About me

Here is Jiecheng Liao (James, 廖皆成).

I am an undergraduate student currently finishing my Computer Science and Technology Bachelor degree at the Beijing Normal University-Hong Kong Baptist University United International College (UIC).

I had served as a research member at Guangdong Key Laboratory for Artificial Intelligence and Multi-Modal Data Processing advised by Prof. Chen, and currently focusing on my project in Data intelligence lab of UIC. I am also very fortunate to be advised by Prof. Zhang and Prof. Su for some of my projects.

You can find my CV here: Jiecheng LIAO’s Curriculum Vitae.

Check my Personal Website for more interesting stuff.

Email / Github / Personal Website /

Research Interests

Machine Learning
Deep Learning
Computer Vision
Computer Graphics
Medical Image Processing
Smart Contracts Analyzing (on vulnerability detection)

My current research focuses on practical problems that artificial intelligence on Vision faces in Industry and real life. In a word, advanced algorithm and architecture in DL and CV positively influence the life of many people. I wish to devote my talent to this meaningful cause and bring well-being to society.

Honors & Awards

Second Prize in the Guangdong Science and Innovation Competition of Artificial Intelligence Wheeled Robot in September 2023
Third Prize of Group C/C++ of the 14th Lanqiao Cup Guangdong Division in April 2023
Bronze Medal in Kaggle HuBMAP + HPA: Hacking the Human Body in December 2022
Certificate:
- Tencent Computer Vision Project Completion Certificate
- Apsara Clouder Elastic Computing Certificate

On-going Publications

Jiecheng Liao, Weifeng Su, Shi He, Shuhong Chen, Yixuan Ji, Junhao Lu, Liangfu Chen. “\(BMS^3\): Bayesian Modeling Based SwinUNet Segmentation on Self-distillation Architecture”. IEEE International Conference on Bioinformatics and Biomedicine. Under Review, 2024
Shuhong Chen, Zhenkun Luo, Jiecheng Liao, et al. “Smart Contract Vulnerability Detection based on Bytecode Augmentation and Semantic Structure Graph”. IEEE Transactions on Dependable and Security Computing. Under Review
Jiecheng Liao, Junhao Lu, Yixuan Ji, et al. “Mutual Information Calculation on Different Appearances”. International Journal of Science and Research Archive. Accepted

