Dr. Chaher Alzaman

Biography

Chaher Alzaman's work encompasses data analysis, decision trees, neural networks, and classical statistical models. He holds a Ph.D. in algorithm design for solving nonlinear systems, which provides a solid foundation for his research. Alzaman’s research primarily focuses on leveraging neural networks as forecasting tools, exploring the role of big data in predictive analytics. He has designed and implemented a wide range of learning algorithms, including Neural Networks, LSTM, Random Forest, KNN, SVM, and genetic-based algorithms. His work in Data Analytics and Optimization spans multiple projects involving Warehouse Management Systems, Bike Sharing Systems, Real Estate Markets, and Financial Markets. Alzaman's publications in top-tier journals highlight his contributions to the field, including studies on optimizing stock portfolio selections using reinforcement learning and forecasting optimization for stock predictions. He also actively participates in international conferences, sharing insights on machine learning applications in financial contexts.

Research Interests