SHAUKAT ALI SHAHEEAssistant Professor Information Technology & Systems +91-7900444090 (Ext-247) email@example.com
Shaukat Ali Shahee earned his Ph.D from SJM School of Management, Indian Institute of Technology Bombay. In his doctoral research, he explored various challenges posed by imbalanced data in presence of different data intrinsic characteristics. His work has been published in peer-reviewed journals like International Journal of Artificial Intelligence and Soft Computing, Applied Intelligence, Data Mining and Knowledge Discovery, and chapters in the reputed book series Advances in Data Mining: Applications and Theoretical Aspects. His teaching interests are Machine Learning, Artificial Intelligence and Deep Learning, Natural Language Processing and Business Statistics.
Shahee has industry experience of 5.5 years. Before joining academia, he worked as a Quantitative Research Analyst at AlphaCrest Capital Management. Earlier, he was a Deputy Manager at Bank of Maharashtra and Research Engineer at CSE department IIT Bombay.
- Shahee, S. A., & Ananthakumar, U. (2021). An overlap sensitive neural network for class imbalanced data. Data Mining and Knowledge Discovery, 1-34. https://doi.org/10.1007/s10618-021-00766-4
- Shahee, S. A., & Ananthakumar, U. (2020). An effective distance based feature selection approach for imbalanced data. Applied Intelligence, 50(3), 717-745.
- Shahee, S. A., & Ananthakumar, U. (2018). Synthetic sampling approach based on model-based clustering for imbalanced data. International Journal of Artificial Intelligence and Soft Computing, 6(4), 348-364.
Advanced Machine Learning, Management Information Systems