sponsored under the NSF Research Experiences for Undergraduates (REU) offers a summer research program on sensors and smart systems at the Florida Atlantic University, Institute for Sensing and Embedded Network Systems Engineering (I-SENSE). Smart systems are computer systems that incorporate sensing, actuation and control in order to make intelligent decisions about its operations that ensure its essential mission and purpose. Smart systems provide an excellent pathway to introduce undergraduates to the major principles and practices in computer science through their applications that undergraduates have experienced and the research challenges to ensure these smart systems are, e.g., dependable, resilient, and trustworthy. Students in this project are mentored by faculty from I-SENSE, participate in professional development activities, receive career guidance on preparing for graduate school and a career in science and technology. The REU site is led by I-SENSE faculty mentors with significant research expertise, and the I-SENSE institute provides state-of-the-art facilities to support undergraduate researchers. Students will be integrated into existing research groups and projects focused on real-world applications. The research will concentrate on three areas of application expertise: infrastructure systems; marine and environmental systems; and health and behavior. These projects span different contexts of exploration and application, unified by their emphasis on sensing and smart systems. The exploration space presents myriad challenges at the intersection of sensing, computing, signal processing, artificial intelligence, and cyber-physical control. The site’s focus and research projects offer an exceptional opportunity to catalyze interdisciplinary discovery and to engage students in high-level scientific exploration. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Individuals who chronically use alcohol have higher rates of psychological and biological perturbations including a higher incidence of mood-related disorders, inflammatory diseases, and cancers. Although we often focus on heavy drinking as being a cause for concern, problematic drinking patterns evolve from recreational use where repeated alcohol consumption alters homeostatic central and peripheral mechanisms. Recent work has suggested that the blood-brain barrier (BBB) is a critical interface that supports appropriate reactions to stress- eliciting stimuli, but how alcohol impacts BBB integrity and the subsequent peripheral/central interactions, remains largely understudied. Using a rodent model of volitional binge-drinking, I have found that chronic exposure to alcohol increases peripheral inflammation and promotes stress-susceptibility, even after a protracted withdrawal period. Moreover, mice with a history of alcohol have increased circulating levels of neutrophils at baseline and show an exaggerated release of the serine protease, neutrophil elastase, in response to a mild social stressor. Given the proteolytic nature of neutrophil elastase, I will use novel approaches to identify region- specific alcohol-induced BBB permeability and characterize the underlying mechanisms contributing to BBB breakdown with a focus on understanding neutrophil: endothelial cell interactions and how they contribute to complex mood-related behavioral alterations. Importantly, I have begun to investigate how inhibition of neutrophil elastase can promote adaptive responses to stress-eliciting situations. The data I have collected thus far support a novel peripheral mechanism by which alcohol exposure mediates stress-susceptibility and offers insight into managing peripherally-mediated CNS dysfunction. I am confident that this multifaceted approach will provide the scientific community with novel insights that can help guide the development of innovative therapeutic approaches targeting the immune system, which are desperately needed in the field of comorbid substance use and mood disorders.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Children with obesity are at increased risk for dose-related medication errors during emergency care, when compared to children with healthy weight. Inaccurate weight estimates or the use of incorrect dosing scalars are the most important cause of these errors. Ideally, estimates of both total body weight and lean body weight should be available for calculation of lipophilic and hydrophilic drug doses, respectively. This is a critical safety issue. The PAWPER XL-MAC tape is a well-studied device, designed for weight estimation in pediatric emergencies. However, the tape has suboptimal accuracy in estimating total body weight in children with obesity. It also needs to be upgraded to provide estimates of lean body weight in addition to total body weight to facilitate optimum drug dose calculations in children with