Misc

Machine learning projects

• Proposing and implementing a novel deep learning model by using feedforward neural networks and bidirectional long short-term memory (LSTM) to improve the prediction accuracy of protein secondary structure prediction based on benchmark datasets
• Proposing and implementing Reinforcement learning (RL) algorithms such as Q-learning and deep reinforcement learning (DRL) algorithms such as double Deep Q-network (DDQN) for energy management system (EMS) to improve the vehicle energy efficiency and convergence rate based on the data from Alternative Fuels Data Center (AFDC).
• Proposing and implementing the bidirectional long short-term memory (LSTM) network introduced to improve the deep Q-learning-based EMS (Energy manage system) improve the energy efficiency based on the synthesized data.

  Software engineering

• Using Solidworks to create detailed 3D models with complex shapes and geometries, using parametric modeling to govern the behavior of the model and using simulation tools to test and analyze the designs virtually.
• Using Python to simulate real-time sensor data processing and analysis, aiding in decision-making for autonomous systems, predictive maintenance, and performance optimization.
• Using Python to implement the coding, running and testing in the task management system project and using Git to track the project’s version history