Engineering Academy Research Articles

Potential Applications and Ethical Considerations for Artificial Intelligence in Traumatic Brain Injury Management

Artificial intelligence (AI) systems have emerged as promising tools for rapidly identifying patterns in large amounts of healthcare data to help guide clinical decision making, as well as to assist with medical education and the planning of research studies. Accumulating evidence suggests AI techniques may be particularly useful for aiding the diagnosis and clinical management of traumatic brain injury (TBI)—a considerably heterogeneous neurologic condition that can be challenging to detect and treat. However, important methodological and ethical concerns with the use of AI in medicine necessitate close monitoring and regulation of these techniques as advancements continue. The purpose of this narrative review is to provide an overview of common AI techniques in medical research and describe recent studies on the possible clinical applications of AI in the context of TBI. Finally, the review describes the ethical challenges with the use of AI in medicine, as well as guidelines from the White House, the Department of Defense (DOD), the National Academies of Sciences, Engineering, and Medicine (NASEM), and other organizations on the appropriate uses of AI in research.

Artificial intelligence in food and nutrition evidence: The challenges and opportunities based on a convening of content experts

Abstract Science-informed decisions are best guided by the objective synthesis of the totality of evidence around a particular question and assessing its trustworthiness through systematic processes. However, there are major barriers and challenges that limit science-informed food and nutrition policy, practice, and guidance. First, insufficient evidence, primarily due to acquisition cost of generating high-quality data, and the complexity of the diet-disease relationship. Furthermore, the sheer number of systematic reviews needed across the entire agriculture and food value chain, and the cost and time required to conduct them, can delay the translation of science to policy. Artificial intelligence (AI) offers the opportunity: 1) to better understand the complex etiology of diet-related chronic diseases; 2) to bring more precision to our understanding of the variation among individuals in the diet-chronic disease relationship; 3) to provide new types of computed data related to the efficacy and effectiveness of nutrition/food interventions in health promotion; and 4) to automate the generation of systematic reviews that support timely decisions. These advances include the acquisition and synthesis of heterogeneous and multimodal datasets. This perspective summarizes findings from a meeting of experts convened at the National Academy of Sciences, Engineering and Medicine. The purpose of the meeting was to examine the current state and future potential of AI in generating new types of computed data as well as automating the generation of systematic reviews to support evidence-based food and nutrition policy, practice and guidance.

Priorities and Recommendations to Make ALS a Livable Disease Emanating from the 2024 National Academies of Sciences, Engineering, and Medicine Report Living with ALS.

Amyotrophic lateral sclerosis (ALS) is a relentless, fatal neurodegenerative disease. The progressive loss of voluntary muscle function, diagnostic delays, lack of effective treatments, and challenges accessing multidisciplinary care and resources have tremendous impact on quality of life. The congressionally directed ALS committee of the National Academies of Science, Engineering, and Medicine, in their 2024 report "Living with ALS,"recommends critical actions for specific United States stakeholders to make ALS a livable disease over the next decade. This review summarizes the context and recommendations of the report. Advocacy efforts are critical to make these recommendations a reality for the ALS community. ANN NEUROL 2024.

Serum per- and polyfluoroalkyl substance (PFAS) levels and health-related biomarkers in a pilot study of skiers in New England

BackgroundPer- and polyfluoroalkyl substances (PFAS), synthetic chemicals with adverse health effects, are used extensively in consumer products. Ski waxes, applied to the base of skis, contain up to 100% PFAS by mass, but exposure and health effects are poorly characterized. ObjectivesOur objectives were to quantify serum PFAS concentrations among skiers and explore associations with reported ski wax use and biomarkers of cardiometabolic, thyroid, and immune health. MethodsWe recruited 30 active adult skiers to provide non-fasting blood samples and complete questionnaires. We quantified 18 PFAS using mass spectrometry, and measured serum lipids, thyroid hormones, and immunoglobulins. We explored associations of individual and aggregate measures of serum PFAS with wax use indicators and health biomarkers using multivariable regression models, adjusted for age and gender identity. ResultsNine PFAS (PFBS, PFHpS, PFHxS, Sm-PFOS, n-PFOS, PFDA, PFNA, PFUnDA, n-PFOA) were detected in 100% of participants, and MeFOSAA in 93%. Compared to NHANES, median serum concentrations (ng/ml) were similar, but higher in coaches (e.g., PFOAall: 1.1, PFOAcoaches: 2.7, PFOANHANES: 1.2; PFNAall: 0.5, PFNAcoaches: 1.7, PFNANHANES: 0.4). Factors reflecting wax exposure were positively associated with PFAS: e.g., >10 years as a snow sport athlete, compared to ≤10 years, was associated with 3.2 (95% CI: 0.7, 5.6) ng/ml higher aggregate PFAS, as defined by National Academies of Science, Engineering, and Medicine (NASEM). An IQR (6.3 ng/ml) increase in NASEM PFAS was associated with 32.1 (95% CI: 7.0, 57.2), 35.5 (13.5, 57.5), and 12.8 (0.6, 25.1) mg/dl higher total cholesterol, LDL-C, and sdLDL-C, respectively. DiscussionOur study provides early evidence that recreational skiers, particularly coaches, are exposed to PFAS through ski wax. Several PFAS were associated with higher serum lipids among these physically active adults. Interventions to remove PFAS from fluorinated wax could decrease direct exposure to skiers and reduce PFAS release into the environment.