obesity. The goal of this project is to upgrade the PAWPER XL-MAC tape, to be accurate and reduce the risk of potentially harmful dosing errors in the treatment of pediatric patients. The central hypothesis in this project is that the PAWPER XL-MAC tape system can be modified to improve the accuracy of TBW estimates in children with obesity and to provide accurate estimations of LBW in children and adolescents. This hypothesis will be tested by pursuing three specific aims: (1) Assemble two large datasets for the secondary analysis; (2) Recalibrate the existing TBW estimates produced by the PAWPER XL-MAC tape in children with obesity; and (3) Develop and validate a model to estimate LBW in children using the PAWPER XL-MAC tape. Important secondary aims will be to extend the PAWPER XL-MAC tape to ensure all adolescents can receive a weight estimate, and to investigate the relationship between IBW standards and measured LBW in children and adolescents. Our aims will be addressed in two database studies. Firstly, we will pool datasets from the National Health and Nutrition Examination Surveys from 1999-2000 to the present (33,683 children and adolescents), and a validated dataset of 2,434 pooled nutritional anthropometric surveys from 51 low- and middle-income countries (1,717,172 children). In the first study we will recalibrate the existing TBW estimates of the PAWPER XL- MAC tape in children with obesity and severe obesity to enhance its accuracy. We will also extend the length of the tape to ensure it can provide weight estimations for adolescents. In the second study, we will develop a model to estimate LBW using recumbent length and MAC as input variables. We will also investigate the relationship between IBW standards and measured LBW in children. We will use methodology that we have previously devised in the development of the pediatric and adult versions of the tape. The proposal is relevant to the NICHD’s mission of leading research and training to enhance the lives of children and adolescents. In this proposal, the focus on prioritization of patient safety in a patient group already at high risk of poor outcomes from acute illness or injury, is faithful to that mission.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Metabolic disorders represent one of the largest burdens in our society, with an estimated 10-30% of adults affected by metabolic syndrome and over 11% of Americans diagnosed with diabetes. While genes that contribute to feeding and metabolism are well described, these phenotypes are highly polygenic, and the influence of individual alleles is shaped by genetic architecture. As such, a critical gap exists in our understanding of how naturally occurring genetic variation shapes feeding behavior and metabolism. Evolutionary medicine offers a powerful approach to explore how naturally occurring genetic variants impact feeding states, and the role genetic architecture plays in shaping these alleles. Evolution provides natural experiments that shape phenotypes in unique ways, and understanding how these phenotypes arise offers insights into how they change across taxa, including humans. We use the blind Mexican cavefish, Astyanax mexicanus, as a model to understand how naturally occurring genetic variation shapes feeding and metabolism. Astyanax exists as a single species in two forms: multiple populations of eyed, surface-dwelling fish and at least 30 populations of blind cavefish. We have shown that cavefish are hyperphagic, perpetually insulin-resistant (akin to diabetic), and exhibit slowed metabolism. We have also identified naturally occurring mutations in two well-known feeding receptors: melanocortin 3 (MC3R) and melanocortin 4 (MC4R). While the role of MC4R is well understood, much less is known about MC3R, and very little is known about how natural variations in these two receptors shape feeding. This proposal leverages innovative approaches developed in my lab over the past seven years to address this problem from a multidimensional perspective. Aim 1 will explore how MC3R and MC4R work together to regulate feeding and the impact of genomic architecture on these alleles. Aim 2 will use CRISPR-Cas9 to swap MC3R and MC4R alleles between surface fish and cavefish, allowing us to examine the impact on feeding behavior and neural activity in feeding centers. Aim 3 will assess brain-wide development in cavefish and explore the role of MC3R and MC4R in these processes. This proposal is innovative in its use of CRISPR-based allele swapping and advanced brain imaging techniques to uncover the genetic and neural mechanisms underlying these phenotypic variations. The overarching goal is to bridge the gap between laboratory-generated mutations and the complexities of natural genetic diversity, providing insights that could inform our understanding of obesity and metabolic disorders in humans.

