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Weichen ***** Computer Vision Engineer

$780 / day


I’m a highly motivated and results-driven Machine/Deep Learning Research Engineer, currently leading the R&D Team at Bodymapp Pty Ltd. I completed my Ph.D. in Deep Learning at the University of Sydney under the supervision of Prof. Dong Xu. My expertise lies in devising and enhancing AI algorithms for 2D & 3D visual applications. I have published research papers in top AI Conferences and Journals, including CVPR, T-PAMI, and T-IP. My skills also include building, managing, and optimizing DevOps and AWS MLOps pipelines, which enhance the speed and accuracy of 3D body mesh reconstruction and measurement engines. Additionally, I am experienced in implementing and collecting ML annotations to continuously improve neural net models.

I possess a rich portfolio of research in AI, covering 2D/3D image/video de-noising, 3D human point cloud and mesh reconstruction, SLAM, and multi-modality/multi-domain transfer learning, with applications aimed at practical solutions.


.NET Framework3D mesh3D point clouds (Lidar)3D ReconstructionAtlassian/GitAudio processingAudio-SequencesAWS MLOpsBashBlenderCC#C++CaffeCI/CDCSSDe-noisingDevOpsDistortion CorrectionEvaluation MetricsFirebaseGoogle/Microsoft OfficeHTML.JavajQueryLandmark DetectionLocalizationMATLABMySQLNumPyOmniGraffleOpen3DOpenCVPostgreSQLPythonPyTorchRecognitionRegressionRGB/Depth image/videoScikit-LearnSegmentationSLAMSublimeTensorFlowTextVisual Studio CodeXML
AI Research ScientistComputer Vision EngineerData ScientistDeep Learning EngineerMachine Learning Engineer


2017 - 2021 Doctor of Philosophy (Ph.D.), Deep Transfer Learning at University of Sydney
2013 - 2016 Bachelor of Information Technology (BIT), Honours Student (Honours Class I) at University of Sydney
2009 - 2012 High School Affiliated at Nanjing Normal University


May 2021 - Present Research Engineer & RnD Team Lead at Bodymapp Ltd

– Analyze and summarize work progress, share and discuss technical and DevOps ideas.
– Correct depth camera lens distortion using combinations of ML and DL methods (Python, mainly neural nets).
– Implement 3D human mesh reconstruction model from depth videos using combinations of ML and DL methods (Python & Matlab).
– Build AWS ML backend pipeline for a mobile application (bash, Python, AWS S3, EC2, Terraform, etc.).
– Optimize 3D human model measurement system (C++).
– Build and maintain annotation platform (Label Studio) for continuous improvement of neural net models (Python & XML).
– Assist in monitoring and maintaining algorithm reliability in the production pipeline (AWS & plugins).

July 2019 - Dec 2019 Academic Tutor (ELEC5307 Advanced Signal Processing with Deep Learning) at University of Sydney

– Teach Python programming language and methods for deep learning.
– Introduce Transfer Learning and Domain Adaptation.
– Design two assignments :
1. Organize students to collect fruit data and do fruit image classification challenges with deep CNN.
2. (bonus) Organize students to collect office supply data and do transfer learning office supply image classification tasks using domain adaptation techniques.