Overcoming the Impact of Students for Fair Admission v Harvard to Build a More Representative Health Care Workforce: Perspectives from Ending Unequal Treatment.

Policy Points In a recently commissioned report on solutions for eliminating racial and ethnic health care inequities entitled Ending Unequal Treatment, the National Academies of Sciences, Engineering, and Medicine found a health workforce that is representative of the communities it serves is essential for health care equity. The Supreme Court decision to ban race-conscious admission constraints pathways toward health workforce representativeness and equity. This paper draws on the National Academies report's findings that health care workforce representativeness improves care quality, population health, and equity to discuss policy and programmatic options for various participants to promote health workforce representativeness in the context of race-conscious admissions bans.

Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis: One Decade Later.

In 2012, the National Academies of Sciences, Engineering, and Medicine convened a committee charged with addressing the quality of cancer care in the United States and providing recommendations to policymakers and the cancer care community on strategies to improve cancer care delivery from the time of diagnosis through end-of-life. The resulting committee report, titled Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis (2013), presented a conceptual framework that included six interconnected components of care with corresponding recommendations. Over the past decade, the delivery of high-quality of cancer care has become more challenging and increasingly demanding on the workforce. In this manuscript, we review the goals and recommendations made in 2013, describe progress to date, and offer insights into future dedicated efforts and/or new strategies needed to achieve high-quality cancer care.

Orofacial Pain.

This article explores the multiple etiologies, diagnosis, and management of orofacial pain. Published in 2019, the International Classification of Orofacial Pain has become the internationally accepted classification system for primary and secondary facial pain. New discoveries in temporomandibular disorders have demonstrated that they are far more complex than the traditional dental mechanistic point of view. A 2020 consensus report released by the National Academies of Sciences, Engineering, and Medicine entitled "Temporomandibular Disorders: Priorities for Research and Care" highlighted this paradigm shift and its importance for patient care, education, and research. Orofacial pain comprises many disorders with different etiologies and pathophysiologies. The subjectivity of the pain experience and the interrelated anatomy and physiology of the craniofacial area add to the complexity of diagnosis when the source and etiology of pain are not clear. As orofacial pain straddles the expertise of multiple disciplines, a multidisciplinary approach combining medication, physical therapy, and procedural and psychological strategies is essential in treating patients with orofacial pain.

Urban Traffic Identification by Comparing Machine Learning Algorithms

The Internet of Things (IoT) applied to intelligent transport systems has become a key element for understanding the way traffic flow behaves in cities, which helps in decision-making to improve the management of the transport system by monitoring and analyzing network traffic in real time, all with the aim of daily benefiting users of the city’s road infrastructure. Traffic volume estimation in real time, with high effectiveness, may help mobility management and improve traffic flow. Moreover, machine-learning algorithms have shown effectiveness in various scientific fields and have provided a significant platform for achieving intelligent applications. Therefore, we applied various machine learning algorithms to classify the vehicular traffic status in the traffic network of two cities with more than 2 million inhabitants. It was first necessary to establish, from the attributes provided by the datasets, the object class from the LOS (Level of Services) thresholds proposed by the National Academies of Sciences, Engineering, and Medicine, for the basic segments of highways in an urban area. We then selected the attributes of interest using the Recursive Feature Elimination Method (RFE) to reduce the dimensionality of the data, and applied the DT, RF, ET, KNN, and MLP algorithms to train and classify the level of vehicular congestion, defining various volumes of training and validation data. The results show the high effectiveness of the algorithms, highlighting the MLP algorithm as the one that provides the highest effectiveness on average for the evaluated datasets, with a mean precision of 99.5%.

