I am currently a Master's student and aim to become a PhD candidate in Quantum Machine Learning, publishing since my undergraduate studies, starting with Network Node Load Prediction in IMS Networks, then exploring Energy-Efficient Task Scheduling and Adaptive Thermal Power Algorithms using Deep Reinforcement Learning. Now, I am focusing on exploring Quantum Machine Learning and Computation in solving high-performance computational problems. I am developing and asserting new ways to mitigate quantum hardware noise problems, starting with comparative analysis with classical approaches and methods.