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Summer 2022 CUBE Program for Underrepresented Undergraduates

CUBE: Collaborative Undergraduate Biostatistics Experience

                            Program dates: 
Monday, June 6, 2022 to Friday, July 29, 2022                         
   Move-in day at Virginia Tech*:
Saturday, June 4, 2022
   Housing at Virginia Tech*: Students will stay in a furnished apartment with a full kitchen at the historic  Patrick Henry Hotel in Downtown Roanoke. Housing will be covered by the CUBE program. 
Housing details for University of Virginia are still underway.

This program is currently funded by the integrated Translational Health Research Institute of Virginia (iTHRIV), as well as by Virginia Tech’s College of Science, the Department of Statistics, the Fralin Life Sciences Institute (FLSI), the Institute for Society, Culture, and Environment (ISCE), and the Center for Biostatistics and Health Data Science (CBHDS).

The Collaborative Undergraduate Biostatistics Experience (CUBE) is an 8-week training program designed to give motivated, underrepresented minority undergraduate students the opportunity to engage in a full-time (~40 hours/week) collaborative data science experience, along with related professional development activities. CUBE is aimed at promoting diversity, equity, and inclusion in the STEM fields.

The goal is to offer students an experience working with a real-world dataset under the mentorship of experienced collaborative data scientists, as well as clinical experts, to help them determine if they want to pursue a career in collaborative applied data science, while they develop skills for the workforce or graduate school. Virginia Tech's collaborative project will be carried out under the mentorship of Charlotte Baker, PhD, and the students will be programming in R and analyzing a large publicly available dataset to characterize factors associated with ACL injuries. 

The program includes weekly research and professional development seminars, periodic social events, and a final symposium during which students will present their research. Four students (two at each participating site: Virginia Tech and University of Virginia) will be selected to participate in this program during Summer 2022, and will be compensated $4,800.** Housing and social outings will also be provided, pandemic permitting***. Students will be responsible for food/meals and roundtrip travel to and from the site. 

**Note: Payment is taxable income to participating students who are current US Citizens or have a working visa within the US. Please review IRS publication 970, Tax Benefits for Education for additional information.

***Note: Virginia Tech and University of Virginia are planning for in-person educational opportunities in Summer 2022. However, these opportunities will be subject to any state, federal, and university regulations related to the COVID-19 pandemic. We will keep applicants posted as new regulations emerge. All CUBE participants will be expected to abide by each university's public health regulations.

The CUBE Program was featured in iTHRIV's February 2022 newsletter. See below a brief video from Tosin Ogunmayowa sharing his experience working with CBHDS for the past year as a graduate student intern and his enthusiasm to serve as a CUBE mentor for Summer 2022. 

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Program Eligibility and Expectations

  • Underrepresented minority undergraduate students considering a career in data science, or a similar field, are encouraged to apply.
  • Preference will be given to undergraduate students who are rising seniors enrolled in a STEM program who have a cumulative GPA of 3.0 or higher. Well-prepared undergraduate students who are rising juniors will also be strongly considered.
  • CUBE interns must commit at least 40 hours/week to the training program, and therefore interns are not permitted to enroll in summer classes, participate in MCAT prep courses, engage in activities for pay, or engage in other activities that may interfere with program activities.
  • CUBE interns commit to participating in the full 8-week program. Students may not take vacation during this training period.
  • International students are welcome to apply, noting that they must have a working visa in the US in order to receive payment.

Application Instructions

Please complete your application using the link below, noting that you will be asked to upload your resume, an unofficial transcript, and a cover letter. Cover letters might include information related to the following questions: 

  • Why are you interested in the CUBE program?
  • What strengths do you bring to the CUBE program?
  • Describe areas of improvement that you think the CUBE program can help with.
  • How do you think the CUBE program might contribute to your career plans or continued education?

Application Deadline:
Rolling acceptance through Saturday, April 30, 2022 at 11:59 PM EST

If you have any questions, please contact Alicia Lozano (

We look forward to receiving your application!