CEST conversation with Prof. Marc A. Rosen: Evolving responsibilities and contributions in science and engineering for global carbon neutrality transitions

Prof. Marc A. Rosen is a Professor of Mechanical & Manufacturing Engineering at Ontario Tech University (formally University of Ontario Institute of Technology) in Oshawa, Canada, where he served as founding Dean of the Faculty of Engineering and Applied Science. Prof. Rosen has served as President of the Engineering Institute of Canada and of the Canadian Society for Mechanical Engineering. He has received numerous awards and honors, including an Award of Excellence in Research and Technology Development from the Ontario Ministry of Environment and Energy, the Engineering Institute of Canada Smith Medal for achievement in the development of Canada, and the Canadian Society for Mechanical Engineering Angus Medal for outstanding contributions to the management and practice of mechanical engineering. Prof. Rosen received a distinguished scholar award from Toronto Metropolitan University (formerly Ryerson University) and a Mid-Career Award from University of Toronto. He is a fellow of the Royal Society of Canada, the Engineering Institute of Canada, the Canadian Academy of Engineering, the Canadian Society for Mechanical Engineering, the American Society of Mechanical Engineers and the International Energy Foundation.

The development of polymers and fibers: an interview with Stephen Cheng.

Polymer and fiber science has evolved significantly since the 1920s, with polymers becoming integral to both industry and daily life. China's fiber research, initiated in the 1950s, has made substantial societal and technological contributions, particularly in chemical fibers. How will future advancements in polymers and fibers address ongoing challenges and drive further innovation? NSR spoke to Prof. Stephen Cheng, a member of the National Academy of Engineering (U.S.) and former Dean of the College of Polymer Science and Polymer Engineering at the University of Akron. He is currently Dean and Honorable Professor at South China University of Technology. His research interests center on the condensed states in polymers, liquid crystals, surfactants and hybrid materials, focusing on the interactions, responses, dynamics and structures of materials at varying lengths, energy and timescales, in which the material itself embodies the technology.

PSLBI-4 Influence of gender on animal science research funding from the National Institute of Food and Agriculture

Abstract According to the National Academies of Sciences, Engineering, and Medicine, females and males in science disciplines obtain bachelor’s degrees at or near parity, yet females are not equally represented in academic faculty positions. This is true for agricultural fields including the animal sciences. The USDA’s National Institute of Food and Agriculture (NIFA) administers the Agriculture and Food Research Initiative (AFRI), a flagship competitive grants program that funds research, education, and extension efforts with a total appropriation of $445 million in 2024. Our objective was to determine the difference between genders for submission rates (i.e., number of standard and seed grant applications submitted), peer reviewers of grant applications, and success rates (i.e., number of grant awards/number of applications submitted) in the main animal related AFRI program area priorities. All applications submitted to AFRI programs in animal genomics, reproduction, health, nutrition and growth, and welfare during yr 2013-2022 were evaluated. Gender was assigned to Project Directors (PD) and peer reviewers using first names as input into Gender API software (Gender-API.com; Passau, Germany) with ≥ 95% accuracy and ≥ 20 database occurrences used as quality filters and binary outcomes only (i.e., male or female). Effect of gender on submission rates, peer review panel compositions, and success rates were then analyzed using Pearson’s Chi-squared tests with P ≤ 0.05 considered significant. Results: A total of 3,757 applications were submitted, of which 2,761 (73%) PD genders were assigned and analyzed further. Overall, the proportional submission rate for females was 28% and for males was 72%. Submission rates for females increased (P = 0.0614) over time ranging from 22% in 2013 to 33% in 2021. Submission rates differed by gender across programs (P < 0.0001) and ranged from 23% female in animal reproduction to 48% female in animal welfare. Across 48 panels, 41% of panelists were female; no differences were identified for the proportion of female panelists over time (P = 0.9509) or by program (P = 0.9298). Overall, the funding success rate for females was 23% and for males was 22%. Success rates did not differ between genders over time (P = 0.9080) or by program (P = 0.9094). Females submitted less than one-half as many applications as did males, but the proportion of submissions by females increased over time. This trend remained consistent despite challenges of relocation of NIFA and COVID-19 during this time. Overall, the proportion of NIFA panelists who were female exceeded the proportion of applications submitted by females. Funding success rates did not differ by gender and increased for both genders over time. These results indicate that although differences in gender existed for application submission rate and panel composition, these differences did not impact funding success rate of applications in animal science programs at NIFA, which did not differ between genders.

