program Description

ADJOINT is a yearlong program that provides opportunities for U.S. mathematicians – especially those from the African Diaspora – to conduct collaborative research on topics at the forefront of mathematical and statistical research.

Beginning with an intensive two-week summer session at SLMath, participants work in small groups under the guidance of some of the nation’s foremost mathematicians and statisticians to expand their research portfolios into new areas. The two-week summer session will take place June 30 to July 11, 2025 in Berkeley, California. Throughout the following academic year, the program will provide conference and travel support to increase opportunities for collaboration, maximize researcher visibility, and engender a sense of community among participants.  

ADJOINT enriches the mathematical and statistical sciences as a whole by providing a platform for researchers, especially members of the African-American mathematical and statistical communities, to advance their research and careers and deepen their engagement with the broader research community. 

During the workshop, each participant will: 

• conduct research at SLMath within a group of four to five mathematical and statistical scientists under the direction of one of the research leaders 
• participate in professional enhancement activities provided by the onsite ADJOINT Director 
• receive funding for two weeks of lodging, meals and incidentals, and one round-trip travel to Berkeley, CA 

After the two-week workshop, each participant will:

• have the opportunity to further their research project with the team members including the research leader 
• have access to funding (up to $2000 per person) to attend conference(s) or to meet with other team members to pursue the research project, or to present results 
• become part of a network of research and career mentors

Eligibility

Applicants must be a U.S. citizen or permanent resident, possess a Ph.D. in the mathematical or statistical sciences, and be employed at a U.S. institution.

All members must be in residence and actively engaged in the program 8:30 am - 5 pm daily (without teaching, mentoring, or other professional responsibilities) for its duration:  June 30 to July 11, 2025.

Selection Process

The guiding principle in selecting participants and establishing the groups is the creation of diverse teams whose members come from a variety of institutional types and career stages. The degree of potential positive impact on the careers of African-Americans in the mathematical and statistical sciences will be an important factor in the final decisions.

Application Process

Applicants must provide:

• a cover letter specifying which of the offered research projects you wish to be part of; if more than one, please indicate your priorities
• a CV
• a personal statement, no longer than one page, addressing how your participation will contribute to the goals of the program (e.g., why you are a good candidate for this workshop and what you hope to gain)
• a research statement, no longer than two pages, describing your current research interests, and relevant past research activities, and how they relate to the project(s) of greatest interest to you (e.g., what motivates your current interests and what is your relevant research background) 

Due to funding restrictions, only U.S. citizens and permanent residents are eligible to apply.

2025 Research Leaders and Topics

Loni Philip Tabb (Drexel University)
County-level Cardiovascular Health Metrics and Their Relationship with Social Determinants of Health – What’s the Importance of Residential Segregation?

• To promote a paradigm shift from a focus solely on the absence or presence of cardiovascular disease (CVD), the American Heart Association (AHA), in 2010, defined a novel construct of cardiovascular health (CVH). This broader and more positive construct was termed Life’s Simple 7 (LS7) and was based on seven health behaviors and factors. Specifically, the LS7 framework included indicators of dietary quality, participation in physical activity, exposure to cigarette smoking, and measures of body mass index, fasting blood glucose, total cholesterol, and blood pressure levels – where each metric was characterized as poor, intermediate, or ideal. While significant evidence exists that documents the prevalence, determinants, outcomes and mechanisms of CVH utilizing the LS7 framework, in 2022, the presidential advisory of the AHA introduced an enhanced approach at assessing CVH, where new metrics were considered, and the age spectrum was expanded to also include the entire life course. As such, Life’s Essential 8 (LE8) was developed, where the components included: diet (updated), physical activity, nicotine exposure (updated), body mass index, blood lipids (updated), blood glucose (updated), blood pressure, and sleep health (new). While geographic variations in CVH have been identified, based on the original LS7 CVH framework, to our knowledge, a county-level CVH score, based on the AHA’s LE8 conceptual framework, has not yet been developed. In particular, population level estimates that capture the 8 components of CVH have not been utilized to create a standardized score to characterize the county-level CVH environment. Such a county-level metric could aid in describing the CVH environment more broadly, with an eye towards creating more informed and evidence-based policies and even interventions targeted at improving CVH overall.

