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Amir Golnabi

Assistant Professor, Mathematical Sciences

Richardson Hall 244
BS, Montclair State University
PhD, Dartmouth College
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I studied Mathematics and Computer Engineering at the University of Salamanca in Spain. After completing 4 years of coursework, I transferred to Montclair State University where I graduated with a Bachelor of Science in Mathematics in 2007. Thereafter, I started my graduate studies at the Thayer School of Engineering at Dartmouth College, and worked on the "Computational Aspect of Microwave Imaging for Biomedical Applications." In June 2012, I completed my Ph.D. degree in Biomedical Engineering, and joined the Pulmonary Imaging and Bioengineering Laboratory at the Massachusetts General Hospital (MGH) and Harvard Medical School. During my postdoctoral research fellow training, I worked on "Complex Systems Approach to Bronchoconstriction in Asthma."

I have a track record of peer-reviewed publications, conference presentations, and awards, including the Sylvia Sorkin Greenfield Award for the Best Paper Published in Medical Physics in 2013, and the groundbreaking study entitled “Tri-Ponderal Mass Index vs Body Mass Index in Estimating Body Fat During Adolescence”, which was recently published in the Journal of the American Medical Association Pediatrics. I was also the recipient of the prestigious IEEE Microwave Theory and Techniques Society (MTT-S) Graduate Fellowship for Medical Applications in 2010. My research interest includes mathematical modeling, numerical methods, inverse problems, medical image processing, and image reconstruction algorithms. I am also interested in undergraduate mathematics education. I hold a patent in System and Method for Collection and Use of Magnetic Resonance Data and Microwave Data to Identify Boundaries of Interest.

I am very passionate about teaching and I am currently with the Department of Mathematical Sciences as an Assistant Professor. I teach a variety of lower- and upper-level mathematics courses, and I am very interested in implementing novel techniques to engage students in classroom, promoting deep learning, and improving students’ learning experience through shifting pedagogical practices.


Biomedical Engineering: Mathematical Modeling, Medical Imaging, Image Reconstruction Algorithms, Data Analysis, and Image Processing
Undergraduate Mathematics Education: Deep learning, Undergraduate Research Experience


Office Hours


9:15 am - 10:00 am
11:15 am - 12:00 pm
11:15 am - 12:45 pm


Research Projects

Mathematical Modeling and Medical Imaging

I am interested in the science of biomedical imaging, how data can be collected, processed, assembled, and presented as an image, how it may be visualized, and how it may be interpreted. In addition, my research focuses on the application of biomedical imaging for new methods, techniques, and tools to further understanding of biological mechanisms of human diseases.

Adjunct Mathematics Instructor Resources and Support: Improving Undergraduate Precalculus Teaching and Learning Experience

Undergraduate students' persistence in STEM is heavily influenced by their classroom experiences, particularly in entry-level mathematics courses. Considerable research has been conducted showing that improved instruction by full-time faculty can increase student motivation and persistence in mathematics courses. However, entry-level courses, such as PreCalculus, are often taught by adjunct and other part-time instructors, who traditionally have tended to be offered only minimal professional development and support for teaching undergraduate mathematics. Thus, there is a pressing need to focus on developing instructional practices among adjunct and other part-time instructors. This project will build a model of course coordination and adjunct instructor support to improve the teaching and learning of PreCalculus.

While some work has been done to understand the benefits of supports for part-time instructors at the undergraduate level, they have focused mostly on graduate teaching assistants rather than adjunct instructors. Our project extends this work to adjunct instructors and will contribute to the research base the adjunct instructor population. By building a model of adjunct instructor resources and support, this project contributes to deeper understanding of how such efforts impact (1) adjunct instructor knowledge and instructional practices, (2) adjunct instructor job satisfaction, and (3) student academic success and retention in STEM majors. This understanding could help other departments and institutions with similar instructor populations to better support their adjunct faculty, with the goal of improving student learning and persistence in PreCalculus and beyond.

Research Assistant Opportunity

Research assistant wanted with an interest in medical image reconstruction. This position is ideal for anyone considering future graduate study/career in medical imaging and/or image processing.

Responsibilities include regular importation and quality assurance of remote biomedical image data using FTP and MATLAB. Implementation of new mathematical techniques for image reconstruction.

Required Skills: Programming experience in MATLAB and shell scripting, familiarity with both Linux and Windows operating systems, with a focus on command line interface.

Anyone interested in the position should write to me (with an attached CV) at: golnabia[at]montclair[dot]edu.

Undergraduate and Graduate Research Opportunity

I am constantly looking for motivated undergraduate and graduate students who are interested in doing research in applied mathematics and have a GPA greater than 3.5/4. If you are qualified, just stop by my office or send me an email including your CV.