Development, validation, and clinical assessment of a liquid chromatography-tandem mass spectrometry serum assay for per- and polyfluoroalkyl substances (PFAS) recommended by the National Academies of Science, Engineering, and Medicine (NASEM).

Per- and polyfluoroalkyl substances (PFAS) are widely used in industry, residential, and consumer products. Studies have shown associations between high PFAS exposure and adverse health effects. In 2022, the National Academies of Science, Engineering, and Medicine (NASEM) published Guidance on PFAS Exposure, Testing, and Clinical Follow-up providing laboratory and clinical direction. The Guidance suggests nine PFAS should be measured in serum or plasma specimens and summed to provide a total PFAS concentration using a NASEM-recommended method. Follow-up clinical recommendations are based on the calculated PFAS NASEM summation. We developed and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method in accordance with NASEM recommendations but distinguished by the ability to separate closely related structural isomers. As part of our validation, PFAS prevalence was evaluated in a population survey comprised of clinical donor and remnant specimens (n = 1023 in total). In this study, 82.2% of the specimens had PFAS NASEM summations of 2 to < 20ng/mL and 2.5% had a summation ≥ 20ng/mL. The median PFAS NASEM summation was 4.65ng/mL in this study, lower than the 7.74ng/mL median observed in the 2017-2020 Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey (n = 3072). This lower median PFAS NASEM summation may reflect a decline in PFAS population levels over time or sample population exposure differences.

63 Impacts of protein supplementation frequency on animal performance, rumen fermentation and methane emission from growing beef cattle

Abstract Nutrient supplementation is one of largest expenditure in forage-based beef production systems, especially when forage quality is poor or limited. Decreasing supplementation frequency may have a role in improving sustainability by increasing animal performance and minimizing cost of labor and fuel. This study evaluated the impacts of protein supplementation frequency (canola meal pellet; CMP) on animal performance, rumen fermentation, and enteric methane production from beef cattle fed forage-based diet. A total of 60 crossbred backgrounding steers [body weight (BW) = 278 ± 10 kg) was randomly assigned to one of the three treatments (n = 20/treatment): i) control (no CMP supplementation), ii) control + everyday CMP supplementation (0.83 kg/d per steer), and iii) control + every other day supplementation of CMP. The study was comprised of 21 d of adaptation followed by three 21-d periods, with enteric methane measured for 7 d per period. Animals were fed grass hay-based diets once a day at 0800 h and remained on their respective diets throughout the 63-d study. Diets were formulated considering animal BW, feed nutrient density and environmental condition in accordance with the National Academies of Sciences, Engineering and Medicine. Each treatment group was assigned to a pen, with the cattle and diets rotated among pens weekly to allow the animals to access the GreenFeed system stationed in one of the pens for enteric methane measurement. For measurement of rumen fermentation products, three ruminally canulated steers (BW = 350 ± 20 kg) were allocated to the three treatments using a 3 x 3 Latin Square Design with 21-d periods so that one animal received all the treatments over the three experimental periods. Animals were adapted to the treatments for 17 d and rumen samples were collected between d 19 and 21 at 0700 h, 1000h, 1300 h, 1600 h and 1900 h. Data were analyzed using the Mixed procedure of SAS. Relative to the control treatment (9.9 kg/d), DM intake was 4 to 5% greater (P &amp;lt; 0.001) following CMP supplementation regardless of supplementation frequency. Similarly, average daily gain was greater (7 to 11%, P = 0.01) for CPM supplemented treatments as compared with control (1.04 kg/d) irrespective of supplantation frequency. Rumen fermentation was affected by treatments. Total VFA concentration was greater (P = 0.01) for the every other day supplementation of CMP as compared with control and daily supplementation treatments. Conversely, rumen ammonia concentration was not affected by treatments. The control group had greater acetate and reduced propionate molar proportions that resulted in a 5 to 6% greater acetate:propionate ratio (P &amp;lt; 0.01) as compared with the CMP supplemented groups. Enteric methane production (g/d) was greater for the daily CMP supplementation (P = 0.02) while yield (g/kg daily weight gain) was not affected by treatment. Our results indicated that reduction of protein supplementation frequency improved animal performance without negatively impacting rumen fermentation.

