Career Profile
Highly motivated, self-driven Computer Vision / Backend practitioner with 1.5+ yrs research experience in Deep Learning and Computer vision. Participated in multiple related projects of deep learning, computer vision, data mining and back end.
Related Experience
Work Description:
Participated in Deep Intermodal Video Analytics (DIVA) project at Johns Hopkins University with following responsibilites:
1. Designed, implemented and fine-tuned vehicle semantic part detection / pose estimation neural network and data pipeline.
2. Synthesized car images using graphical rendering engine (i.e. Unreal Engine) with spare key point annotation, plus domain randomization for bridging the gap between synthetic data and real (DIVA) data.
3. Provide cues of temporal shape dynamics and functional relationship between cars and humans for action recognition.
4. Perform object (car and human) tracking with feature embedding algorithms and deep nets (e.g. triplet loss network) using hard data mining strategy and particle filter (SMC - Sequential Monte Carlo) / Kalman filtering graphical model.
Link: here
Work Description:
Participated in Measuring Patient Mobility in the ICU (ICU) project at Johns Hopkins University with following responsibilites:
1. Design hierarchical activity filtering system and pose/appearance based feature extraction + temporal spatial classifier for activity classification in ICU.
2. Train activity classifier with few-shot and semi-supervised based methods to overcome the scarcity in training data.
Link: here