CUBE Partners and Mentors

Alex Hanlon

Alexandra L. Hanlon (CUBE Director, VT)

Dr. Hanlon obtained her doctorate degree in Biostatistics from Temple University, and has spent the last 30 years building her career as a collaborative statistician in the health sciences. She came to Virginia Tech in 2019 as a Professor of Practice in the Department of Statistics, and now serves as the founder and Director of the Center for Biostatistics and Health Data Science (CBHDS).  She spent the ten years prior to coming to Virginia Tech at the University of Pennsylvania. There she built the BECCA (Biostatistics * Evaluation * Collaboration * Consultation * Analysis) Lab in the School of Nursing, partnering with Jesse Chittams as her managing director. Aligning with Jesse’s commitment to diversifying the profession of collaborative biostatistics, BECCA became known for mentoring and training underrepresented high school, undergraduate, and graduate students in collaborative biostatistics. Dr. Hanlon has served as principal or co-investigator on numerous federally and foundation funded research projects within the areas of mental health, cancer, cardiovascular disease, stress, sleep, communication, violence, gerontology, obesity, biobehavioral studies, and care transitions. She has co-authored over 400 peer-reviewed publications through her collaborations. She serves on various Data Safety Monitoring Boards for drug development clinical trials, and as a scientific reviewer for the Patient-Centered Outcomes Research Institute (PCORI), the National Science Foundation (NSF), and the National Institutes of Health (NIH). She is a Fellow of the American Statistical Association (ASA) and currently serves on the ASA's Board of Directors.

Alicia Lozano (Biostatistics Mentor, VT)

Ms. Alicia Lozano obtained her master’s degree in Biostatistics from Drexel University in Philadelphia. Her interest in research was initiated through her participation in two summer research experiences for underrepresented minorities as an undergraduate student in mathematics. She has seven years of collaborative experience supporting numerous clinical or biomedical research projects, starting as a graduate student intern at the University of Pennsylvania and now as a Research Associate and Assistant Director of the Center for Biostatistics and Health Data Science (CBHDS) at Virginia Tech. Currently, Alicia is funded on several contracts and NIH grants, and has contributed to work in a broad range of areas, including but not limited to sleep, cardiovascular health, diversity recruitment strategies in older adults with mild cognitive impairment, Puerto Rican youth wellness, and social determinants of health. Her statistical expertise and experience include experimental study design, randomization scheme generation, sample size/power estimation, data management and survey development in REDCap and Qualtrics, data cleaning and analysis using SAS and R statistical software, as well as the preparation of grant proposals, manuscripts, and data safety monitoring committee reports. As a rising collaborative statistician in the health sciences, she has mentored over 15 undergraduate and graduate students and has authored over 40 peer-reviewed research publications, with several also under review or in progress.

Kimberly Weems (Partner & Mentor, NCCU)

Dr. Kimberly S. Weems earned her B.S. in mathematics from Spelman College and her M.A. and Ph.D. in applied mathematics with a statistics emphasis from the University of Maryland, College Park. Afterward, she pursued postdoctoral studies in the Statistics Department at North Carolina State University (NCSU), where she later joined the faculty and served for two years as Co-Director of Statistics Graduate Programs. From 2004 through 2018, she served as an instructor with the NCSU-Duke Summer Institute for Training in Biostatistics. Since moving to North Carolina Central University, Dr. Weems has been instrumental in enhancing the statistics curriculum in the mathematics department. She has been a speaker, panelist, mentor, and session organizer at the Fostering Diversity in Biostatistics Workshop and Joint Statistical Meetings Diversity Workshop. In addition, she is a faculty mentor with the National Alliance for Doctoral Studies in the Mathematical Sciences and a member of the Mathematical Sciences Institutes Diversity Initiative leadership team. Her research interests include flexible statistical models for count data.

Monica Ahrens (Biostatistics Mentor, VT)

Dr. Monica Ahrens received her PhD in Biostatistics from the University of Iowa in 2022. During her time at the University of Iowa, Monica taught an R programming course for the Iowa Summer Institute for Biostatistics (ISIB), a program devoted to creating a pipeline for under-represented minority students to attend graduate school in statistics and biostatistics. In addition, Monica worked as a collaborative research assistant throughout her graduate school career, working in areas such as health policy, electronic health records, injury epidemiology, Parkinson’s disease and neuroscience. After finishing graduate school, Monica joined the faculty at the Center for Biostatistics and Health Data Science (CBHDS) and worked under Dr. Alexandra Hanlon as a collaborative biostatistician.