Research Projects

GBC: Gaussian-splatting Based Colorization
- 06.2024-Present
- Outline
  - Pioneered an innovative system for colorizing and three-dimensionally reconstructing monochrome historical films and documentaries, enhancing the preservation and visualization of archival footage.
- Key Responsibility
  - Engineered a real-time colorization pipeline integrating segmented optical flow and the DeOldify algorithm, coupled with ColMap for feature extraction.
  - Developed an end-to-end 3D reconstruction framework utilizing Gaussian Splatting, enabling immersive visualization of colorized historical content.
\(BMS^3\): Bayesian Modeling Based SwinUNet Segmentation on Self-distillation Architecture
- 03.2024-08.2024
- Outline
  - Developed a novel approach for medical image segmentation enhancing domain invariance and generalization.
- Key Responsibility
  - Integrated Bayesian modeling with Swin Transformer-based U-Net architecture and implemented self-distillation mechanism, conducting experiments on multiple prostate MRI datasets.
- Achievement
  - Outperformed state-of-the-art methods with 74.9% average DSC on target datasets and improved computational efficiency to 0.8155 images/second.
ESP32-based Real-Time IV Drip Monitoring and Alert Platform
- 11.2023-04.2024
- GITHUB
- DEMO
- Outline
  - Developed an innovative IoT-based system for real-time monitoring and control of intravenous drips in hospital settings.
- Key Responsibility
  - Designed and implemented an integrated system using ESP32, incorporating drop sensors for real-time monitoring, servo motors for flow control, wireless communication for alert transmission, and a centralized nurse terminal as monitor for multiple IV stations.
Mutual Information Calculation on Different Appearances
- 11.2023-04.2024
- Outline
  - Conducted research on applying mutual information (MI) to assess similarity between images, particularly focusing on comparing appearances of different individuals.
- Key Responsibility
  - Implemented and analyzed mutual information, entropy, and information gain algorithms for image matching and similarity assessment, including pre-processing techniques, probability density function calculations, and performance evaluations across various image scenarios.
U-Net Conditional GAN-Based Data Augmentation in Classification Problem with Low Data Resource
- 10.2023-12.2023
- Outline
  - Modified an innovative data augmentation technique using conditional Generative Adversarial Networks (cGANs) to address low data resource challenges in medical image classification.
- Key Responsibility
  - Designed and implemented a U-Net based cGAN architecture for generating synthetic medical images, integrating it with classification models (ResNet, DenseNet) to enhance performance on datasets including ChestXray8, LiTS, NCT-CRC-HE-100K, and BreastUltra.
Precision Area Control and Line Crossing Alerts based on YOLOv8
- 11.2023-12.2023
- Outline
  - Developed an advanced real-time detection system for traffic monitoring and human tracking applications on certain area and lines.
- Key Responsibility
  - Implemented a YOLOv8-based detection system with custom zone counting and cross line detection functionalities, adapting and fine-tuning the COCO-trained model to optimize performance for specific traffic and human detection requirements.
HuBMAP + HPA - Hacking the Human Body (Kaggle Competition)
- 07.2022-10.2022
- Outline
  - Participated in a Kaggle competition focused on identifying and segmenting functional tissue units (FTUs) across five human organs using tissue section images.
- Key Responsibility
  - Developed a semantic segmentation model using ASPP and FPN for feature extraction, implementing model fusion techniques to enhance accuracy and reduce complexity, achieving a public score of 0.79 on Kaggle.
- Achievements
  - Won a bronze medal in the competition.
OpenGL My World: Interactive 3D Environment
- 04.2024-05.2024
- GITHUB
- Key Features
  - Developed an immersive 3D world using OpenGL with dynamic object tracking and interaction
  - Implemented first-person movement, diverse textures, and detailed building structures
- Technical Achievements
  - Optimized performance for smooth rendering and interaction
  - Implemented collision detection, random object generation, and gravitational physics
  - Integrated skybox for enhanced visual immersion
  - Developed robust user input handling and debugging systems
BCI Signal Processing
- 12.2023-02.2024
- Main
  - Utilize transfer learning on the “efficientnet” to classify six kinds of harmful brain activities based on EEG signal, and use both the semantic data signal and SWIN transformer to make the prediction.
  - Add new noise reduction methods to deal with the accident pulse, and finish the competition of HMS on Kaggle and the database obtains a high score; Works on this project will continue.
Compiler Construction Development based on C
- 09.2023-01.2024
- GITHUB
- Main
  - Constructed a new compiler in C in 3 phases: lexical analysis, syntax analysis and semantic analysis. Implemented a C-based compiler with a DFA lexer, AVL tree symbol table, a parsing table for shift/reduce operations, and Hindley-Milner type checking with β-reduction.

Early Projects

Non-chordal Music Generation
- 10.2022-11.2022
- Main
  - Designed and implemented a non-chordal music generation system using Bi-LSTM. Provided two ways for generating the non-chordal music, Auto-generation and Continuation Generation. Employed temperature sampling and designed lexical lists to map the corpus for digital storage.
Network Communication Software
- 06.2023
- GITHUB
- Main
  - Developed a network communication software using C++ with QT for the GUI, featuring a multi-threaded server and client for data transmission, and MySQL for data storage.
Software of Film Analysis, Prediction and Auto-arrangement for Theatre
- 05.2023-06.2023
- Main
  - Developed a software using QT and MySQL for film analysis, prediction, and auto-scheduling, featuring deep learning for data analysis and multiple visualization methods.
Designed Database for Medical Donation and Web Processing
- 10.2022-12.2022
- GITHUB
- Main
  - Created a web-based donation platform that aims to facilitate donations to poverty and disaster-affected areas worldwide.
  - Designed a relational database for a web-based donation platform using MySQL, focusing on entities such as users, beneficiaries, donations, and comments, with a front-end implemented in Bootstrap.
Webpage and Database Design for Book Purchase and Exchange Store
- 05.2022-06.2022
- GITHUB
- Main
  - Developed a comprehensive book platform allowing users to purchase and exchange books, with the entire system self-developed.
Library Lending System
- 05.2022-06.2022
- GITHUB
- Main
  - Developed a Java-based library book lending system with a command-line interface, featuring user management, book tracking, and error handling, structured with interfaces and abstract classes.

Skills

Computer Skills
- Programming Languages: Python, C, C++, PHP, Java, Bash, LaTeX
- Deep Learning Frameworks: Pytorch, TensorFlow, Scikit-learn
- Web Design: HTML, CSS, JavaScript; Database Design: MySQL
Language Skills
- Chinese (Native)
- English (Proficient)
- Japanese (Average)
Hobbies
- Web building, Construction of IoT, e.g. telecontrol; bot chat, Fine-tuning language models
- Archery

Jiecheng Liao