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Amir Gandomi Sereshki

Assistant Professor of Information Systems and Business Analytics


Degrees

PHD, 2012, Ryerson University; MS, 2005, Iran University Of Sci & Tech; BS, 2003, Iran University Of Sci & Tech


Bio

Dr. Amir Gandomi is an Assistant Professor in the Department of Information Systems and Business Analytics at Frank G. Zarb School of Business. Prior to joining Hofstra University, he served as an Assistant Professor in Ted Roger's School of Information Technology Management, Ryerson University.

Dr. Gandomi’s research interests include optimization (convex and nonconvex), machine learning, reinforcement learning, and natural language processing with a focus on applications in healthcare and marketing.

In healthcare, Dr. Gandomi aims to develop innovative solutions to help physicians with the diagnosis and treatment planning of medical conditions. He leverages the latest advances in machine learning, deep learning, and reinforcement learning to generate solution-oriented applied research. Dr. Gandomi is collaborating with an industry partner in New York where he directs a data science team working on research projects on individualized treatment planning and optimization of dynamic treatment regimes.

Dr. Gandomi is pursuing two lines of research in marketing. In his research on Marketing/OR interface, he employs stochastic modeling, game theory, and optimization to develop theoretical models to analyze the effectiveness of loyalty programs and to optimize their design. The second area involves generating insights from large-scale unstructured datasets using machine learning and natural language processing.

Dr. Gandomi has been awarded over $250,000 in research grants and scholarships. One of his publications titled Beyond the hype: Big data concepts, methods, and analytics was recognized as a “Hot Paper” by Web of Science in 2016 as it received enough citations to place it in the top 0.1% of papers in the field of Social Sciences. This article has been the most downloaded and most cited article of the journal since 2016 and is currently among the top 15 most-cited articles ever published on Big Data in Web of Science journals. For the complete list of his publication, please refer to Dr. Gandomi's Google Scholar Profile.

Dr. Gandomi has extensive experience in designing and developing Business Analytics curriculum and degree programs. He currently serves as the Chair of the Curriculum Committee in Zarb’s Information Systems and Business Analytics Department.


Teaching Interests

Data Science and Business Analytics, Text Mining, Sentiment Analysis, Web Analytics, Decision Analysis, Business Statistics, Simulation, Operations Management.

Research Interests

Big Data, Machine Learning, Natural Language Processing, Reinforcement Learning, Medical Informatics, Operations Research/Marketing Interface.

Recent Courses Taught

Course Title Level
BAN 122 INTERMEDIATE BUSINESS STATS Undergraduate
BAN 172 SOCIAL MEDIA & WEB ANALYTICS Undergraduate
BAN 192 PRACTICUM IN BUSINESS ANALYTIC Undergraduate
BAN 203 AVND QUANTVE ANALYSIS FOR MGRS Graduate
BAN 272 WEB ANALYTICS FOR BUSINESS Graduate
IT 014 INTRO COMPTR/CONCPT SOFTWARE Undergraduate
IT 204 SIMULATION IN BUISINESS Graduate
IT 309 RESEARCH SEMINAR IN INFO TECH Graduate
Photo of Amir Gandomi Sereshki

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