Research Topic: Human-object contact identification, (Python, OpenMesh,OpenCV)Summary: the camera detection for when humans and surrounded objects are contacting.• Became proficient in Python, OpenMesh, and OpenCV to detect and predict contact between human and objects when the object is out of the camera view.• Used CAD to generate mesh to compute human-object contact in photo.• Implemented a convolutional neural network on annotated human joint image dataset. Model achieved 95.2% accuracy.• Assisted PhD students to manually annotate human joints, using Blade, to generate a dataset used for human-object detection.• Presented results in the UCI Research Symposium to a 40 person cohort consisting of researchers and professors in various computer, data, and mathematical science groups across campus.• Awarded a total of $1375 by the UCI Summer Undergraduate Research Fellowship for excellence in research.

Research Topic: BRLiDAR Dataset: Semantic Point Clouds Annotation for Humans in IndoorEnvironments, (Python, C++, ROS)Summary: Research LiDAR 3D point cloud semantic segmentation for pedestrians in an indoor environment.• Provide indoor pedestrian detection solution for laser sensors.• Collaborated with PhD and master to construct the Velodyne Light Detection and Ranging (LiDAR) sensors pedestrian 3D pointcloud dataset by auto-labeling strategy using Robot Operating System (ROS) python and C++ API• Provided tutorial that deploy the state-of-the-art pointcloud semantic segmentation models to evaluate our dataset• Write research publications in progress.