The Operations & Information Systems (OIS) department Research Seminar Committee cordially invites you to attend the research talk by Murtaza Nasir on January 28th 11:00 to 12:30 pm as part of the Manning Operations & Information Systems Speaker Series for Spring 2022. Look forward to you joining us for this talk.
Zoom Link: https://tinyurl.com/ois-s22-speakers
Title: Essays on Data Science & Analytics: Methodology Development and Applications
Abstract: Machine learning (ML) has become increasingly important in the domain of business decision making processes and understanding business problems. In this work we propose some novel machine learning methodologies that enable us to overcome some challenges with working with imbalanced and complex datasets. Furthermore, we present some works that show applications of these as well as some existing ML methodologies. The first methodology, titled “SANSA, a synthetic average neighborhood sampling algorithm”, improves on existing synthetic data generation algorithms for imbalanced learning by providing a novel tuning parameter that allows the algorithm to adapt to a wide variety of datasets, as opposed to existing methods. The second methodology presented, titled “SIFT, a simple interaction finding technique”, presents a novel methodology to make black-box machine learning models more transparent by analyzing and presenting how the any given trained model makes decisions. The methodology can be used to identify novel interactions between predictors as well as any potential biases in the model. In the remaining chapters of this work, we show some applications of machine learning algorithms, including SANSA and SIFT. We present chapters on using machine-learning based analytics to understand important factors and their interactions for successful completion of substance use disorder treatment as well as for various COVID-19 diagnostic as well as prognostic outcomes.
Organized by the OIS Dept. Research Seminar Committee: Yao Chen, Amit Deokar, JM Song, Harry Zhu