Funded Research Projects

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14641/189

An index of publicly funded research projects conducted by Texas A&M affiliated researchers.

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2020 DOD CySP Texas A&M University
Cybersecurity Center; TAMU; https://hdl.handle.net/20.500.14641/345; DOD-National Security Agency
Project Description: The Texas A&M Cybersecurity Center's CTF outreach program’s goal was to develop and deploy a CTF-based engine for students, teachers, and schools participating in the SkillsUSA Texas and TIVA institutions. Although Fall 2020 and Spring 2021 witnessed most schools still in virtual learning mode and all face-to-face conferences either canceled or moved to a virtual format, the Texas SkillsUSA Cyber competition was held virtually. To prepare the highschool students a short “teaser” ctf competition was help in fall 2020. This was the first year that the Texas A&M TAMUctf development team developed and hosted the Texas SkillsUSA cyber competition, which had three two-student teams from two Texas high schools. The CTF competition was a one-day event lasting six hours, allowing the student development team to improvise and modify the CTF format as the day progressed. The development team paused the CTF based on feedback received during the competition and provided short "lessons" on the challenges that the competitors struggled with. The most significant highlight of the project was that one of the Texas teams secured second place in the National SkillsUSA competition, with the Texas competition being a significant factor in their win. The TAMUctf development team has been requested to develop and host the Texas Competition for 2022!
2020 STARTALK Texas A&M University
Teaching, Learning And Culture; TAMU; https://hdl.handle.net/20.500.14641/414; DOD-National Security Agency
In collaboration with College Station Independent School District in Texas, we propose a summer program that provides engaging and stimulating language and culture learning experiences in Chinese and Korean to a total of 60 non-heritage language learners in 2nd/3rd grades. In the four-week program, students will develop communicative competence and cultural awareness in Chinese/Korean through the theme A Trip to East Asia. They will follow four characters on a trip to China/Korea, learn to use the target language with authentic materials and in culture-rich contexts. Standards-based and thematically-organized curriculum will be developed and implemented by a team consisting of language teachers, graduate students, and university faculty who are proficient in the target languages and cultures, knowledgeable about the U.S. education system, and experienced in implementing world language pedagogy. Students’ learning of the target language and culture will be further reinforced through the use of technology and STEM project learning.
2022 John A. Knauss Fellowship Application #2 Ed Higgins
Sea Grant Program Office; TAMU; https://hdl.handle.net/20.500.14641/471; DOC-National Oceanic and Atmospheric Administration
U.S. Senate Operations—gain an appreciation of the operations of the U.S. Senate, personal offices such as Senator Schatz’s, and committee offices: the respective responsibilities of personal and committee offices, and how they accomplish the business of the Senate and the Congress; how Members and staff interact. Legislative Business—familiarity with floor process in the Senate to debate legislation and consider the President’s nominees; familiarity with Committee and Subcommittee process to conduct hearings, hold executive sessions, and conduct negotiations with other Member offices and House committee staff; analysis of bill and report language, and development of amendments to both. Strategic Interactions—development of a trajectory of meetings and interactions with other personal offices, committee offices, federal agencies, and non-federal stakeholders that achieves a specific operational/execution goal, and establishes an enduring relationship.
