Vu Le

I'm a first year Computer Science PhD student in the University of Massachusetts Amherst (UMass), advised by VP Nguyen . I also work at Berkeley Lab to enhance QubiC (Quantum Bit Control), an open-source FPGA-based control and measurement system for superconducting quantum bits.

I broadly intertested in accelerated computing, machine learning, and systems. My research focuses on leveraging machine learning to study readout fidelity, mid-circuit measurement and state discrimination while exploring efficient computer architectures for improved scalability and performance.

My CV will be available upon request.

Contact:
  • Personal email: vule20.cs AT gmail [DOT] com
  • UMass email: vdle AT cs.umass [DOT] edu
  • Berkeley Lab email: vule AT lbl [DOT] gov

Scholar  /  Github  /  LinkedIn  /  Blogs

profile photo

News

  • 03/2025: Our new paper is accepted at ACM MobiSys 2025!
  • 02/2025: I’m honored to receive the James Kurose Scholarship in Computer Science.
  • 01/2025: I open sourced my GitHub repository and tutorials for the QubiC quantum control system
  • 12/2024: I officially become a research affiliate with Berkeley Lab.
  • 09/2024: My new academic website with the vule.us domain is live now.
  • 09/2024: One paper accepted at ACM SenSys 2024.
  • 09/2024: I joined University of Massachusetts Amherst, USA as a PhD student.
  • 01-04/2024: I received multiple offers to pursue my CS PhD in the USA.
  • 10/2023: One paper accepted at IEEE/CVF WACV.
  • 06/2022: I graduated with a bachelor degree from Vietnam National University, Hanoi.

Selected Research

I'm interested in quantum computing, computer architecture, deep learning, and scalable networked systems. Most of my research is about computer systems, systems and computer vision applications. Some papers are highlighted.

blind-date MagicStream: Bandwidth-conserving Immersive Telepresence via Semantic Communication
Ruizhi Cheng, Nan Wu, Vu Le, Eugene Chai, Matteo Varvello , Bo Han
ACM SenSys 2024,   (A* conference)
project page  /  paper

MagicStream, a first-of-its-kind semantic-driven immersive telepresence system that effectively extracts and delivers compact semantic details of captured 3D representation of users, instead of traditional bit-by-bit communication of raw content.

blind-date Fast and Interpretable Face Identification for Out-Of-Distribution Data Using Vision Transformers
Hai Phan, Cindy Le, Vu Le, Yihui He, Anh Totti Nguyen
CVF/WACV 2024   (A conference)
project page  /  paper  /  code  /  poster  /  presentation

Using vision transformers for out-of-distribution data face identification, runs twice faster while achieving comparable performance with the state of the art DeepFace-EMD model.

Miscellanea

Apart from being a researcher, I'm also an experienced software and devops engineer. I enjoy building scalable backend systems that can handle large traffics. On top of that

In addition, I'm also into:

  • Photography: Sony A6400 and a bunch of sigma and sony lenses!
  • Counter Strike 1.6, GTA5 and Age of Empire!
  • Travel
  • Hiking

Web Traffic

Thanks Jon Barron for the website template.