Tosin Ogunmayowa
Tosin Ogunmayoa (Biostatistics and Professional Development Mentor, VT)
Tosin Ogunmayowa is a Graduate Intern for the Center for Biostatistics and Health Data Sciences (CBHDS) and a PhD candidate in the Department of Population Health Sciences at Virginia Tech. His PhD research focuses on using multilevel modeling approach to understand the social and structural determinants of health inequity. His statistical experience includes data preparation, analysis, and visualization using R, SAS, and ArcGIS Pro, while his research experience includes preparation of manuscripts and grant proposals. Tosin has experience in mentoring underrepresented minority students through the Black College Institute, an academic summer enrichment program for rising high school juniors and seniors, and through the Graduate Student Ambassador Program at Virginia Tech.
Gina-Maria Pomann
Gina-Maria Pomann (Professional Development Mentor, DUKE)
Gina-Maria is an Assistant Professor in the Department of Biostatistics and Bioinformatics at Duke University who collaborates with clinical and translational scientists to address scientific problems and develop best practices related to biostatistics collaboration. Gina-Maria is the Director of the Duke Biostatistics, Epidemiology and Research Design (BERD) Methods Core, which employs effort from over 40 faculty, staff and student biostatisticians who collaborate with clinical and translational investigators at Duke. Gina-Maria developed the Biostatistics Core Training and Internship Program (BCTIP) that has facilitated the training and inclusion of over 60 interns on collaborative teams. Gina-Maria founded and presided over the NCSU student chapters for We Connect Now and the NCSU Society for the Advancement of Chicanos, Hispanics and Native Americans in the Sciences (SACNAS) , she won the 2012 outstanding student award at North Carolina State University for her work promoting diversity, and was invited to give the keynote address for the 2020 STEM career showcase for students with disabilities.
Joseph Rhodes
Joseph Rhodes (Professional Development Mentor, UPENN)
Joseph joined the University of Pennsylvania in 2014 after graduating with a degree in Mathematical Sciences from Rutgers University, College of Arts & Sciences, Camden, NJ. With over 8 years of experience, Joseph has acquired considerable expertise in data coordination, management, cleaning and manipulation, statistical programming and reporting, and REDCap database development and administration. He is currently a data scientist with the Biostatistics Consulting Unit (BECCA Lab) within the University of Pennsylvania. In addition, Joseph has significant experience in mentoring . During his career, he has trained roughly 20 interns in the above expertise and has volunteered with the several Diversity Initiatives by the American Statistical Association including Diversity Mentoring Program and Statfest.
jesse chittams
Jesse Chittams (Professional Development Mentor, UPENN)
Mr. Jesse Chittams joined the University of Pennsylvania in 1994 after graduating with a degree in Mathematical Statistics from the University of Maryland. With over 28 years of experience, Mr. Chittams has acquired considerable expertise in data management and statistical analysis through his managerial roles at several data coordinating centers. Currently, Mr. Chittams is the Managing Director of the Biostatistics Consulting Unit (BECCA Lab) within the University of Pennsylvania. Furthermore, Mr. Chittams also has significant experience in mentoring high school students, undergraduate, and graduate students one-on-one through the Diversity Initiative in Research for Underrepresented Minorities (DRUM) program that he initiated in 2001. Throughout his career, he has helped to train over 100 interns in statistics, and served as the Chair of the Committee on Minorities in Statistics for the American Statistical Association. 
Tina Davenport
Tina Davenport (Professional Development Mentor, DUKE)
Dr. Clemontina Davenport earned a BS in Mathematics, an MS in Applied Mathematics, and an MSTAT and PhD in Statistics before joining the CTSI BERD Methods Core within the Department of Biostatistics and Bioinformatics at Duke in 2014. She is currently a Senior Biostatistician and has extensive collaborative research experience in internal medicine, investigating factors that may explain racial disparities in poor health outcomes, primarily in kidney disease, but also in diabetes, hypertension, cardiovascular disease, and others. She collaborates on a wide range of studies, including RCT/RPTs and retrospective observational studies and serves as key personnel on several grants. Tina has taught a first-year master’s level course since 2017 and has worked to develop online training materials for junior researchers. Tina is passionate about teaching and mentorship, the importance of diversity and equity in research and healthcare, and dismantling structural racism. In her free time, she enjoys playing games with her two amazing children, watching soap operas, reading, and taking naps. 
Paulette Ceesay
Paulette Ceesay (Professional Development Mentor, Merck & Co)
Paulette Ceesay is a Principal Scientist in the neuroscience and ophthalmology therapeutic areas at Merck where she provides statistical support in the design, methodology and implementation of clinical trials.  She has also worked in the diabetes, cardiovascular, and anti-infective areas. Paulette co-leads the Biostatistics and Research Decision Sciences Diversity and Inclusion Task Force. The goal of the Task Force is to attract more diverse candidates, as well as continue to develop and inspire current employees as part of Merck’s diverse and inclusive work force. She was also an adjunct in the statistics department at Temple University.  Prior to her statistics career, she was a group health and pension actuary.
Lola Luo (Professional Development Mentor, FDA)
Dr. Lola Luo received an undergraduate degree in computer science from Penn State University.  After several years of employment as a statistical programmer in pharmaceutical industry, she joined FDA in 2014 after graduating with a PhD degree in Biostatistics from the University of Pennsylvania.  For the past 8 years, Dr. Luo has gained experiences in reviewing malignant and non-malignant hematological applications submitted by pharmaceutical companies.  Furthermore, Dr. Luo has participated in several advisory committee meetings as the FDA statistician. 
Charlotte Baker
Charlotte Baker (Professional Development Mentor, VT)
Dr. Charlotte Baker earned her undergraduate degree from Appalachian State University in Health Promotion, followed by Masters and Doctorate degrees in Public Health from the University of Pittsburgh and University of Kentucky, respectively. She currently serves as an Assistant Professor of Epidemiology in the Department of Population Health Sciences at Virginia Tech. She conducts public health research in sports injury epidemiology, physical activity, blood disorders including sickle cell disease, and health equity in order to improve health over the lifespan. Dr. Baker is an expert in data analytics and works to translate research to practice in order to serve and enhance the lives of the underserved.
Sarah Ratcliffe