A Conference on the History and Legacy of the 1919 Canales Investigation in Texas
History; TAMU; https://hdl.handle.net/20.500.14641/552; National Endowment for the Humanities
A Multiscale Approach to Magnesium Intercalation Batteries: Safer, Lighter, and Longer-Lasting: Justin Andrews
Chemistry; TAMU; https://hdl.handle.net/20.500.14641/219; NASA-Washington
1. EXECUTIVE SUMMARY: Research Goal: The goal of this research has been to design and develop the basic building blocks of inherently safer electrochemical energy storage vectors as replacements for conventional Li-ion batteries. A focus was placed on exploring metastable phase space to identify viable vanadium oxide cathode materials that are capable of reversibly inserting multivalent ions and Li ions from aqueous electrolytes. These materials have been developed with an eye towards the design of all-printed batteries. Brief Background and Motivation: Lithium-ion batteries are the gold-standard for electrochemical energy storage due to their unrivaled combination of high voltage and exceptional specific and volumetric energy densities; however, the development of ‘beyond-Li-ion’ battery technologies has received considerable attention in an attempt to mitigate growing safety concerns, rising materials criticality constraints, and energy storage limitations enforced by the monovalency of the Li-ion. Safety issues in Li-ion batteries are derived from the intrinsic reactivity of Li and manifest in catastrophic failure arising from dendrite formation and1,2 thermal runaway,2,3 which are further exacerbated by the high flammability of most Li-ion battery electrolytes2. These safety problems are of great concern, particularly in applications, such as manned space flight, where safety and device endurance are paramount. The development of inherently safer battery technologies that do not compromise on energy storage capacity is thus an urgent imperative. In the case of Mg-ion batteries, it has been argued that the full realization of Mg batteries (i.e., an Mg battery which includes a metallic Mg anode) would enable significant improvements to both safety (e.g., it has been claimed that Mg is not dendrite forming, Mg has a higher melting point than Li thereby reducing the risk of thermal runaway)12 and energy storage density thereby making them safer, lighter and longer-lasting. Indeed, the projected improvements in the volumetric and specific energy densities enabled by this technological pivot would lead to transformational reductions in weight and volume of the packaged cells, relative to existing Li-ion cells, in principle establishing Mg batteries an immediately attractive alternative to Li-ion technology.19 However, the lack of suitable cathode materials capable of reversibly storing the highly polarizing Mg2+ (only a couple of viable oxide materials)17,20–25 has significantly stymied progress towards their full realization. In an effort to address this technological knowledge gap, this research has focused on leveraging the discovery of a successful ?-V2O5 Mg-ion cathode, a major breakthrough during the first year of this NASA NSTR fellowship, towards the development and optimization of additional cathode materials. A closed-loop design approach, has been implemented to elucidate cathode design principles based on experimental evaluation of V2O5 intercalation cathode materials and aided by first-principles calculations and synchrotron characterization techniques.20,26 This approach has led to the discovery of several new V2O5 polymorphs (?’-V2O5, ?-V2O5, ?-V2O5) that have exhibited promising results as cathode materials in Li-ion, multivalent ion, and aqueous Li-ion batteries. Attention has furthermore been given to scaling the synthesis of these materials to enable the design of large-scale prototypes. While this research has focused on the fundamental aspects of the chemistry of these materials it has also sought to achieve functional devices, with a focus on 3D printing of these materials for the design of flexible batteries.
A Natural Language based Data Retrieval Engine for Automated Digital Data Extraction for Civil Infrastructure Projects
Construction Science; TAMU; https://hdl.handle.net/20.500.14641/675; National Science Foundation
This research project will create new knowledge and resources to significantly enhance the reusability of digital data during the lifecycle of civil infrastructure assets. The rapid development of digital technologies is transforming how civil infrastructure asset data and information is produced, exchanged, and managed throughout its life cycle. Despite growing digital data availability, such data cannot be fully exploited without the ability to infer meaning from the varying data terminologies entered by practitioners. The lack of common understanding of the same data, or similar data given in different terms, preclude data exchange or can lead to extraction of the wrong data and misinterpretation. This research project will leverage the advancements in linguistics and computer science to develop a novel approach that can recognize users' intention from their natural language input and automatically extract the desired data from heterogeneous datasets. The results of this research will benefit the construction industry by accelerating the industry's transition to digital data-based project delivery and asset management. The research will also broaden engineering education by creating advanced course materials both at undergraduate and graduate levels. Diversity in data terminology creates an important hurdle for computer-to-computer communication, creating a big burden to end users who must perform the role of middleware in digital data exchange. This issue exists throughout the life cycle of a civil infrastructure asset. This project will develop a computational theory and a platform for its implementation to analyze users' plain English data requirements, and automatically match their intention to the data entities in heterogeneous source datasets based on semantic equivalence. To accomplish this goal, the research team will: a) utilize Natural Language Processing and machine learning techniques to recognize user's intention from their natural language queries, b) translate text-based domain knowledge into an extensive civil engineering machine-readable dictionary that defines meanings of technical terms using a text-based automated ontology learning method, c) design an algorithm that finds the most semantic-relevant data entities in digital data sets for a given keyword input, and d) test the performance of the algorithm in terms of its accuracy using civil infrastructure text documents such as technical specifications, design manuals, and guidelines. The research outcomes will provide fundamental tools and resources for other researchers and industry professionals for various text-mining and intelligence-inference systems. It will facilitate seamless data exchange between various proprietary software applications used during the life cycle of civil infrastructure assets, including applications involving design evaluation and selection, digital model construction, and regulation compliance checking.