NSF Awards · FY 2025 · 2025-09

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive federal fellowship program. GRFP helps ensure the quality, vitality, and strength of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM), including STEM education. GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant achievements in STEM. This award supports the NSF Graduate Fellows pursuing graduate education at this awardee institution. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Autonomous robots are increasingly deployed in practical applications like agriculture, aquaculture, and environmental monitoring. However, operating in large, remote, and uneven environments presents major challenges due to limited battery life and strict timing requirements. This project develops a new robotic system that enables robots to plan efficient paths while ensuring on-time task completion. The research advances the sustainability, reliability, and cost-effectiveness of mobile robots for these important sectors. This project addresses three interrelated research tasks: (1) developing methodologies for building energy-cost maps for large, uneven terrains using multi-modal learning models that integrate terrain images, elevation data, and robot states collected via aerial-ground collaboration; (2) designing time- and energy-aware path planning algorithms that optimize both navigation energy consumption and task completion timing with theoretical performance guarantees; and (3) integrating these models and planning algorithms into an autonomous robotic system for fish farm operations to validate its practical performance. Together, these efforts aim to enable reliable, energy-efficient, and time-sensitive robot deployments in unstructured environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The purpose of this project is to plan and organize the 2025 National Science Foundation (NSF) Principal Investigator (PI) Meeting of Computer System Research (CSR) Program, held in Boca Raton, FL Sept 17-18, 2025. The purpose of the meeting is to bring together active PIs and Program Directors (PDs) to exchange information and ideas to continue to advance research and explore new computer systems research directions. The program is planned for two days and will include keynotes, presentations by the PIs of featured projects, panel discussions, breakout meetings, poster sessions, an evening reception, and "office hours" with Program Directors. Successful outcomes of this work will inform both PIs and NSF PDs. 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

Einstein's General Relativity is the theory that describes the physics of a classical gravitational field. The theory of General Relativity (GR) is successful in understanding the fundamental aspects of space-time and making predictions for the evolution of the universe and various astrophysical phenomena. However, it is well-known that GR is incomplete. It loses its capability of making predictions in the extremely strong gravitational field (e.g., inside a black hole, or at the very early stage of the Universe during the Big Bang). One of the most fundamental open questions in physics is how to complete GR to predict physics in an extremely strong gravitational field. This project aims toward the complete theory of gravity called "Quantum Gravity". The theory of Quantum Gravity is expected to play a crucial role in describing the physics inside black holes and in the early Universe. Eventually, Quantum Gravity will lead to a revolutionary understanding of space-time and advance the research of fundamental physics as well as applications in all aspects. Additionally, this project includes activities in physics education at university and general public levels. This award supports the development of a candidate Quantum Gravity theory known as "Loop Quantum Gravity" (LQG). LQG is a theory featuring the background independence and non-perturbative quantization of spacetime structure. This project focuses on developing the theory of LQG with cosmological constant in 4 dimensions, in particular, the spinfoam formulation of the theory. The main objectives and tasks of this project are: (1) to advance numerical methods for spinfoam models, both with and without cosmological constant, (2) to develop an effective theory from spinfoam LQG, connecting to the semiclassical consistency, corrections to Einstein gravity, and entanglement entropy, (3) to investigate and understand the physical implications of spinfoam LQG in scenarios such as bouncing cosmology, black-hole-to-white-hole transitions, and matter couplings, and (4) to develop the combinatorial quantization of the SL(2, C) CS theory with a complex level, which underlies the spinfoam model with cosmological constant, and to clarify its relation with the quantum Lorentz group. 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

