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1. Mapping industry workforce needs to academic curricula – A workforce development effort in model‐based systems engineering

   https://doi.org/10.1002/sys.21745  

   Akundi, Aditya; Ankobiah, Wilma (February 2024, Systems Engineering)

   Abstract Model‐based systems engineering (MBSE) is rapidly gaining popularity among U.S. industries. Though industry practitioners and academic researchers have identified several advantages in transitioning to MBSE, several adoption challenges of MBSE in industries, such as insufficient tool knowledge, lack of skilled personnel, and resistance in organizations toward a shift to MBSE, are observed. Attesting to the challenges in industry adoption of MBSE, a previous research study by the authors characterized the adoption challenges as tools‐based, knowledge‐based, cultural, political, and cost‐related, and customer understanding and acceptance of MBSE practices. This study is motivated to explore further and address the challenge of low MBSE tool knowledge and lack of skilled personnel with MBSE knowledge for industry adoption. This paper presents a two‐phased research approach framed by an overarching question of the extent to which the MBSE academic curriculum is aligned with industry workforce requirements. In Phase 1 of the study, we survey industry professionals from Defense, Aerospace, Automotive, and other industry clusters to identify MBSE tools, languages, and concepts preferred by industry professionals in a candidate for hire. This is followed by Phase 2 of the survey targeted at academic institutions with Systems and MBSE programs to analyze the extent to which MBSE curricula reflect industry workforce hiring requirements. Further, we also identify the challenges reported in academic institutions in training the Workforce on MBSE. The contributions of this paper are two‐fold: providing a pathway for academic institutions to align their curricula to MBSE industry workforce requirements and triggering discussion in the broader MBSE community to identify strategies for addressing MBSE adoption challenges and training future model‐based systems engineers. 

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2. Perceptions and the extent of Model-Based Systems Engineering (MBSE) use – An industry survey

   https://doi.org/10.1109/SysCon53536.2022.9773894  

   Akundi, Aditya; Ankobiah, Wilma; Mondragon, Oscar; Luna, Sergio (April 2022, 2022 IEEE International Systems Conference (SysCon))

   Model-Based Systems Engineering (MBSE) supports the development of complex systems through capturing, communicating, and managing system specifications with an emphasis on the use of modeling languages, tools, and methods. It is a well-known fact that varying levels of effort are required to implement MBSE in industries based on the complexity of the systems a given industry is associated with. This paper shares the results of a survey to industry professionals from Defense, Aerospace, Automotive, Consultancy, Software, and IT industry clusters. The research goal is to understand the current state of perception on what MBSE is and the use of MBSE among different industry clusters. The survey analysis includes a comparison of how MBSE is defined, advantages on the use of MBSE, project types, specific life cycle stage when MBSE is applied, and adoption challenges, as reported by the survey participants. The researchers also aim to trigger discussions in the MBSE community for identifying strategies to address MBSE related challenges tailored to a specific industry type. 

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3. Industry-Driven Model-Based Systems Engineering (MBSE) Workforce Competencies—An AI-Based Competency Extraction Framework

   https://doi.org/10.3390/systems13090781  

   Akundi, Aditya; Ravipati, Phani_Ram Teja; Luna_Fong, Sergio A; Otieno, Wilkistar (September 2025, Systems)

   Model-based systems engineering (MBSE) is being rapidly adopted in U.S. industries across various sectors. While practitioners and academics recognize many benefits of adopting MBSE, industries also report challenges such as limited tool expertise and a shortage of skilled personnel. Highlighting the difficulties in industry adoption of MBSE, prior research by the authors identified challenges such as tool limitations, knowledge gaps, cultural and political barriers, costs, and the level of customer understanding and acceptance of MBSE practices. Additionally, another study by the authors points out a gap between industry demands for MBSE skills in new hires and the current academic training programs. To further assess the MBSE industry’s workforce needs, this paper introduces a two-phase method for the Structured Extraction of MBSE competencies using large language models based on current workforce demands from LinkedIn job postings. Phase 1 involved extracting 1960 job descriptions from LinkedIn using the term “model-based systems engineer.” In phase 2, large language models (LLMs) employing deep transformer architectures were used to transform unstructured text into structured data. An AI agent was used as an autonomous software layer to manage every interaction between the raw dataset from Phase 1 and the LLM. Supported by the analyzed data, a competency framework is proposed that summarizes the tools, technical skills, and soft skills expected of a model-based systems engineer by the industry. The framework is designed to include core competencies shared across all MBSE roles, with specific competencies tailored for aerospace & defense, manufacturing and automotive, and software and IT sectors. 