A New Cryo-Ion Mobility Spectrometer for Studies of Biomolecule Hydration
Chemistry; TAMU; https://hdl.handle.net/20.500.14641/527; National Science Foundation
With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor David Russell at Texas A&M University is developing a novel instrument to study charged species surrounded by a few water molecules. The instrument being developed is called cryo-ion mobility-mass spectrometer (c-IM-MS) and it can determine the size and structure of the charge species by monitoring how they fly in a long tube under an extreme low temperature. Professor Russell's study are providing information to help understand the role of water molecules in affecting protein structure and function, especially those in direct contact with proteins. The gained knowledge will ultimately enable better understanding of many important biological and chemical questions, such as how antifreeze proteins protect plants and fish living in cold climates. The students working on this project have the opportunity to gain experience for both instrument building and biomolecule studies. The instrument design will be shared with other scientists in the field so the to-be-developed approach can be widely used to answer structural questions about how proteins and other biomolecules behave in water. During the past decade, the Russell laboratory has developed several prototype c-IM-MS instruments and described proof-of-concept studies that illustrate the unparalleled capabilities of the c-IM-MS instrument. The ability to experimentally observe structural changes that are a function of the extent of hydration is critical for establishing structure/function relationships. Such studies compliment the rapid growth in computational studies of biomolecule structure/function relationships---the ability to draw correlations between theoretical and experimental results. In this project, Professor Russell focuses on the design of the next-generation instrument by incorporating a number of recent technological innovations to include studies of larger proteins and protein complexes. He evaluates the overall instrument performance in terms of ion transmission and effects on ion dehydration and benchmark instrument performance against existing MS analyzers. The ultimate goals are to develop an instrument that is capable of better understanding peptide-water interactions and answering questions such as how does hydration affect peptide conformational preferences, and how does the peptide alter the structure of water.
A Novel Technology for Engineering Binders to Membrane Proteins
Microbial Pathogenesis And Immunology; TAMHSC; National Institutes of Health
Antibodies have been coined the ‘magic bullets’ against many human diseases. However, there remains significant challenges in the engineering of antibodies targeting multi-pass membrane proteins, which encompass a large number of therapeutic targets such as cell surface receptors and the ion channel proteins. The difficulty in engineering binders to membrane proteins stems from the limitation of the current in vitro selection/panning technologies, such as phage display, which require highly purified target protein. Unfortunately, membrane proteins are often refractory to purification due to their dependence on the cell membrane for proper folding and activity. Currently, there is no effective in vitro technology for the discovery/engineering of binders to multi-pass membrane proteins. The overall goal of this study is to develop a novel technology – SMURF (Simple proxiMity coUpled mRNA display) – for engineering protein binders to protein targets on the cell surface, thus bypassing the need to purify the target protein. SMURF combines mRNA display with the proximity-assisted-DNA-assembly phenomenon and, unlike conventional panning in which all binders to a solid support are enriched, SMURF fosters the enrichment of binders only to a desired target protein on the cell surface. In Aim 1, we will demonstrate the SMURF principle using oligonucleotides and optimize the primer sequences. Aim 2 will establish the SMURF enrichment of a model protein in a mixture of non-target proteins in solution. Finally, in Aim 3, a model protein will be displayed on the mammalian cell surface and a library of binders will be screened to demonstrate and quantify the whole-cell SMURF enrichment efficiency. The successful completion of this study will establish a novel technology for facile discovery/engineering of binders to whole-cell-displayed membrane proteins and should greatly expand the repertoire of drug targets amenable to therapeutic intervention.