Students diagnosed with autism spectrum disorder (ASD) possess many critical qualities and characteristics associated with success in computing fields. Studies have shown that post-secondary graduation rates for students with ASD are lower than the general student population. Several studies have identified underdeveloped verbal/non-verbal communication abilities and social skills as significant factors to these attrition rates. The goal of the Neurodiversity Research Innovation Experience (NEURODRiVE) program is to support students so that they can successfully pursue and obtain employment in computing fields. Special attention will be given to creating workforce opportunities for Palm Beach State College (PBSC) students diagnosed with ASD, as this underutilized talent pool is of strategic importance to Florida. By providing tailored support and immersive learning experiences, NEURODRiVE will improve educational and employment outcomes for all PBSC students. The project team will leverage the power of incorporated technologies that provide progressive, scaffolded experiences leading to real-world relationships in academic and career settings. The program will expose students to customized AR/VR modules where they will learn to navigate verbal/non-verbal communication and social skills in simulated workplace situations. The program will encourage participants to evaluate, critique, and present their AR/VR module experience to practice peer-to-peer communication skills. Industry partners will participate in the development of simulated job interviews in a VR environment to assist students in familiarizing and preparing for internships and job interviews. PBSC will work with local industry partners to provide internships for participating students. The project team will provide “flip-side mentorship” training for faculty and industry partners on evidence-based communication techniques that support student success in the classroom, and the workplace. 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 2025 · 2025-05

Project Summary Amphetamine (Amph) and Amph-like drugs are commonly abused psychostimulants that come with a high addiction liability. Numerous studies have shown that Amph alters the function of various proteins in the brain. Among others, proteins linked to dopamine signaling are major targets of Amph. However, despite decades of active research, the full picture of how Amph generates addiction remains far from completely understood. For example, while it is well accepted that the increase of extracellular dopamine induced by Amph, as well as by all other addictive drugs, is the first step toward addiction, it is unknown how this increase in dopamine generates physiological and behavioral modifications that ultimately lead to addiction. To identify novel proteins that will help us to elucidate the mechanism of action of Amph, we have designed a forward genetic screen using mutated strains from the Million Mutations Project (MMP). The MMP is a collection of C. elegans mutants containing already mapped and identified mutations in specific genes. Thus, using the MMP strains for a genetic screen facilitates the identification of the gene required for the behavior the screen was set for. We will screen these mutants for Amph-induced behaviors and select animals that do not respond to Amph treatments or exhibit a hyper-response to Amph. Then, using the MMP database and the genetic tools offered by C. elegans, we will identify the genes responsible for the altered response to Amph.

NSF Awards · FY 2025 · 2025-05

This Engineering Research Initiation (ERI) award supports research that looks to solve the coupled problem of optimal and stable topology selection for multi-robot systems in a real-world environment, thereby promoting the progress of science and securing the national defense. This project will focus on development of distributed solutions to the optimal topology selection problem among robots with asymmetric interactions where robots have different sensor modalities. Conventionally, centralized computation and perfect localization is assumed for multi-robot systems. However, when a system is deprived of such a setting, robots in a team must rely on robust one-to-one interaction using on-board sensors. This project looks to select an optimal set of robot-robot interactions to conduct stable multi-robot coordination using distributed algorithms. This research seeks to enable more robust coordination of multi-robot systems to environmental conditions such that these teams of robots can be used in out of lab settings without depending on any centralized base station. Multi-robot coordination has viable applications from enhancing agricultural yield by monitoring crops, to automating safety of critical infrastructure like power stations, and acting against adversaries. Furthermore, both undergraduate and graduate students will have the opportunity to participate in interdisciplinary working groups for early career professionals focused on translational research and pedagogy. This research aims to make fundamental contributions to multi-robot systems which are stable and robust in coordination to carry out tasks. It looks to achieve this goal by formulating an optimal topology selection problem and developing scalable control-theoretic methods for topology control that guarantee stability and robustness to disturbance in the presence of asymmetric robot interactions. The project takes a multi-tiered approach to: i) solve a distributed optimal topology selection problem; ii) validate the algorithms in high-fidelity physics based simulations, and iii) test the algorithms on a team of unmanned aerial vehicles, in real-world conditions using the off-the-shelf robotic and sensor platforms. The optimal topology selection problem for multi-robot systems will be formulated as complex mixed integer semidefinite programs. This research seeks to extend the scope of applying chordal decomposition combined with the alternating direction method of multipliers method to exploit sparsity in large semidefinite programs. The testbed will be developed at the state-of-the-art facility at Florida Atlantic University’s SeaTech, Dania Beach campus which is already equipped with a team of unmanned aerial vehicles and a OptiTrack motion capture system for robot localization. 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 · 2025-02

