Bio

I am a first-year Ph.D. student in Computer Engineering at Boston University. Prior to BU, I received my M.Phil. degree (2023) from City University of Hong Kong, supervised by Prof. Shiqi Wang, and B.Eng. degree (2020) from Northeast Electric Power University, supervised by Prof. Yimin Hou, Prof. Jinglei Lv, and Prof. Yang Li.
During my studies, I interned at the Computer Vision team of Samsung Research, advised by Dr. Hui Zhang, and the Medical Natural Language Processing team of Philips Research, advised by Dr. Shuang Zhou. In 2017, I attended a summer school at University of California, Irvine.
𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝘀: I put all my effort into Foundation Models, e.g., Large Pre-trained Language Models, Trustworthy AI, and Computer Vision.
here
Some of my presentations and resources can be found
here
𝐖𝐡𝐚𝐭 𝐢𝐬 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐬𝐮𝐫𝐩𝐫𝐢𝐬𝐢𝐧𝐠 𝐟𝐢𝐧𝐝𝐢𝐧𝐠 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡?
𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 - Artificial Intelligence (AI)
AI In the 2020s And Beyond
𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 - Graph Neural Network (GNN)
Graph Convolutional Neural Networks
Attention-based BiLSTM-GCN
Dynamic Graph Convolutional Neural Networks
𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 - Natural Language Processing (NLP)
Foundation Models for Sequential Decision Making
Factual Associations in LLMs
Graph Matching
Sub-word BPE Algorithm for NMT
Concept Matching for Medical Terms
𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 - Computer Vision (CV)
Image Quality Assessment and Perceptual Optimization
Deep Learning Models Compression and Acceleration
3D Human Pose Estimation and Human Body Reconstruction
YOLO Object Detection
𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 - Tutorials and Useful Coding Scripts
Usage of Cloud Server and Setting-up
Python Environment Setting-up
TensorFlow for Deep Learning
Crypto Currency Return and Price Prediction with Machine Learning
Big Data Parallel Processing by PySpark and Horovod Distributed Deep Learning
Download Papers from Sci-Hub via Unix Shell
Retrieve and Download Google Scholar Citation Papers
Homepage Shows Real-time Google Scholar Citations through PHP
Dynamic (Ajax) Web Crawler in Python
Deploy Machine Learning and Deep Learning Models with Flask and Docker as Web Applications
Convert PowerPoint (PPT) to PDF with Animations
Download YouTube Videos with Unlimited Speed via youtube-dl
Compile Hadoop, Install Redis, Flink, Kafka, ZooKepper, and Spark on macOS
Hadoop HDFS Data
Hive Configuration on macOS
Spark Configuration on macOS
Hadoop Configuration on Linux
Hive Configuration on Linux
Storm Configuration on Linux
Compiling Kaldi ASR on macOS
Server SSH and SCP Scripts
Shell Tmux Usage
Go Programming Scripts
Julia Programming Scripts
Python Conda Scripts
Python PyPI Package Building Scripts
npm Scripts
R Packages
SQL Programming Scripts
CSV Shell Scripts
macOS Homebrew Scripts
Install LaTeX on Linux
LaTeX Package Installation on macOS and EPS to PDF
LaTeX Useful Newcommands
LaTeX IEEE Conference Useful Scripts
LaTeX IEEE Trans Useful Scripts
Matlab GPU Acceleration Tricks
Run Multiple Python Scripts via Shell sh
Build PyTorch (CPU) from Source on macOS
PyTorch Control the Usage of CPU Resources
Build TensorFlow (CPU) from Source on macOS
Build TensorFlow (CPU) from Source on Linux
Build TensorFlow (GPU) from Source on Linux
Docker Basic Commands
Vim Basic Commands
Git Basic Commands
M.Phil. Thesis (LaTeX), City University of Hong Kong
𝐄𝐱𝐜𝐞𝐥𝐥𝐞𝐧𝐭 𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧
On the Inductive Bias of Language Modeling | Oral Presentation (Tatsunori B. Hashimoto)
智能制造优化调度及展望
𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐁𝐨𝐨𝐤𝐬