A Novel Technology for Engineering Binders to Membrane Proteins
Microbial Pathogenesis And Immunology; TAMHSC; https://hdl.handle.net/20.500.14641/217; National Institutes of Health
Antibodies have been coined the ‘magic bullets’ against many human diseases. However, there remains significant challenges in the engineering of antibodies targeting multi-pass membrane proteins, which encompass a large number of therapeutic targets such as cell surface receptors and the ion channel proteins. The difficulty in engineering binders to membrane proteins stems from the limitation of the current in vitro selection/panning technologies, such as phage display, which require highly purified target protein. Unfortunately, membrane proteins are often refractory to purification due to their dependence on the cell membrane for proper folding and activity. Currently, there is no effective in vitro technology for the discovery/engineering of binders to multi-pass membrane proteins. The overall goal of this study is to develop a novel technology – SMURF (Simple proxiMity coUpled mRNA display) – for engineering protein binders to protein targets on the cell surface, thus bypassing the need to purify the target protein. SMURF combines mRNA display with the proximity-assisted-DNA-assembly phenomenon and, unlike conventional panning in which all binders to a solid support are enriched, SMURF fosters the enrichment of binders only to a desired target protein on the cell surface. In Aim 1, we will demonstrate the SMURF principle using oligonucleotides and optimize the primer sequences. Aim 2 will establish the SMURF enrichment of a model protein in a mixture of non-target proteins in solution. Finally, in Aim 3, a model protein will be displayed on the mammalian cell surface and a library of binders will be screened to demonstrate and quantify the whole-cell SMURF enrichment efficiency. The successful completion of this study will establish a novel technology for facile discovery/engineering of binders to whole-cell-displayed membrane proteins and should greatly expand the repertoire of drug targets amenable to therapeutic intervention.
A prospective cohort study to examine periconceptional influenza vaccination
Epidemiology And Biostatistics; TAMHSC; https://hdl.handle.net/20.500.14641/428; DHHS-NIH-National Institute of Allergy and Infectious Diseases
PROJECT SUMMARY Pregnant women are up to five times more likely to be hospitalized with influenza than non-pregnant women, and young infants are more than four times as likely as older children to die from influenza. To protect pregnant women and their infants, the American College of Obstetricians and Gynecologists recommends that all women who are or will be pregnant during influenza season should receive an influenza vaccine. Based on current recommendations, influenza vaccination is currently part of standard prenatal care. Despite these recommendations and the demonstrated health benefits of prenatal vaccination, fewer than 40% of mothers are vaccinated during pregnancy, and vaccination rates are especially low during early pregnancy. Concerns for the safety of vaccination on pregnancy-related outcomes are commonly cited as contributing factors to this low rate of immunization. Few studies have evaluated the risk of spontaneous abortion (SAB) associated with influenza vaccination, a pregnancy outcome which may be a particular concern for women planning pregnancy or in the first trimester of their pregnancy. To date, what studies have been conducted have had major methodological flaws. Furthermore, no study has yet evaluated the impacts of paternal exposure to influenza vaccines or the health effects of pre-conception vaccination. Limited evidence in this area can present challenges to parents and their providers while making decisions on vaccination, thereby reducing public confidence in vaccination around the time of conception. This has been demonstrated by the lower confidence reported by physicians when recommending vaccination for women in their first trimester. A common limitation to existing vaccine studies is that recruitment begins during pregnancy, meaning that women in the earliest stages of pregnancy who are at highest risk of SAB and are less likely to be vaccinated are not included in these studies. This study aims to analyze data from a cohort of women and their partners recruited prior to conception in order to evaluate the association between the risk of spontaneous abortion and influenza vaccination during the weeks prior to and after conception. This study will consider both maternal and paternal vaccination as well as the number of vaccinations received in the previous year. To address this, the research team plans to analyze data from 11,150 female and 2,540 male participants of the Pregnancy Study Online (PRESTO) cohort, a North American prospective preconception cohort study. Influenza vaccination is currently considered the optimal strategy for protecting pregnant women and their infants against influenza. Using data from a large, cohort of women and their male partners, this application will address an important issue for prenatal care in the US and other countries. Study results will be useful to clinicians when evaluating whether to make vaccine recommendations and by families in their decision-making on whether to receive influenza vaccine around the time of conception.
