Beilong Tang

I’m Beilong Tang, a senior Undergraduate student from Duke Kunshan University, majoring in Applied Mathematics and Computational Sciences/Computer Science. I have a strong background in machine learning, computer science, programming, and math.

I’m currently doing research on using Large Language Models to conduct Speech Separation under the supervision of Prof. Ming Li. Previously, I did research related to Federated Learning under the supervision of Prof. Bing Luo.

My research interests are in Deep Learning, Signal Processing, Federated Learning, IoT. I’m currently looking for PhD Positions related to these fields.

For technical blog, please refer here.

News

Mar 12, 2025	I have accepted my offer to pursue a PhD in ECE at NCSU under the guidance of Dr. Hamid Krim! A new life chapter is about to begin!
Nov 01, 2024	I’m very honored to speak on behalf of DKU students at the Donor Appreciation Dinner.
Sep 15, 2024	I submitted my first first-author paper TSELM: Target Speaker Extraction using Discrete Tokens and Language Models to ICASSP 2025
Aug 15, 2024	Our paper FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics is accepted by ACM MobiHoc 2024

Latest posts

Dec 02, 2024	SLT Conference
Nov 01, 2024	Read source code
Sep 29, 2024	Welcome to my blog!

Selected Publications

Preprint

TSELM: Target Speaker Extraction using Discrete Tokens and Language Models

Beilong Tang, Bang Zeng, and Ming Li

(Submitted to ICASSP 2025) arXiv preprint arXiv:2409.07841, 2024

arXiv Bib Code

@article{tang2024tselm,
  title = {TSELM: Target Speaker Extraction using Discrete Tokens and Language Models},
  author = {Tang, Beilong and Zeng, Bang and Li, Ming},
  journal = {(Submitted to ICASSP 2025) arXiv preprint arXiv:2409.07841},
  year = {2024},
}

INFOCOM Demo

Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS

Sichang He, Beilong Tang, Boyan Zhang, and 4 more authors

In IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2024

arXiv Bib Code

@inproceedings{FedKit,
  author = {He, Sichang and Tang, Beilong and Zhang, Boyan and Shao, Jiaoqi and Ouyang, Xiaomin and Nugraha, Daniel Nata and Luo, Bing},
  booktitle = {IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},
  title = {Fedkit: Enabling Cross-Platform Federated Learning for Android and iOS},
  year = {2024},
  volume = {},
  number = {},
  pages = {1-2},
  keywords = {Training;Data analysis;Federated learning;Conferences;Computational modeling;Pipelines;Production},
  doi = {10.1109/INFOCOMWKSHPS61880.2024.10620662},
}

MobiHoc Demo

FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning & Analytics

Jiaxiang Geng, Beilong Tang, Boyan Zhang, and 2 more authors

ACM MobiHoc, 2024

arXiv Bib

@article{geng2024fedcampus,
  title = {FedCampus: A Real-world Privacy-preserving Mobile Application for Smart Campus via Federated Learning \& Analytics},
  author = {Geng, Jiaxiang and Tang, Beilong and Zhang, Boyan and Shao, Jiaqi and Luo, Bing},
  journal = {ACM MobiHoc},
  year = {2024},
}