Convex Optimization (Stephen Boyd and Lieven Vandenberghe)
Nonlinear Programming (Dimitri P. Bertsekas)
Foundation Models for Natural Language Processing Pre-trained Language Models Integrating Media (Gerhard Paaß and Sven Giesselbach)
Pattern Recognition and Machine Learning (Christopher Bishop)
Reinforcement Learning: An Introduction (Richard S. Sutton and Andrew G. Barto)
Digital Image Processing (Rafael C. Gonzalez and Richard E. Woods)
Multiple View Geometry in Computer Vision (Richard Hartley and Andrew Zisserman)
Foundation Models for Natural Language Processing (Gerhard Paaß and Sven Giesselbach)
Graph Representation Learning (William L. Hamilton)
Computer Systems: A Programmer's Perspective (Randal E. Bryant and David R. O'Hallaron)
Computer Organization and Design: The Hardware/Software Interface (David A. Patterson and John L. Hennessy)
𝐀𝐜𝐚𝐝𝐞𝐦𝐢𝐜 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬
Writing and Technical Presentations by Prof. Ayse Coskun
The Most Common Habits from more than 200 English Papers written by Graduate Chinese Engineering Students by Felicia Brittman
How to Write Good Research Articles by Prof. Xiaohua Jia
业余做研究的经验 by Dr. Yuandong Tian
What is Research and How to do it? by Prof. Yi Ma
How to write a good CVPR submission? by Prof. Bill Freeman
How to Be a Responsible Reviewer by Prof. Jiebo Luo
How to Use the IEEEtran LaTeX Class
IEEE Editing Mathematics Guide (Standard)
IEEE Math Typesetting Guide (LaTeX)
IEEE Formula Comma and Period
IEEE Reference Guide (2021)
IEEE Citation Examples
Science and Engineering Journal Abbreviations
Standard abbreviations used in the IEEE Reference list
IEEE Editorial Style Manual (2021)
LaTeX Mathematical Symbols
Writing Mathematical Formulas in Markdown
InCites Journal Citation Reports (2021)
中国计算机学会推荐国际学术会议和期刊目录 (2019)
中国科学院SCI分区表 (2019)
中国科学院国际期刊预警名单
Python编码风格与规范 @ Tencent
C++编码风格与规范 @ Tencent
JavaScript编码风格与规范 @ Tencent
Go编码风格与规范 @ Tencent
CVPR Paper, Supplementary Materials, and Rebuttal LaTeX Templates
PowerPoint (PPT) and LaTeX Demos of Academic Posters
National Science Foundation (NSF) Proposal & Award Policies & Procedures Guide (PAPPG)
National Science Foundation (NSF) Biographical Sketch
NSF's Proposal Preparation & Submission Guidelines
ACL Fellow Nomination Form
CityU AP Promotion
RICE AP Offer
𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐝 𝐑𝐞𝐚𝐝𝐢𝐧𝐠𝐬
文章千古事, 得失寸心知 by Prof. Song-Chun Zhu
Statement of Purpose by Dr. Kai-Fu Lee
Dartmouth Summer Project on Artificial Intelligence (1956)
Turing Test (1950) by Alan Mathison Turing
The Bitter Lesson from 70 years of AI research by Richard Sutton
AI创业江湖里的师徒帮
清华大学计算机系与人工智能40年
Academic Achievements of Prof. Richard Yi-Da Xu
Brief Bio of Prof. Richard Yi-Da Xu
Prompt Template Engineering Experiment by Prof. Edward Chang
心灵之旅 by Prof. Edward Chang
生命是什么? by Prof. Edward Chang
读博那些事儿 by Prof. Yiqing Xu
The Ph.D. Grind by Prof. Philip J. Guo
You and Your Research by Prof. Richard Hamming
You’ve Got to Find What You Love by Steve Jobs
How to Be a Successful Ph.D. CS Student by Prof. Mark Dredze and Prof. Hanna M. Wallach
A Brief History of Computational Vision by Prof. Song-Chun Zhu
Artificial Intelligence by Prof. Song-Chun Zhu
Ph.D. in Computer Vision Summary by Prof. Mike Shou
博士这五年 by Dr. Mu Li
博士五年总结系列 by Dr. Yuandong Tian
What My PhD Was Like by Prof. Jean Yang
CVPR之感想 by Dr. Yuandong Tian
上海交通大学学生生存手册
李琳山教授个人数位典藏
Randy Pausch Last Lecture: Achieving Your Childhood Dreams
Email: shuyuej@ieee.org
Scholar
GitHub
News
Publications
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No-reference Image Quality Assessment via Non-local Dependency Modeling
Shuyue Jia, Dingquan Li, Shiqi Wang
IEEE 24th International Workshop on Multimedia Signal Processing (IEEE MMSP'22)