Accelerated Preparation of Leaders for Underserved Schools (A-PLUS): Building Instructional Capacity to Impact Diverse Learners
Educational Adm & Human Resource Develop; TAMU; https://hdl.handle.net/20.500.14641/198; Department of Education
There will be a total of 5400 school leaders who serve on campuses of diverse learners, particularly those that serve English learners, struggling learners, and economically disadvantaged students. These leaders will be served and trained in (a) culturally responsive pedagogy and leadership, (b) instructional leadership, (c) critical dialogues, (d) climate issues, (e) professional, personalized learning communities, (f) data analysis and school improvement interventions, (g) instructional improvement, and (h) strategic planning.
Acquisition of Goods and Services
Vice President For Research; TAMU; https://hdl.handle.net/20.500.14641/377; USDA - Agricultural Research Service
Acquisition of Goods and Services
Vice President For Research; TAMU; https://hdl.handle.net/20.500.14641/377; USDA - Agricultural Research Service
Active Inner Veto for Improved SuperCDMS SNOLAB Dark Matter Search Sensitivity
Physics And Astronomy; TAMU; https://hdl.handle.net/20.500.14641/329; DOE-Office Of Science
The goal of this project was to develop and study a new geometry of cryogenic detector that could act as an active veto surrounding a smaller, inner cryogenic detector. This drastically reduces the background event rates, enabling more effective rare event searches. An annular germanium detector was fabricated with athermal phonon sensors and successfully tested. A threshold of better than 10keV was desired; 4keV was demonstrated.
Adaptive Multiscale Simulation Framework for Reduced-Order Modeling in Perforated Domains
Mathematics; TAMU; https://hdl.handle.net/20.500.14641/682; National Science Foundation
Processes in perforated domains occur in many important applications. These include complex processes in soil, membranes, and filters. With current imaging techniques, detailed microscale geometries of these perforated materials can be constructed. However, it is prohibitively expensive to solve complex processes in these perforated domains due to a rich hierarchy of scales. For this reason, some types of reduced-order computational techniques are needed. The goal of this project is to develop and analyze novel computational techniques for solving challenging multiscale problems in perforated domains. The new approaches will bring the information from the detailed geometries to large-scale simulations and will improve the predictions in the simulations. This will further allow deigning new materials and optimize processes. Many current approaches for multiscale methods for problems in perforated domains have been restricted to homogenization, which is applicable when the media has scale separation. However, in many realistic perforated media, there is no scale separation, i.e., pore sizes can have a wide variety of scales. The multiscale methods of this project develop a general framework that allows rigorous and systematic reduction. The PI's goals are: (1) to develop systematic local model reduction tools for computing multiscale basis functions; (2) to develop and analyze new finite element techniques using these basis functions; (3) to study the interplay between localization of the basis functions and the global coupling mechanism; (4) to apply the developed methods to a wide variety of flows with nonlinearities and multiphysics in 3D; (5) to test and demonstrate their capabilities for solving problems in engineering and geosciences.
