AbouEl-Makarim Aboueissa Ph.D.
I am a Professor of Statistics (tenured) in the Department of Mathematics and Statistics in the College of Science, Technology, and Health at the University of Southern Maine (USM). Prior to joining USM, I was at the Grand Valley State University as the only full-time Visiting Assistant Professor. My graduate education is in both theoretical and applied statistics. My doctoral degree is in statistics with concentration being applied statistics. My experience includes teaching both undergraduate and graduate courses in statistics, data science, biostatistics, and statistical evaluation of the clinical data from multi-center clinical trials. I have a good range of teaching experience both in-site and online gained over 20 years. I regularly consult with other academic scholars and students to assist them with statistical methods that can be used in their fields.
I have strong teaching experience both online and in classroom, gained over 20 years. I prepare both undergraduate and graduate courses and deliver my lectures weekly, hold regular office hours and review comments and questions after each session, grade and write feedback on homework, labs and exams, and am always accessible to students by email, phone, and in person. Many times, to help my students to see the ‘big picture’, I present students with ‘real data’ sets and we discuss about the context in which the data were collected so that the students can learn how to make a connection between the data collection approach(es), statistical methods and how other professions may have been involved in these projects. I often use projects involving real data in the mid-semester and final exams. In other words, learning and exams for my students take place in classroom environment, where the data are extracted from real-life situations, which also then equals the actual context where these students’ learnings/knowledge will be applied and drawn. I use often quizzes and regular homework assignments as a gauge of how well my students are learning the concepts and procedures of a particular topic. Quizzes and regular homework give my students opportunities to practice new skills and to learn what kinds of questions to ask. Projects and exams give my students an opportunity to apply their learnings, tie ideas together and to analyze and solve a mathematical or statistical problem in greater detail and depth. My courses emphasize a teaching and learning approach that is very often problem based and investigative. In short, I embrace every teaching opportunity that I can find, and I work enthusiastically and effectively with my students at a variety of levels. I believe that in keeping all my courses and tutoring sessions student-centered, I can create a dialogue with my students and in this way support, encourage and help them to learn the process to discover answers for their questions.
My solid training in theoretical statistics coupled with over 15 years of collaborations in the areas of public health, medicine, nursing and applied medical puts me at an extremely advantageous position as a researcher at the interface of interdisciplinary and translational research. The scope of my research interest is broad, drawing upon theoretical and applied statistics. Most of my recent work has focused on developing statistical techniques for estimating population parameters from incomplete data assuming that an underlying population is normally or lognormally distributed. My research collaborations over the last decade encompass projects in areas as diverse as community-based participatory research involving underserved populations. Most of these collaborations reported the results of community, public health research, applied medical, pharmacology and toxicological studies, and Environmental Science; examples include (1) the cytotoxicity and genotoxicity of particulate and soluble hexavalent chromium in leatherback sea turtle lung cells, (2) an investigation of how heart failure and myocardial infarction hospitalization rates vary in Maine along the rural-urban continuum, (3) an exploration of the geographic and social factors that influence food insecurity in Maine’s second largest population center, Lewiston, (4) an outcome analysis of a nurse-run cardiovascular risk factor screening program designed to reach rural Mainers, (5) a theoretical analysis of how the urban landscape impacts obesity risk, and an analysis of maternal and child health trends, outcomes, and risk factors in Maine, (6) the Maine Savvy Caregiver Project (MSCP); the purpose of the MSCP was to translate the Savvy Caregiver Program to a community wide evidence-based intervention for dementia family caregivers statewide and replicate outcomes from the original Savvy RCTs, (7) Particulate depleted uranium is cytotoxic and clastogenic to human lung epithelial cells, (8) Chronic Exposure to Zinc Chromate Induces Centrosome Amplification and Spindle Assembly Checkpoint Bypass in Human Lung Fibroblasts. In these projects, I have played a much larger and more important role than simply performing statistical analysis of data sets. I have been an integral part of the study design process and have been invaluable in data interpretation.
Schedule Spring 2018
MAT 210 Business Statistics (online)
MAT 220 Statistics for Biological Sciences (online)
MAT 498 Topics
STA 591 Topics in Biostatistics
Schedule Fall 2018
MAT 210 Business Statistics
MAT 220 Statistics for Biological Sciences
MAT 488 Introduction to Data Mining
STA 588 Introduction to Statistical Data Mining