This award supports the 56th meeting of the Southeastern International Conference on Combinatorics, Graph Theory and Computing, to be held March 3-7, 2025 at Florida Atlantic University in Boca Raton. The conference has been held annually since 1970, in Baton Rouge, Louisiana and Boca Raton, Florida, bringing together a good mix of senior and junior researchers in various subareas of Combinatorics. The Fifty-sixth Conference will feature a series of instructional lectures by distinguished mathematical scientists that comprise a mix of established senior speakers, current "stars," and promising newcomers. The plenary speakers for this conference are Jack Edmonds, Jan Goedgebeur, Emily Heath, Donald Kreher, and Joel Spencer. Apart from plenary sessions there are sessions for contributed papers. Specific topics that will be addressed at the conference through special sessions are algebraic combinatorics, graphs and matrices, and graph decompositions. The conference website can be found at https://www.math.fau.edu/combinatorics/index.php 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 · 2024-11

Hurricane Helene made landfall as a Category 4 storm on September 26, 2024, delivering 12-16 inches of rainfall and a 9-foot storm surge to Florida’s Gulf Coast karstic coastlines. During hurricanes, the combined effects of intense rainfall, storm surge, and flooding can enhance groundwater recharge and discharge, intensify aquifer salinization, mobilize contaminants, and deteriorate both groundwater and surface water quality. For example, sudden discharges of nutrient-rich groundwater following extreme precipitation events have been associated with phenomena like planktonic blooms and red tides. Although groundwater-surface water interactions and aquifer salinization in coastal areas are widely studied, most research were conducted during regular weather conditions, potentially underestimating the magnitude of extreme events on coastal aquifer dynamics. Therefore, this study aims to assess both the immediate and long-term effects of hurricanes on hydrogeology and nutrient geochemistry in karstic aquifers. The findings will inform coastal management strategies and improve hydrogeological model predictions, helping to mitigate hurricane-induced impacts on coastal ecosystems and water resources. This project will foster collaboration between two early-career researchers and actively involve undergraduate and graduate students, including those from underrepresented minorities, with results integrated into Texas A&M University at Galveston and Florida Atlantic University courses. This project will employ interdisciplinary hydrological, geophysical, and geochemical methods to: (1) Evaluate the degree of aquifer salinization and its effects on nutrient speciation, and (2) Quantify groundwater discharge and nutrient fluxes. Electrical resistivity tomography (ERT) will be used to assess aquifer salinization, while radon-222 will be utilized to quantify groundwater discharge. Nutrients and major ion concentrations will be measured from groundwater and surface water samples, with analyses focused on how hydrochemical patterns affect nutrient speciation. The research will be conducted post-hurricane and during baseflow conditions, enabling an assessment of the hydrological disturbances caused by the hurricane on aquifer salinization, groundwater-surface water interactions, and nutrient geochemistry, as well as tracking their progression over time. Additionally, the project will build on previously collected post-storm data from Alabama and Texas, allowing for a comparative analysis of groundwater system responses across different aquifer types (porous and karstic) in the Gulf Coast. This is especially relevant, given that the region is among the most vulnerable in the U.S. to the impacts of extreme weather events and climate change. 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 · 2024-11

Ecological instability has important implications for communities and ecologies, and cultural adaptations may support resiliency when facing resulting challenges. This collaboration between Florida Atlantic University and the University of Puerto Rico at Cayey examines how communities adapt culturally to environmental disruption and climate instability in an ecologically sensitive area. The Rhizomatic Nexus project studies similarities and differences that exist in the social experiences of people located in different but interconnected places in the Caribbean, focusing on cultural responses to climate instability in the "Hurricane Alley" between South Florida and Puerto Rico. This project creates and supports ethnographic laboratories at two MSIs to study how people adapt socially to environmental changes. The investigators study how communities adapt and respond to sustained ecological instability through the lens of culture. The work builds research capacity and provides mentorship opportunities for faculty and students. The goal of the project is to understand how people from diverse cultural backgrounds and life experiences deal with and respond to ecological instability by conducting research with communities under pressure from environmental change. This research highlights the challenges and opportunities faced by people living in rapidly fluctuating ecologies alongside failing or damaged infrastructures. Understanding cultural responses and adaptation to ecological instability can generate important and actionable insights that connect communities and individuals across and beyond the Caribbean, including coastal communities and island societies around the world. 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

