SCARA Manipulator: Dynamics & Simscape Control
SCARA CAD integration, analytical inverse kinematics, trajectory generation, and independent-joint PID tracking in MATLAB/Simulink Simscape Multibody.
Autonomous Systems & Deep Reinforcement Learning Researcher
I am a graduate researcher with a strong background in Mechatronics and Control Theory. My research focuses on developing intelligent, safety-aware decision-making algorithms for autonomous vehicle navigation, multi-agent trajectory forecasting, and deep generative computer vision in dynamic urban environments.
Formal academic training in Mechatronics Engineering, Control Theory, and Machine Learning.
Developing robust algorithms for perception, multi-agent forecasting, and optimal decision-making in dynamic environments.
Designing hybrid Reinforcement Learning (RL) and Imitation Learning formulations with safety guarantees for vehicle motion planning and obstacle avoidance in unstructured dynamic urban traffic.
Modeling crowd interactions and social dynamics using Spatio-Temporal Graph Convolutions (ST-GCNN) paired with Conditional VAEs and Gaussian Mixture Model latent spaces.
Object detection with YOLOv11, unpaired image-to-image translation with CycleGAN, and generative text-to-video experiments.
Comparative histopathology image classification using Vision Transformers (ViT) and Deep Residual Networks (ResNet), with careful evaluation of model behavior and limitations.
Open-source implementations, experiments, visual results, and technical documentation across AI, robotics, and control.
Proficiency in deep learning libraries, robotics tools, software engineering, and mathematical foundations.
Academic teaching assistantships and machine learning engineering experience.
I am always open to discussing novel research directions, exchanging ideas on Autonomous Systems & Deep Learning, and actively exploring prospective Ph.D. positions and academic collaboration opportunities.