350 Awardee Talk: Beef cattle mineral nutrition: What do we know and where do we go from here

Abstract Trace minerals are pivotal in enhancing cattle growth and ensuring profitability in beef production. Historically, supplementation strategies have aimed at preventing deficiencies, significantly improving growth and reproductive performance. However, as cattle breeding has evolved to achieve remarkable growth rates, the challenges related to health and stress during the feeding period have intensified. This presentation explores refined trace mineral recommendations, focusing on zinc’s “stress requirement” for cattle undergoing transit and health challenges, and its impact on performance. The segmented nature of the beef industry, necessitating multiple transports, induces physiological stress and oxidative stress, highlighting the need for tailored mineral supplementation. Further, when recognizing feedlot cattle as the high-performing athletes they are, the potential benefits of adjusted trace mineral concentrations become apparent. Preliminary findings suggest that optimal zinc concentrations may exceed current National Academies of Sciences, Engineering, and Medicine (NASEM) 2016 recommendations, whereas for other minerals like copper and manganese, the existing guidelines remain appropriate. This presentation will explore the differential effects of increasing dietary zinc and copper in conjunction with various growth-promoting technologies. Preliminary data indicates that increasing zinc concentrations can linearly enhance average daily gain (ADG) and hot carcass weight (HCW), especially when using potent anabolic implants, while the response to increased copper concentrations exhibits a more quadratic relationship with performance. Building upon the foundational work of pioneering researchers in the field of mineral nutrition, this presentation advocates for the continuous refinement and optimization of trace mineral supplementation strategies. By integrating cutting-edge technologies and fostering collaborative research efforts, we aim to further enhance the sustainability of the beef industry. A deeper understanding of trace mineral requirements in the face of modern production challenges will pave the way for more precise and effective nutritional strategies.

Creating an Integrated System of Data and Statistics on Household Income, Consumption, and Wealth

The nation's disparate federal statistics makes it difficult to accurately measure income and wealth inequality and other aspects of economic well-being for the nation's households and families. This report provides the recommendations from a panel appointed by The Committee on National Statistics (CNSTAT) of the National Academies of Sciences, Engineering, and Medicine. The report reviews the major income, consumption, and wealth statistics currently produced by U.S. statistical agencies, provides guidance for modernizing and integrating the information to better inform policy and research, and builds on the current effort at CNSTAT to create a 21st Century Data Infrastructure to use blended data from multiple sources. In addition to providing guidance on the appropriate definitions of household, family, and individual income, consumption, and wealth, and variations in definitions that would be useful for particular purposes, the report provides suggestions for pathways forward using multiple data sources to construct a data infrastructure for income, consumption and wealth for households. The report highlights new statistics that help in measuring the disparities in income, consumption and wealth and the changes over time in both levels and inequalities, always stressing that the disparities occur both across socio-demographic characteristics and geography. The report highlights the potential for blending multiple data sources and modeling across data sources, including surveys, tax records, state and federal administrative records, and commercial data, and documents the legal and administrative barriers to creating integrated, high-quality estimates and a data infrastructure for researchers to evaluate the impacts of public policy.

Ending Unequal Treatment and Achieving Optimal Health for All

This Viewpoint discusses the findings of a recent National Academies of Sciences, Engineering, and Medicine report suggesting that current health care delivery and accountability structures perpetuate, rather than reduce, health inequities and details several changes needed to address these structural problems.

Интервью с юбиляром: доктору технических наук, профессору Киричеку Андрею Викторовичу – 60

In august 2024, the Vice-Rector of the Federal State Budgetary Educational Institution of Higher Education Bryansk State Technical University, Doctor of Technical Sciences, Professor, Full Member of Tsiolkovsky Russian Academy of Cosmonautics, Corresponding Member of the Russian Engineering Academy and the Academy of Engineering Sciences of the Russian Federation Andrey Viktorovich Kirichek turns 60.

