1. Develop and Train Machine Learning Models Assist in building predictive models using supervised and unsupervised learning techniques for industrial and control applications. 2. Data Collection and Preprocessing Collect, clean, and analyze datasets from simulations or real-world systems to prepare them for modeling and analysis. 3. Implement Optimization Algorithms Apply nature-inspired and mathematical optimization algorithms to improve system performance and process efficiency. 4. Simulation and Control System Modeling Support the development of simulation models for dynamic systems using tools like MATLAB/Simulink or Python-based libraries. 5. Technical Reporting and Presentation Document findings, prepare technical reports, and present results to the research or industrial team.