Advanced Methods for Mimicking the Osteogenic Niche to Heal Bone
Molecular And Cellular Medicine; TAMHSC; https://hdl.handle.net/20.500.14641/638; DHHS-NIH-National Institute of Arthritis and Musculoskeletal and Skin Diseases
DESCRIPTION (provided by applicant): Of the 13 million yearly fractures that occur in the United States, about 10% fail to repair and in extreme cases this can result in immobility or amputation. While autologous bone grafts are the most effective method to heal complex defects, the available graft material is limited, and the procedure involves additional surgery known to cause chronic donor-site pain in many patients. Human mesenchymal stem cells (hMSCs) have been intensely investigated for their ability to promote bone healing, but results have been variable and disappointing. This is partly due to variability in cell preparations that occurs through donor variation or through inconsistent culture methodologies. Our work has also indicated that hMSCs are not retained at the site of injury for sufficient time to achieve engraftment and promote repair. In an attempt to solve these problems, we recently demonstrated that acceleration of canonical Wnt signaling with the small molecule PPAR¿ inhibitor GW9662 produces osteogenically enhanced hMSCs (OEhMSCs). Further, these OEhMSCs produce extracellular matrix (hMatrix) that dramatically increases OEhMSC retention and bone repair in calvarial and femoral defects. Our central hypothesis for this proposal is that an injectable microsphere vehicle co-administering GW9662, hMatrix and hMSCs will promote osteo- repair through a mechanism that involves extended hMSC retention, trophic factor secretion and paracrine activation of the host stroma. Our hypothesis will be tested via three Specific Aims. Aim 1: Optimize the delivery of OEhMSCs, hMatrix and GW9662 via collagen/poly (lactide-co-glycolide) capsules in vitro. Aim 2: Evaluate bone repair in immune-compromised murine models of calvarial and femoral trauma. Aim 3: Delineate the mechanisms by which the hMatrix components collagen types VI and XII and their cognate integrins increase OEhMSC retention and expression of osteoinductive and angiogenic paracrine factors. These studies will lay the groundwork for translating this novel hMSC-based method for osteo-repair to the clinic. Successful completion of this project could lead to a revolutionary new method for bone repair that could effectively dismiss the need for autologus bone graft in regenerative orthopedics. Our multi-disciplinary team of stem cell biologists, biochemists, bioengineers, orthopedic clinicians and commercialization experts are highly equipped to achieve the goals of the project.
Advanced numerical methods for multiphysics Magnetohydrodynamics
Mathematics; TAMU; https://hdl.handle.net/20.500.14641/339; National Science Foundation
The objective of this project is to develop innovative numerical methods capable of solving energy-related problems in the context of renewable and alternative energies. The numerical techniques developed in this project will help design grid-scale liquid metal batteries capable of storing large quantities of renewable energies. This research will also help improve the performance of large power electric transformers cooled by environment-friendly vegetable-based oils containing ferromagnetic particles. Finally, by facilitating the understanding of magneto-hydrodynamic instabilities in liquid metals, this project will help to ascertain the integrity and the efficiency of the electromagnetic pumps that will be used to extract energy from the next generation of Liquid-Metal Fast-Breeder Reactors and Tokamaks. This project will be done in collaboration with an European team; the project will foster diversity, international exchanges, and multidisciplinarity. The educational component of the project will contribute to increase the competitiveness of the STEM workforce in the US in computational magnetohydrodynamics. The research program will be organized into four areas: (1) Development of new efficient semi-implicit algorithms to solve partial differential equations with variable material properties (density, electric conductivity, magnetic permeability) using spectral or very high-order methods; (2) Modeling of ferromagnetic fluids and development of new numerical techniques to solve the magneto-static equations in the context of liquid metals and ferromagnetic fluids; (3) Development of level set techniques to account for more than two phases, and development of new high-order level set techniques to guarantee mass conservation and maximum principle; (4) Integration of the mathematical models and numerical techniques developed in (1)-(2)-(3) into a massively parallel open source code to test the proposed methods on realistic applications (liquid metal batteries, thermo-convection of ferromagnetic oil in high-voltage transformers, liquid metal dynamos). This project will involve the Principal Investigator, one post-doctoral collaborator, one graduate student, and European collaborators.