The global macroeconomic burden of Alzheimer's disease and other dementias: estimates and projections for 152 countries or territories

Alzheimer's disease and other dementias (ADODs) severely threaten the wellbeing of older people, their families, and communities, especially with projected exponential growth. Understanding the macroeconomic implications of ADODs for policy making is essential but under-researched. We used a health-augmented macroeconomic model to calculate the macroeconomic burden of ADODs for 152 countries or territories, accounting for: the effect on labour supply of reduced working hours of informal caregivers; the effect on labour supply of ADODs-related mortality and morbidity; age-sex-specific differences in education, work experience, labour market participations, and informal caregivers; and treatment and formal care costs diverting from savings and investments. ADODs will cost the world economy 14 513 billion international dollars (INT$, measured in the base year 2020; 95% uncertainty interval [UI] 12 106-17 778) from 2020 to 2050, equivalent to 0·421% (95% UI 0·351-0·515) of annual global GDP. Japan incurs the largest annual GDP loss at 1·463% (1·225-1·790). China (INT$2961 billion [2507-3564]), the USA (INT$2331 billion [1989-2829]), and Japan (INT$1758 billion [1471-2150]) face the largest absolute economic burdens. The economic burden of informal care ranges from 60·97% in high-income countries to 85·45% in lower-middle-income countries, and treatment and formal care costs range from 10·50% in lower-middle-income countries to 30·80% in high-income countries. The macroeconomic burden of ADODs is substantial and unequally distributed across countries and regions. Global efforts to reduce the burden, especially with regard to informal care, are urgently needed. National Institute on Aging, National Institutes of Health; Chinese Academy of Engineering; Chinese Academy of Medical Sciences; Bill & Melinda Gates Foundation; Davos Alzheimer's Collaborative through Data for Decisions.

MANTA: a negative-triangularity NASEM-compliant fusion pilot plant

Abstract The MANTA (Modular Adjustable Negative Triangularity ARC-class) design study investigated how negative-triangularity (NT) may be leveraged in a compact, fusion pilot plant (FPP) to take a ‘power-handling first’ approach. The result is a pulsed, radiative, ELM-free tokamak that satisfies and exceeds the FPP requirements described in the 2021 National Academies of Sciences, Engineering, and Medicine (NASEM) report ‘Bringing Fusion to the U.S. Grid’ (2021 Bringing Fusion to the U.S. Grid). A self-consistent integrated modeling workflow predicts a fusion power of 450 MW and a plasma gain of 11.5 with only 23.5 MW of power to the scrape-off layer (SOL). This low P SOL together with impurity seeding and high density at the separatrix results in a peak heat flux of just 2.8 MW m−2. MANTA’s high aspect ratio provides space for a large central solenoid (CS), resulting in ∼15 minute inductive pulses. In spite of the high B fields on the CS and the other REBCO-based magnets, the electromagnetic stresses remain below structural and critical current density limits. Iterative optimization of neutron shielding and tritium breeding blanket yield tritium self-sufficiency with a breeding ratio of 1.15, a blanket power multiplication factor of 1.11, toroidal field coil lifetimes of 3100 ± 400 MW · yr, and poloidal field coil lifetimes of at least 890 ± 40 MW · yr. Following balance of plant modeling, MANTA is projected to generate 90 MW of net electricity at an electricity gain factor of ∼ 2.4 . Systems-level economic analysis estimates an overnight cost of US$3.4 billion, meeting the NASEM FPP requirement that this first-of-a-kind be less than US$5 billion. The toroidal field coil cost and replacement time are the most critical upfront and lifetime cost drivers, respectively.

How interdisciplinary is it? A new method for quantifying interdisciplinarity in student teams & examination of a large project-based program

ABSTRACT The European Higher Education Area and the US National Academies of Science, Engineering, and Medicine have called on higher education to support interdisciplinary learning. The National Academies recommend evaluating interdisciplinary education against relevant criteria, but beyond listing student majors, institutions cannot easily quantify interdisciplinarity in education. The Rao-Stirling diversity index, which incorporates measures of cognitive distance, is used to quantify the interdisciplinarity of research. This study extends the use of the Rao-Stirling diversity index to the context of higher education to: (1) determine whether it provides a more nuanced measure of interdisciplinarity than number of majors, and (2) to examine patterns in interdisciplinarity across 79 student teams in Georgia Tech’s Vertically Integrated Projects Program (N = 1218). The analysis employed cognitive distances developed in a previous study. Distributions of diversity indexes and enrollment by major were examined across the program, along with visualizations for 4 teams. Results show the Rao-Stirling diversity index provided a more comprehensive measure of team interdisciplinarity, and it indicated higher interdisciplinarity in more teams and in comparatively smaller teams than the number of majors would imply. Indexes across the program were examined graphically and explored through regression. Results indicated that higher interdisciplinarity was associated with smaller team size, implying a possible need for additional support for these teams. The utility of the index in quantifying the interdisciplinarity of teams and in revealing a previously unknown pattern confirm its usefulness within the context of higher education. Limitations, implications for research and practice, and future directions are discussed.