Efficient memory processes rely on our brain's ability to store similar experiences as distinct memories. This process, performed in part by a structure in the brains of mammals called hippocampus, facilitates memory discrimination and is affected in brain disorders like dementia and post-traumatic stress disorders. As a result, animals and people suffering from these disorders experience difficulties recalling or accurately retrieving memories. Our understanding of how the hippocampus encodes similar experiences as distinct memories, allowing for easy discrimination during recall, is still limited. Recent advancements in neuroscience suggest that coordinated activity between excitatory and inhibitory neurons enables a specific computation known as pattern separation within the hippocampal circuit. This computation transforms similar input patterns into highly dissimilar output patterns and is thought to be the basis for memory discrimination. In the proposed research, the investigators aim to determine the contribution of a specific type of inhibitory neurons called cholecystokinin-expressing (CCK) neurons to the hippocampal circuit’s function. Their long-term goal is to enhance our understanding of critical computations, like pattern separation, performed by this brain region, which are crucial for memory discrimination. As part of this project, the investigators also provide a strong educational and training environment to students and new generations of scientists, and they participate in outreach programs, such as the Big Brother Big Sister event organized by the Reno Museum of Natural History, which they use as a platform to share their research with the general public and students of all ages. The investigators aim to determine the contribution of CCK neurons to hippocampal circuit function, focusing on the plasticity of CCK neurons during the developmental period of juvenile mice. Their previous work demonstrates that environmental enrichment (EE) leads to increased synapses formed by CCK neurons in the dentate gyrus, suggesting their involvement in the maturation of hippocampal function and pattern separation. For the proposed work, they use an EE paradigm in mice and take advantage of viral mediated gene delivery technique combined with optogenetic approaches to manipulate the activity of the CCK neurons. They determine how the remodeling of the inhibitory CCK network adjusts the computation in the DG. In the first Objective of the project, they determine the contribution of CCK neurons to feedback and feedforward inhibitory microcircuits, both of which can impact pattern separation. In the second Objective, they measure the change in pattern separation and filtering performance of the DG induced by the EE using a novel in-vitro electrophysiological protocol. Together their research aims to unravel the mechanisms underlying pattern separation by exploring the involvement of CCK neurons in the hippocampal circuit. By increasing our understanding of these fundamental computations, they will shed light on the processes that support efficient memory functioning and potentially contribute to the development of novel therapeutic approaches for memory-related disorders. This project is jointly funded by the Modulation Program of the Neural Systems Cluster in the BIO Directorate and the Established Program to Stimulate Competitive Research (EPSCoR). 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

Marine animal tracking, at both individual and group levels, is crucial for wildlife conservation. It provides essential information and invaluable insights into population dynamics, health, risks, and vulnerability, all of which help shape conservation policies, management decisions and strategies. Traditional tracking methods face significant challenges in balancing cost and precision. They either require attaching transmitters to animals that communicate with radio receivers or satellites (high accuracy but expensive and invasive) or rely on manually produced sketches from photos of distinctive features such as scars (low accuracy and labor-intensive). The overarching goal of this project is to optimize this cost-precision trade-off by designing and delivering an artificial intelligence (AI)-driven system for individual photo-identification and tracking in conservation studies of Florida manatees, a threatened species. The system aims to streamline the creation, maintenance, query, and behavior analysis of manatees using photo-identification. This project will train several graduate students, and will advance collaboration between AI researchers and conservation scientists. In order to bring transformative advancements to current conservation capabilities, emphasizing cost-effective, evidence-based conservation planning, the project will 1) develop new algorithms grounded in explainable AI to identify and track individual manatees by their distinctive features, such as scars and markers, which serve as interpretable evidence for tracking; 2) support long-range spatio-temporal tracking by representing each animal as a series of sketch images throughout their lifespan, annotated with timestamps, geographic information, and metadata on life encounters; and 3) craft a framework for region-based conservation resource planning and management that models evolving patterns in local regions, including both natural and human-caused disturbances, to assess how local animal populations react to these regional changes. The collaborative research team will also extend approaches to additional threatened or endangered marine species (sea turtles, whales, rays). This project will have a lasting impact on the research community and education sectors by highlighting critical needs and showcasing viable design ideas in both conservation and computer science, and in their nexus. This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program. 