AWS S3 Express and Edge

S3 on edge team

• Enrolled in the research project, focused on turning offline signal processing into real-time signal processing, applied the methodology through the integration of real-time sensing of anxiety changes with biofeedback

• Completed real-time signal environment simulation, handled EEG signal noise reduction independently, researched the brain-computer interface for acrophobia monitoring assisted in extracting frontal alpha asymmetry and conducted calculations to adjust the VR environment in real-time, determined the anxiety state by signal data

• Published two full contributed papers at IEEE/EMBS international conference on Neural Engineering (NER)

• Working with Prof. Hope Michelson on her research project “Machine Learning to Detect Fertilizer Adulteration in Developing Countries”, focusing on improving the existing classification model to optimize the APP based on the feedback from Tanzanian users, with the goal of implementing the service of accurately assessing the nutrient content of fertilizer

• Participated in the research project to study robot perception and tele-operating robots, developed a model that can learn without catastrophic forgetting, allowed the robot to continuously recognize different objects

• Researched the papers on continuous learning and deep learning, built a continuous learning framework for object detection, trained a dynamic learning model and completed model optimization