  Utilizing data from two well-known publicly available datasets found in the Centers for Disease Control and Prevention PLACES and the County Health Rankings and Roadmap, we aim to address the following goals: (1) create a county-level CVH score based on the AHA’s LE8 framework and the previous AHA’s LS7 framework; (2) quantify and contrast the geographic heterogeneity in the county-level CVH scores to better understand the patterning of CVH across US counties; and (3) determine the geographic patterning in the association of county-level CVH with residential segregation (a known predictor of CVH). Findings from this research will help organizations like the American Heart Association, as well as public health researchers and practitioners, medical professionals, health systems, and policy makers to further understand the county-level CVH environment – with an eye towards improving CVH at the individual- and population-levels.

• Pre-requisites: Computing abilities with R/Python (importing and merging data from several publicly available data sources), data wrangling and cleaning, regression modeling, spatially varying regression modeling (basic/introductory understanding)

Shanise Walker (Clark Atlanta University)
Directed Antimagic Graphs

• In graph theory, graph labeling is a technique used to assigned labels to the vertices, edges, or both of a graph according to specific criteria. Rosa introduced the concept of graph labeling in 1967 to investigate the cyclic decompositions of the complete graph into isomorphic subgraphs. Various problems and applications (scheduling, communication networks, coding theory, etc.) have been studied using graph labeling. One such study is on antimagic graphs introduced by Hartsfield and Ringel in 1990 where the authors proved various graph families were antimagic. There has been extensive research on determining whether graphs are antimagic.
  
  In this research project, we will focus on directed antimagic graphs. The notion of antimagic graphs was extended to directed graphs by Hefetz, Mütze, and Schwartz in 2010. An antimagic labeling of a directed graph is a bijection on the set of arcs in the graph with integers such that all oriented vertex sums are distinct. An oriented vertex sum is the sum of labels of all arcs entering that vertex minus the sum of labels of all arcs leaving it. Hefetz, Mütze, and Schwartz proposed the following two questions:
  
  1. Is every orientation of any simple connected undirected graph antimagic?
  2. Does every undirected graph admit an antimagic orientation?
  
  Counterexamples to the first question were found using the complete bipartite graph with partite sets of sizes one and two, denoted , and the complete graph on three vertices, denoted . The goal of this project to explore the following open question and conjecture of Hefetz, Mütze, and Schwartz.
  
  3. Is every connected directed graph with at least four vertices antimagic?
  
  Conjecture: Every connected undirected graph admits an antimagic orientation.

• Pre-Requisites: Familiarity with basic graph theory and general graph labeling.

• Bibliography: 

  • J. A. Gallian. "A dynamic survey of graph labeling." Electronic Journal of Combinatorics 1. Dynamic Surveys (2023): DS6.

  • D. Hefetz, T. Mütze, and J. Schwartz. "On antimagic directed graphs." Journal of Graph Theory 64(3) (2010): 219-232.

  • J. Jin and Z. Tu. "Graph antimagic labeling: A survey." Discrete Mathematics, Algorithms and Applications 16(1) (2024): 2330002.

  • D. B. West. Introduction to graph theory. Vol. 2. Upper Saddle River: Prentice Hall (2001)

ADJOINT Program Directors

Dr. Caleb Ashley, (Boston College)

Dr. Naiomi Cameron (Spelman College) - 2025 site director

Dr. Edray Goins (Pomona College)

Dr. Donald E.K. Martin (North Carolina State University)

Dr. Anisah Nu’Man (Spelman College)

The Simons Laufer Mathematical Sciences Institute (SLMath) has been supported from its origins by the National Science Foundation, joined by the National Security Agency, over 100 Academic Sponsor departments, by a range of private foundations, and by generous and farsighted individuals.