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 Pain is a major global health problem, causing a significant economic and social burden. Most clinically used opioid drugs are -opioid receptor (MOR) agonists with liabilities of tolerance, physical dependence and addiction mediated by this receptor. Centrally acting kappa-opioid receptor (KOR) agonists also inhibit pain, but without abuse potential and without the adverse side effects associated with MOR agonists. Antidepressants that target neurotransmitters serotonin and norepinephrine relieve pain in patients with chronic neuropathic pain syndromes. However, KOR agonists and antidepressants are not perfect. KOR agonists developed to date exhibit undesirable dysphoria and aversion, while antidepressants have not been successful in all pain conditions. Thereby, there is a large unmet need for innovative therapies for pain management. The overall goal of the proposed research is to develop novel peptide analgesics, for use along the entire continuum of care, as an alternative to the existing treatment options for acute and chronic pain. Peptides have long been recognized for their roles in the normal function of the central nervous system (CNS), making them particularly attractive candidates for the discovery and development of novel pain medications. Conventional methods of drug administration such as oral or intravenous are inefficient in delivering peptides to the brain. Both the blood-brain barrier (BBB) and blood-cerebrospinal fluid barrier (BCB) restrict the transport of these therapeutic agents from blood into the CNS. Alternatively, intranasal (i.n.) delivery may be a route of administration that would allow therapeutic peptides to bypass the BBB and BCB and directly enter the brain. To address the need for novel therapeutics to treat acute and chronic pain syndromes, we designed new cyclic peptide-based analgesics suitable for i.n. delivery that combine selective KOR agonist and antidepressant pain reliving mechanisms. Combining KOR agonist activity with simultaneous delivery of norepinephrine and/or serotonin may improve pain management when more than one physiological mechanism or system is implicated and may potentially minimize side effects associated with the KOR activation. The proposed cyclic peptides represent a new class of analgesics structurally distinct from the commonly prescribed pain medications. To further validate our approach for the design of novel cyclic peptide-based analgesics we propose to: (a) further improve the analgesic properties of the OL-based cyclic peptides and minimize or eliminate undesired side effects by modifying amino acid sequences using rational synthetic approach based on our previous studies (Aim 1), (b) assess metabolic stability and nose-to-brain transit of selected peptides in mice (Aim 2); (c) assess the therapeutic potentials of selected peptides in well-established pain rodent models and identify lead OL-based cyclic peptides (2 peptides) with improved analgesic activity and reduced or complete absence of abuse ability and side effects for further development (Aim 3).

NSF Awards · FY 2024 · 2024-09

This Major Research Instrumentation (MRI) grant will develop a multi-agent AI system of (a) three bio-inspired underwater vessels integrated with multimodal (optical and acoustic) underwater communication interfaces and (b) a buoy operating as an underwater/sea-surface control station. Progress in cooperative multi-agent underwater systems is fundamental for the short and long-term study of ocean and coastal zones, but integration of effective technologies to develop a network of underwater vessels is still limited. Contrary to land and air, 3D underwater robotic systems have not yet been able to achieve comparable levels of self-organization. Technical issues that impede operation in complex unknown underwater environments include 1) localization and communication to determine the exact position of each vessel; 2) efficient propulsion systems that allow the vessel to maneuver in multiple directions and perform precise station-keeping; and 3) effective autonomous control schemes able to adaptively optimize vehicle- and fleet-operation in time-varying uncertain environments. The school of connected vessels developed under this project will enhance our understanding of the hydrodynamics and control of multi-swimmer systems, advance the theory and practice of programmable multi-function underwater networks, and enable effective and efficient survey of sensitive coastal zones. Moreover, this project will help broaden participation and training of underrepresented minorities in engineering and support outreach activities for high school students and the general audience. The development of the connected three-vessel-and-buoy instrument will support research and training at the intersection of three emerging technologies: 1) bio-inspired propulsion and the dynamics of collective swimmers; 2) artificial intelligence applied to underwater mobility and 3) programmable underwater multi-modal networking. In specific, outcomes of this project are: (a) a bio-inspired underwater vessel with undulating fin propulsion and integrated communication and sensing capabilities (three copies); (b) a software-defined protocol stack for underwater multimodal communication, networking and positioning; (c) a connected multi-agent system of three bio-inspired robotic fish with the ability to autonomously coordinate, share information and cooperate for a basic mission or to be wirelessly remotely controlled by a single human operator. At conclusion, this effort is expected to provide a stable, shared-use, programmable research