Advances in Data Science: Theory, Methods and Computation
Statistics; TAMU; https://hdl.handle.net/20.500.14641/249; National Science Foundation
Due to advancements in data acquisition techniques over the last two decades, new types of exceedingly complex datasets have emerged and present tremendous challenges that require synergy of interdisciplinary ideas for analysis and decision making. As a result, the field of data-science is rapidly evolving as an interdisciplinary field, where advances often result from combinations of ideas from multiple disciplines. A convening of leading experts, early-career researchers, and students from varied disciplines to exchange ideas is essential for progress in this field. Texas A&M University will host a two-day conference on Advances in Data Science in February 2022. More information on the conference can be found at https://stat.tamu.edu/advances-in-data-science-conference/. The primary objective of the conference is to provide a much-needed platform for accelerating the depth and quality of research on the foundations of data science through interdisciplinarity. The conference will bring together researchers from three major disciplinary areas (Statistics, Mathematics and Engineering) for presentation and dissemination of their research, to engage in discussions and foster future collaborations. This conference will involve women, minorities and young researchers across the nation. The conference will present a tremendous opportunity for first generation undergraduate students to be inspired and pursue careers in data-science in both academia and industry. The conference will feature a number of activities to engage the students and recognize their contributions through awards. 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
Advances in Data Science: Theory, Methods and Computation
Statistics; TAMU; https://hdl.handle.net/20.500.14641/249; National Science Foundation
Due to advancements in data acquisition techniques over the last two decades, new types of exceedingly complex datasets have emerged and present tremendous challenges that require synergy of interdisciplinary ideas for analysis and decision making. As a result, the field of data-science is rapidly evolving as an interdisciplinary field, where advances often result from combinations of ideas from multiple disciplines. A convening of leading experts, early-career researchers, and students from varied disciplines to exchange ideas is essential for progress in this field. Texas A&M University will host a two-day conference on Advances in Data Science in February 2022. More information on the conference can be found at https://stat.tamu.edu/advances-in-data-science-conference/. The primary objective of the conference is to provide a much-needed platform for accelerating the depth and quality of research on the foundations of data science through interdisciplinarity. The conference will bring together researchers from three major disciplinary areas (Statistics, Mathematics and Engineering) for presentation and dissemination of their research, to engage in discussions and foster future collaborations. This conference will involve women, minorities and young researchers across the nation. The conference will present a tremendous opportunity for first generation undergraduate students to be inspired and pursue careers in data-science in both academia and industry. The conference will feature a number of activities to engage the students and recognize their contributions through awards. 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
AF: Small: Geometry and Complexity Theory
Mathematics; TAMU; https://hdl.handle.net/20.500.14641/371; National Science Foundation
Linear algebra, which includes computing the solutions to a system of linear equations, is at the heart of all scientific computation. The core computation of linear algebra is matrix multiplication. In 1968 V. Strassen discovered that the widely used and assumed best algorithm for matrix multiplication is not optimal. Since then there has been intense research in both developing better algorithms and determining the limits of how much the current algorithms can be improved. There are three parts to the project. The first two are: practical construction of algorithms for matrix multiplication, and determining the above-mentioned limits. The third addresses a fundamental question of L. Valiant which is an algebraic analog of the famous P versus NP problem. Valiant asked if a polynomial that can be written down efficiently also must admit an efficient algorithm to compute it. All three parts will be approached using theoretical mathematics not traditionally utilized in the study of these questions (representation theory and algebraic geometry). The practical construction of algorithms in this project could potentially have impact across all scientific computation. The novel use of modern mathematical techniques previously not used in theoretical computer science will enrich both fields, opening new questions in mathematics and providing new techniques to computer science. The exponent of matrix multiplication, denoted omega, is the fundamental constant that governs the complexity of basic operations in linear algebra. It is currently known that omega is somewhere between 2 and 2.38. Independent of the exponent, practical matrix multiplication (of matrices of size that actually arise in practice) is only around 2.79. For example, matrices of size 1000x1000 may be effectively multiplied by performing (1000)^{2.79} arithmetic operations. If algorithms to achieve an omega of 2.38 were known, the same matrix operation can be performed using 220 million fewer arithmetic operations. By exploiting representation theory, this project will develop practical algorithms with the goal of lowering this practical exponent. It will also address the exponent by analyzing the feasibility of Strassen's asymptotic rank conjecture and its variants, which are proposed paths towards proving upper bounds on the exponent. The project will also address two aspects of Valiant's conjecture on permanent versus determinant. First, commutative algebra will be used to improve the current lower bound for the conjecture, which has not advanced since 2005. The investigator and a co-author have proven that Valiant's conjecture is true under the restricted model of equivariance. The second aspect will investigate loosening this restriction to weaker hypotheses under which the conjecture is still provable. 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.

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