Xin Liu
Applied scientist in Computer Vision/Deep Learning
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About
I am a PhD and applied scientist in Computer Vision, Deep Learning, and Computer Graphics. I have been working in these fields since 2004 when I was a student with 8 years of experiences as an applied scientist in industry. I am familiar with c++, python, Caffe, Pytorch, TensorFlow, OpenCV, OpenGL, etc. I am looking for my next job in these fields in Greater Toronto Area.
Experience
Staff Machine Learning Scientist 2021 - Present
Compass Management Holdings LLC
Lead R&D efforts in Computer Vision, Deep Learning, and NLP. Representative projects are:
Hero image selection (team lead)
- Yolo based object detection, image rating algorithm, and architecture design
Document processing automation (team lead)
- BERT model based document classification, Named Entity Recognition.
Senior Machine Learning Scientist II 2019 - 2021
Compass LLC
Lead R&D efforts in Computer Vision, Deep Learning, and Video Generation. Representative projects are:
Listing photo super-resolution (team lead)
- SR-GAN based algorithm
- Pytorch, python, AWS SageMaker
Video Studio (team lead)
- Video rendering algorithms based on photos and 3D-models & various AI algorithms
- c++, OpenGl, GLSL, python, Pytorch, and AWS
Senior Computer Vision and AI Engineer 2019 - 2019
Aibee US Corporation
Conduct research in Computer Vision and Deep Learning technologies. Representative project:
Object detection, tracking, and pedestrian flow analyses
- SSD, Motion Detection, Kalman Filter
- Tensorflow, python, and c++
Staff Computer Vision and AI Engineer 2018 - 2019
Huawei Seattle Research Center
Lead R&D efforts in Computer Vision and Deep Learning for cellphone applications. Representative project is:
Real-time AI algorithms on cell phones (team lead)
- Super resolution, Denoise, Artifact Removal, Dehaze Networks
- Caffe, Tensorflow, and python for deep learning
- C++, java, OpenCV, and OpenCL for Android development
Analyst III - Computer Vision and Machine Learning 2014 - 2018
R&D, MDA Corporation
Conduct research in Computer Vision, Deep Learning, Image and Video Processing. Representative projects are:
Ship and wake detection from satellite images (team lead)
- Faster R-CNN, and other deep learning based object detection
- c++, python, Caffe and OpenCV
Change detection and classification from satellite images
- Adaptive image differentiation and deep learning based classification
- c++, python, Tensorflow and OpenCV
Resolution enhancement of satellite images (team lead)
- Multi-spectrum fusion and image super-resolution
- c++, Matlab, Caffe and OpenCV
Moving object detection from airborne videos
- Frame registration and differentiation, motion history image, blob detection, classification and object tracking
- c++, Matlab and OpenCV
Research Associate 2007 - 2014
University of Calgary
Conduct research in Computer Vision and Computer Graphics. Representative projects are:
Lens effect simulation from synthetic and cell-phone images
- Sparse-view based depth-of-field synthesis, depth recovery and parallel algorithms
- c++, java, CUDA, OpenCV, and Android SDK/NDK
Real-time Ray Tracing on GPUs
- Acceleration structures and algorithms for quick ray-object intersections
- c++ and OpenCL for GPU programming
3D reconstruction from 2D images
- Shape from X, Delaunay tessellation and refinement
- c++, OpenCV, and OpenGL? NURBS model fusion
- Approximation of high-order 3D parametric surface and curves
- c++ and OpenGL
Education
PhD in Computer Science
University of Calgary
GDP 4.0/4.0
Focused on Computer Vision, Machine Learning, and Computer Graphics
Master of Science in Computer Science
University of Calgary 2007 - 2009
GDP: 4.0/4.0
Focused on Computer Vision, Machine Learning, and Computational Geometry
University of Calgary, Alberta, Canada 2009 - 2014
