Tianyi (Bruce) Chen
Introduction:
Skills:
- Python (machine learning (CV), data processing)
- LateX writing (overleaf: science journal)
- R program (data processing)
- Linux OS (Server)
- C program (IoT programming)
- Web programming (HTML, CSS, JavaScript) with GitHub
- Verilog programming on both Xilinx and Intel FPGA
- Circuit board design
Research: Google Scholar
Tianyi Chen, Ian Philippi, Quoc Bao Phan, et al. High-accuracy fine-tuned vision transformer model for diagnosing COVID-19 from chest X-ray images. TechRxiv. January 02, 2024. (Preprint)
Lab:
Project Experience:
AI-Telehealth Part-II (2024, NAU, Senior, US)
Topic: Vision Transformer, Convolutional Neural Network, Post-Quantum Cryptography, Kyber, Visualization
Continuing the Part-I of AI-Telehealth project, my paper was rejected by the Biosensors and Bioelectronics: X because of "Can't find reviewers (free of publication when we submitted)", which was little frustrated to us. Later Dr. Tuy searched for another Journal to publish. After several revisions, this article is officially accepted and published at https://doi.org/10.1016/j.health.2024.100332, where I served as the only first author. Also, after submitting the revised article, I implemented the optimized model online to open chest X-ray COVID-19 diagnosis service with 95.79% in four-class classification. At the same time, the other group member Ian and I work on applying the post-quantum kyber cryptography in image encryption and decryption, designing and simulating a local AI-Telehealth system, integrated with the optimized model.
I have to say, for the small number of classifications (such as 4 in this research), the fine-tuning of hyperparameters and utilization of special methods to avoid bias is more important than searching for new models, since our experiments show that each predominant model demonstrates similar accuracy performance.
AI-Telehealth Part-I (2023, NAU, Senior, US)
Topic: Image Classification, Vision Transformer
In this project, I write my first paper (preprint), which is about research in more accuracy and efficient computer vision model in classifying chest X-rays about COVID-19. Served as the leader of this project, my task is experimenting and training different pre-trained model structures with fine-tuning training configurations and then modifying the hyperparameters and structures of the selected model, under the supervision and guidance of Dr. Tuy Nguyen and his Ph.D student Bao (under Digital Systems Design Laboratory). Our partial but excellent work make us win the third prize in the NAU EGR-FEST II presentation. If you're interested in this project, visit
here for more information.
FPGA Alarm System (2022, CQUPT, Junior, CN)
Topic: Embedded System, Internet of Things
This is the beginning of my project which happens in an FPGA design race hold by an Intel Innovation Center of China authorized company. I lead team win the third prize. I am in charge of the whole designing, where my members write the documents and record presentations. As shown in the left, this simple designed system can count time using built-in clock, receive information from sensors (temperature and light), display the information on the website (through ESP8266 WiFi block), and alert with set conditions. For more information, please click here (blog).
Education:
Place | Duration | Degree | Major | Status |
---|---|---|---|---|
Chonqing University of Posts and Telecommunications | Sep,2020 - June,2023 | Bachelor of Science | Eletronic Information Engineering | In Progress |
Northern Arizona University | Aug,2023 - May,2024 | Computer Engineering | For more information please visit my personal site. |
Life:
Contact Info:
GitHub: https://github.com/TyBruceChen
https://tychence.wordpress.com/ Personal Site