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4. Faculty Perspectives on Their Role in the Training of STEM Doctoral Students

   https://doi.org/10.18260/1-2--47458  

   Pan, Zilong; Jagota, Anand; Dierolf, Volkmar; Jain, Himanshu (June 2024, ASEE Conferences)

   Traditional PhD training in STEM fields places a strong emphasis on developing doctoral students' academic skills, encompassing research, academic writing, as well as sharing of knowledge through publications and conference presentations, etc. However, with the ever evolving expectations of graduate training, particularly in applied fields, the demand for PhD has transcended the confines of academia. For instance, nearly 90% of engineering PhDs will not enter academia, which underscores the discrepancy between the current PhD training programs and the preparation of students for future careers. To better support doctoral students especially for those who intend to pursue positions in industry including corporate R&D labs, national labs, defense organizations, healthcare institutes, etc., Lehigh University launched an innovative program called Pasteur Partners PhD (P3) specifically for the training of such doctoral students. It is a student-centered doctoral training program based on use-inspired research in partnership with industry. A preliminary evaluation of the P3 program, which was developed with support from NSF’s IGE program, revealed that students benefited significantly from gaining practical skills through industry involvement such as co-advising, resulting in a clearer understanding of how the industry operates, which, in turn, enhanced their employability in the industry [1]. The University administration also provided significant support for the program. However, a broader implementation of P3 encountered challenges and hesitancy from faculty members. Mostly the senior faculty who already had preexisting connections with industry and junior faculty from certain departments were more receptive to joining the P3 program than others. Could this be a result of the prevailing emphasis of the graduate education system on research output (publications) rather than the training of students for their subsequent careers? What other reasons could there be for the faculty’s lack of enthusiasm for the training of their PhD students following P3 track? To answer above questions and examine the challenges and obstacles that the faculty members feel for student centered doctoral training from an institutional and system perspective, we are conducting a survey specifically targeting faculty members in STEM fields. It seeks to comprehensively understand faculty members’ perspective on the primary objectives of doctoral training within different STEM fields. By exploring these objectives, the survey aims to uncover how they vary across disciplines and what faculty members perceive as the most significant goals in their areas of expertise. Moreover, the survey is designed to shed light on the challenges and hurdles faced by faculty members in their pursuit of these training objectives. Faculty participants are encouraged to identify and articulate the specific obstacles they encounter, whether they pertain to institutional constraints, resource limitations, demands of perceived professional success or other factors that impede the realization of these goals. In addition, the survey takes a close look at the resources that faculty members believe would be beneficial in addressing these challenges and improving the effectiveness of doctoral training. This insight is essential for designing support systems that can empower faculty to contribute to the training of doctoral workforce for the benefit of society at large. The survey seeks to gain valuable perspectives on the qualities and skills considered essential for the success of PhD students. These insights will inform curriculum development and help prepare students better for a wider range of career paths. The results of the survey, currently underway, are presented. 

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5. Early lessons learned from pivoting an REU program to a virtual format

   Guessous, L. (June 2022, 2022 ASEE Annual Conference & Exposition)

   Since the summer of 2006, the NSF-funded AERIM Research Experience for Undergraduates (REU) program in the department of Mechanical Engineering at Oakland University has been offering rich research, professional development, networking and cohort-building experiences to undergraduate students in the science, technology, engineering and math (STEM) fields. With a focus on hands-on automotive and energy research projects and a proximity to many automotive companies, the program has been successful at attracting a diverse group of students. In fact, a total of 104 students from 70 different universities have participated in the program over the past 15 years, with about 70% of the participants coming from groups that have traditionally been underrepresented in engineering (women in particular). Most research projects have been team-based and have typically involved experimental and analytical work with perhaps a handful of numerical simulation-based projects over the years. Prior assessment has shown that students greatly valued and benefited from interacting with faculty mentors, industry professionals, industry tours, and each other. As a result of limitations placed on in-person meeting and on-campus activities impacted by the Covid-19 pandemic, the program had to pivot to a virtual format in the summer of 2021. This virtual format brought about several challenges and opportunities, which will be discussed in this paper. Despite the virtual format, the program was successful at attracting a diverse group of students in 2021. Twelve undergraduate students from eight different institutions took part remotely in the program and encompassed several time zones ranging from Eastern Standard Time to Alaska Standard Time. The 2021 cohort included seven women, three underrepresented minorities, and two students with a reported disability. Also noteworthy is the fact that half of the students were first generation in college students. While the PIs were happy with the student make up, running the program in a virtual format was very challenging. For one, what was traditionally a hands-on, experimental research program had to pivot to completely simulation/analytical based projects. This brought about issues related to remote access to software, time lags and difficulties with engaging students while computer simulations were running remotely. While the program was able to offer several seminars and meetings with industry professionals in a virtual fashion, it was not possible to provide industry tours or the casual conversations that would spontaneously occur when meeting face to face with industry professionals. Finally, with students logging in from their homes across the country and across different time zones rather than living together in the Oakland University dorms, the usual bonding and group interactions that would normally occur over the summer were difficult to replicate. In this paper we discuss what was learned from these challenges and how the virtual format also offered opportunities that will be utilized in future years. 

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