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Ahmed Abbasi
Also published under:A. Abbasi
Affiliation
University of Notre Dame, Notre Dame, IN, USA
Topic
Convolutional Neural Network,Ablation Analysis,Accuracy Metrics,Adverse Events,Age Groups,Anxiety Disorders,Artificial Intelligence,Association Rule Mining,Autoencoder,Benchmark Methods,Beta Values,Cardiovascular Characteristics,Classification Task,Compressed Representation,Computational Efficiency,Control Subjects,Current Major Depressive Disorder,Deep Learning,Deep Neural Network,Deep Neural Network Architecture,Deep Neural Network Model,Demographic Groups,Depression And Anxiety,Design Considerations,Design Objectives,Detection Of Adverse Events,Direct Exploration,Edge Devices,Efficiency Metrics,Emotional Faces,Error Distribution,Event Dataset,Event Detection,Events Database,Facial Expressions,False Positive,Feature Matrix,Feed-forward Network,Food And Drug Administration,Foundation Model,Graphics Processing Unit,Graphics Processing Unit Memory,Health Canada,Industrial Tools,Large Language Models,Lexicographic,Linguistic Patterns,User Modeling,
Biography
Ahmed Abbasi is the Joe and Jane Giovanini Endowed Chair Professor in the Department of IT, Analytics, and Operations (ITAO) at the University of Notre Dame. He directs the PhD program in Analytics. He also serves as Co-Director for the Human-centered Analytics Lab (HAL). Prior to joining Notre Dame, he was an Endowed Chair, Associate Dean, and Founding Director of a Data Analytics center at the University of Virginia. Ahmed received his Ph.D. in Information Systems from the Artificial Intelligence (AI) Lab at the University of Arizona, with a PhD minor in Cognitive Science. He has an M.S. in Operations Research from Columbia University and attained an M.B.A. and B.S. in Information Technology from Virginia Tech.
Ahmed has over twenty years of experience pertaining to machine learning, predictive analytics, and natural language processing (NLP), with emphasis on user modeling applications in online settings related to health, security, and digital user experience. Ahmed’s research has been funded by over a dozen grants from the National Science Foundation and industry partners such as AWS, Microsoft, eBay, and Oracle. He has also received the IEEE Technical Achievement Award, INFORMS Design Science Award, IBM Faculty Award, and Kemper Faculty Award for his work on human-centered AI.
Ahmed has published over 100 articles in journals such as MISQ, ISR, IEEE TKDE, ACM TOIS, Journal of Marketing, JMIS, and IEEE Intelligent Systems, and top-tier conferences such as ACL, EMNLP, NAACL, ICDM, INFORMS, ICIS, LREC, and BIBM. One of his articles was considered a top publication by the Association for Information Systems. He also won best paper awards at INFORMS, MISQ, ISR, and WITS, and was a finalist for the AMA’s Hunt/Maynard Award. Ahmed’s work has been featured in various media outlets, including the Wall Street Journal, Harvard Business Review, the Associated Press, WIRED, CBS, and Fox.
Ahmed serves as Senior Editor for INFORMS ISR and Associate Editor (AE) for ACM TMIS and IEEE Intelligent Systems. Ahmed is a senior member of the IEEE, has served as chair of the INFORMS College on AI, and has been on program committees for various conferences related to AI, information systems, NLP, text analytics, and data mining. He has also served as co-founder or advisory board member for multiple predictive analytics-related companies. His research has been evaluated and deployed in major organizations in the security, telecommunications, and health sectors.