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A no-reference image quality assessment method based on non-local features learned by a graph neural network (GNN). The proposed quality assessment framework is rooted in the view that the human visual system perceives image quality with long-dependency constructed among different regions, inspiring us to explore the non-local interactions in quality prediction.
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GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals
Shuyue Jia, Yimin Hou, Xiangmin Lun, Yan Shi, Yang Li, Rui Zeng, Jinglei Lv
IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS)
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Traditional works classify EEG signals without considering the topological relationship among electrodes. Thus, a graph convolutional neural network is presented while cooperating with the functional topological relationship of electrodes.
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Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition
Yimin Hou, Shuyue Jia (Corresponding Author), Xiangmin Lun, Shu Zhang, Jinglei Lv
Frontiers in Bioengineering and Biotechnology
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This paper presents a novel deep learning approach designed toward both remarkably accurate and responsive motor imagery (MI) recognition based on scalp EEG. Bidirectional long short-term memory (BiLSTM) with the attention mechanism is employed, and the graph convolutional neural network (GCN) promotes the decoding performance by cooperating with the topological structure of features.
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A Novel Approach of Decoding EEG Four-Class Motor Imagery Tasks via Scout ESI and CNN
Yimin Hou, Lu Zhou, Shuyue Jia, Xiangmin Lun
Journal of Neural Engineering
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We presented a novel approach that could potentially improve the current stroke rehabilitation strategies by implementing a deep learning approach for an Electroencephalogram (EEG) based on MI Brain-Computer Interface System.
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Constructed 6 convolutional layers, 2 max-pooling layers, and 3 FC layers CNNs for four-class motor imagery classification through TensorFlow, with 50% dropout (spatial dropout after every Conv layer and regular dropout for FC layers) – 11.44% accuracy improvement, batch normalization (BN) – 10.15% improvement, and Short-cut Connection – 1.76% improvement to prevent overfitting, and achieved SOTA results: 94.50% accuracy on scout R5, 94.54% at subject level, and 96% for left fist prediction.
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Took charge of DNNs design, including methods comparisons, such as MLPs, CNNs, RNNs, and LSTMs, classification results calculations, and programming. 10 and 14 subjects’ data were utilized (19,320 and 27,048 samples in the experiments)
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Benchmark Dataset: EEG Motor Movement/Imagery Dataset.
Academic Services
- Reviewer of IEEE T-MM, IEEE T-CSVT, and IEEE Journal of Biomedical and Health Informatics
- Student Member of IEEE, ACM, ACL, and AAAI
Selected Awards
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CityU Top 5 Runner, City University of Hong Kong
Athlete
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Outstanding Athlete, Northeast Electric Power University
Athlete
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3000-meter Steeplechase, The 45th Northeast Electric Power University Games
The 7th Place in college
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2015 National High School Math League, China
Second Prize
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The 32nd Chinese Physics Olympiad (CPhO)
Third Prize