instrument with unique propulsion and integrated wireless networking and positioning capabilities. The instrument will enable rapid testing and repeatable comparative evaluation, while also strengthen collaboration and partnership between different institutions interested in research in AI control, bioinspired underwater mobility and underwater wireless networking. The instrument will also serve as an experimental platform to train undergraduate and graduate students at the intersection of multiple engineering fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The Florida Atlantic University Marine Science Lab is located within the Gumbo Limbo Environmental Complex in Boca Raton, Florida. This lab is adjacent to an estuary and across the street from the Atlantic Ocean. Its location enables scientists to conduct subtropical marine research on a range of organisms, including some species of sharks, rays, marine plants, and threatened and endangered sea turtles. While national and international researchers, as well as students and postdocs, have conducted research at the lab, the facility has been limited by an insufficient sea water system, and no outdoor facilities for research. These limitations restricted the variety of organisms that could be studied. Recent investments by the City of Boca Raton and the Gumbo Limbo Coastal Stewards (a local nonprofit organization) to upgrade the lab’s seawater system have vastly improved sea water conditions and availability. This award will provide crucial resources to expand the research infrastructure of the lab and provide outdoor research tanks, flexible plumbing arrangements for experiments, secure fencing, back-up power, and additional educational displays. These enhancements will allow a broader array of marine organisms to be studied and will support three to four times the number of research projects that can be conducted at the lab per year. More robust research studies will also benefit the larger community, promoting greater science awareness and understanding to the more than 220,000 members of the public that visit the environmental complex every year. Historically, several factors have limited the range and variety of research that could be conducted at the Florida Atlantic University Marine Science Lab. The old seawater system delivered air-saturated water that many marine organisms could not tolerate, restricting lab users to research with air-breathing species. There are no outdoor water tables or even moderately deep tanks in the lab tank inventory. Many marine study systems and species benefit from or require natural light and photocycles. This award will enable expansion of the exterior holding and experimental tank capacity by adding outdoor tanks and flexible configuration water table facilities. Outdoor tanks and water tables will facilitate concurrent experimental and control study designs, plus provide holding space adjacent to experimental space. Additionally, funding will facilitate construction of mandatory secure enclosures around outdoor tanks and water tables Retractable shade covers add versatility. Supply and drainage lines for these tanks for raw or filtered flow-through seawater provide essential resources. A dedicated generator to ensure continuity of water distribution and treatment, as well as data acquisition in the event of power outages, will also be acquired. The award will support the sharing of research with the larger community via additional new weather-tolerant displays, reflecting contemporary studies. The infrastructure improvements award will lead to more timely and innovative research and will enhance research at the lab on biology of diverse marine life including sea turtles, fishes – especially of elasmobranch fishes, diverse invertebrates, as well as mangrove, algal, and seagrass community studies. This award by the Infrastructure Capacity for Biological Research program within the Division of Biological Infrastructure is jointly supported by the Division of Ocean Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY PTP1B, a non-receptor–type oncogenic PTP, also known as PTPN1, is involved in growth factor signaling. The PTP1B gene is frequently amplified in cancers and correlates with poor prognosis. However, despite the attractiveness of PTP1B as a therapeutic target, the development of drug-like inhibitors of this enzyme has proven difficult, primarily due to low cell permeability and a lack of selectivity towards other PTPs. While numerous investigators are developing traditional types of inhibitors that target the reduced, active form of PTP1B, targeting PTP1B-ox has important advantages relating to inhibitor bioavailability and selectivity. The goal of this proposal is to develop charge neutral inhibitors that specifically target the oxidized form of PTP1B (PTP1B-ox), which exists principally in the disease state. This approach was validated in a recent study showing that single-chain variable fragment antibodies can stabilize oxPTP1B and, in so doing, modulate signaling pathways related to energy metabolism and cancer. In Aim 1, we will prepare and evaluate diverse sulfenic acid-reactive combinatorial libraries. In Aim 2, we will screen libraries prepared in Aim 1 to identify compounds that target oxidized PTP1B. Based on our expertise in targeting distinct redox forms of therapeutically important proteins and innovative chemistry (Nat. Chem. Biol. 2012, 2018, 2023 and Nat. Chem. 2021), we will almost certainly identify molecules that target and stabilize the oxidized form of PTP1B. These nucleophilic compounds will lay the foundation for future studies on this topic as an R21 proposal to examine potency and SAR in cellular assays.