Sarah J. Ratcliffe (Partner & Mentor, UVA)

Sarah J. Ratcliffe, Ph.D., is a Professor of Biostatistics at the University of Virginia. She currently serves as the Associate Chair for Research, and Director of the Division of Biostatistics, in the Department of Public Health Sciences. She joined the UVA faculty in 2018, after 17 years at the University of Pennsylvania.
Dr. Ratcliffe has a background in statistics and computing, with specific training and expertise in the analysis of correlated data, especially longitudinal and functional data, in predictive modeling, as well as expertise in modeling informative missing data / dropout. She is currently Director of the Research Methods core of the UVA CTSA (iTHRIV), MPI of an NIH R01 developing prediction algorithms in transplant patients, and PI of an NIH U24 Data Coordinating Center (DCC) for the DIVA Trial. Previous research projects included being MPI/DCC director for the Sustained Aeration of Infant Lungs (SAIL) trial (U01), and MPI of an NIH R01 developing novel statistical methods for longitudinal biomarker trajectories with informative dropout using functional data analysis techniques.
Dr. Ratcliffe is a co-investigator on various clinical studies, leading to research publications in numerous disease areas, including neonatology, fetal and maternal medicine, women’s health, HIV/AIDS research, cardiology and critical care medicine. She serves as the statistical member on several DSMBs, and is a reviewer for NIH study sections. She currently serves on the Executive Board for the International Biometrics Society (2021-), was the 2019 ENAR President, and was elected a Fellow of the American Statistical Association in 2020.

Genevieve Lyons (Biostatistics Mentor, UVA)

Ms. Genevieve Lyons obtained her master's degree in Biostatistics in 2012 from the University of South Carolina. Genevieve is an experienced collaborative biostatistician in the Department of Public Health Sciences Division of Biostatistics at the University of Virginia. She provides statistical support and consulting on a variety of research projects with collaborators in the School of Medicine, School of Nursing, and others. She is the manager of the Research Methods core for the iTHRIV CTSA. Her research interests include maternal and child health, cardiology, cystic fibrosis, secondary data analysis, and health equity.. Other professional interests include data visualization, science communication, and evidence-based policymaking. Genevieve especially enjoys working with students on biostatistics and statistical programming.

Jennie Z. Ma (Biostatistics Mentor, UVA)

Jennie Z. Ma, Ph.D., is a Professor of Biostatistics at the University of Virginia, with a secondary appointment in Nephrology. Her research interests mainly focus on the outcomes research, particularly innovative applications of statistical methods in clinical studies. She has successfully integrated robust study design and statistical methodology with subject-specific expertise, and developed innovative methods in trajectory testing, biomarker selection, and growth modeling in malnourished children.
Dr. Ma has served as a PI, co-PI, and co-Investigator in many federal and foundation funded studies and collaborated with numerous clinical investigators in a broad range of clinical and biomedical studies for more than 25 years. In these studies, Dr. Ma has led the biostatistical efforts and contributed significantly from study conception and design to final scientific reporting.  Besides collaborative research activities, she currently serves as a co-director of the Biostatistics, Epidemiology, and Research Design (BERD) core of the UVA CTSA (iTHRIV), and co-PI of a NIH funded project to investigate the causal effects of physiological factors on renal outcomes using machine learning methods.