Tianyi (Bruce) Chen


Introduction:

My name is Tianyi Chen, currently studying Computer Engineering (BS) at Northern Arizona University (transferred) and previously studied Electronic Information Engineering (BS) at Chongqing University of Posts and Telecommunications. My primary academic focus is on machine learning, a field that deeply fascinates me. In my leisure time, I engage in small-scale IoT projects, where I take great pleasure in combining hardware and software to build practical and functional devices. Additionally, I have a passion for video games and animations. Aside from Chinese, I can speak English and Japanese.

This is my Resume



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, Linh Nguyen, Ngoc Thang Bui, Carlo daCunha, and Tuy Tan Nguyen, "A Vision Transformer Machine Learning Model for COVID-19 Diagnosis Using Chest X-Ray Images," Healthcare Analytics, vol. 5, pp. 100332, Jun. 2024. (Journal Link)
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:

Digital Systems Design Laboratory of Northern Arizona University

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.

This is the picture of the poster presentation of AI-Telehealth Phase-II

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.

This is the picture of winning third prize in NAU Engineering Fest

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).

This is the picture of FPGA alarm platform project

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:

Life in US (2023 Aug - 2024 May, Northern Arizona University, BS)

Life in CN

Contact Info:

tc922@nau.edu/ty_bruce.chen@outlook.com/tianyi.bruce.chen@gmail.com
GitHub: https://github.com/TyBruceChen
https://tychence.wordpress.com/ Personal Site