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Li Wang

Research Fellow on Computer Vision

Biography

I am currently a Research Fellow (postdoctoral) in Zhejiang University(Ningbo) China, especially working on Image editing and Multimodal Alginment including audios, images and texts. I am also an experienced Machine Learning and Computer Vision Engineer with 9+ years experience (including 3+ years commercial experience). I have managed and completed 7+ projects, which applies cutting-edge machine learning and deep learning models to solve real-world and research cases. I have extensive experience of designing and building up machine learning frameworks independently and training large datasets on the GPU Cloud. I’m experienced on software/system development and image/video/geometry processing. I obtained my PhD degree on Computer Vision and Deep Learning at National Centre for Computer Animation, Bournemouth University, Top1 animation centre in UK, 2020. I received my M.Eng. and B.Sci. degrees in Computer Science at Jilin University in 2016 and 2013, respectively.

I like to get my hands dirty on programming and try new things on up-to-date applications. I love sharing ideas with people and learning from them as well. I post many things on this website, and hope you’ll find something interesting.

Education

  • PhD in Computer Science, Sep 2016 - Sep 2020

    Bournemouth University, UK

  • Visiting Scholar, Oct - Nov 2019

    University of Malaga, Spain

  • Visiting Scholar, Apr - Oct 2017

    Tsinghua University, China

  • M.Eng. in Computer Science, Sep 2013 - Jun 2016

    Jilin University, China

  • B.Sci. in Computer Science, Sep 2009 - Jun 2013

    Jilin University, China

Experience

 
 
 
 
 

Research Fellow

Zhejiang University(Ningbo)

Oct 2023 – Present Ningbo, China
Researches on Computer Vision, especially Image editing based on Diffusion Models and Multimodal Alignment including audios, images and texts.
 
 
 
 
 

Computer Vision Engineer

Startup Incubator

Sep 2020 – Jun 2023 Bournemouth and Changchun
  1. Design and implement an AI-powered system for video production. This system is implemented in Python and PyTorch with Deep Learning models (e.g., Diffusion Models, Transformers, CNNs, YOLO etc.) and libraries (e.g., OpenCV, FFMPEG etc.).
  2. Develop and implement a data collection tool: Image2Dataset. This project involves Web Scraping, Image Classification and Object Detection etc.
  3. Develop and implement a 3D geometry texture synthesis framework for geometry processing, which is able to automatically synthesize textures onto arbitrary sufaces. The implementation involves Python, Blender and Differential Renderer (e.g., Soft Rasterizer).
 
 
 
 
 

INTERN Software Engineer

SensorID

Sep 2019 – Oct 2019 Campobasso, Italy
  1. Develop a software with User Interface for real-time monitoring and recording sensor data.
  2. The software is developed in Python with libraries such as Tkinter, Matplotlib and MongoDB as database, then it’s transformed by PyInstaller into a single .EXE file without any python dependencies.
 
 
 
 
 

INTERN Machine Learning R&D Engineer

ITware

Aug 2019 – Sep 2019 Budapest, Hungary
  1. Research about Recommendation System (RS) in Machine Learning area, which involves SVM, Linear Regression, Decision Tree etc.
  2. Design a potential customized scheme of RS for the European iGame Project.
 
 
 
 
 

INTERN R&D Engineer

IBM(China) Ltd.

Jan 2013 – May 2013 Beijing, China
  1. R&D engineer for an intranet office product.
  2. Optimize software performance on various Windows/Linux systems (e.g., OpenSUSE, Redhat, CentOS, Debian, Ubuntu and Windows servers), which involves implementing efficient search/sorting algorithms and parallel computing (e.g., C/C++ in CUDA programming and multi-processing etc.)

Recent Posts

EfficientNet_mobilenet_shufflenet

Brief summary of efficient Mobilenet and Shufflenet

Algorithms_in_ml

Specific_math

Archive for some specific and easy forgotten mathematic.

Object_detection

Summary of object detection in DL

Training_tricks_dl

Summary neural network training tricks.

Projects

Commnad_line_Program_Youtube_Music_Channel_Scraper

This program scrapes the given Youtube music channels by fetching infomation of videos, and saving information and videos into local …

Mesh_preprocessor_in_blender_with_python

This project presents a mesh preprocessor tool which works with python and blender. It’s capable of processing mesh files in …

Decomposition_for_normal_images

This project presents a Matlab program implemented to decompose a normal image into a structure normal image and a detail normal image, …

Stable_video_style_transfer

This project aims to deal with the flickering problem caused by naively applying per-frame stylization methods (e.g., Fast-Neural-Style …

Real_time_recording_sensor_rawdata

This is a small prototype that I had been working on when I was a visiting scholar (more like an intern) in Italy. The main purpose is …

Fast_photographic_style_transfer

This project aims to implement a torch version for fast photographic style transfer based on Fast-Neural-Style. The teaser image is a …

Publications

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors

Through this study, we developed and validated a system for energy expenditure calculation, which only requires low-cost inertial …

Bas-relief modelling from enriched detail and geometry with deep normal transfer

Detail-and-geometry richness is essential to bas-relief modelling. However, existing image-based and model-based bas-relief modelling …

Fast photographic style transfer based on convolutional neural networks

The techniques for photographic style transfer have been researched for a long time, which explores effective ways to transfer the …

Photographic style transfer

Image style transfer has attracted much attention in recent years. However, results produced by existing works still have lots of …