Vu Le

I'm a third-year Computer Science PhD student at the University of Massachusetts Amherst (UMass), working with Prof. VP Nguyen and Prof. Deepak Ganesan. I am also an affiliated PhD student at Lawrence Berkeley National Laboratory, where I work on heterogeneous computing for deep learning-based quantum state classification with sub-microsecond (1 μs) latency, hosted by Yilun Xu.

I am broadly interested in heterogeneous computing — combining AI engines, FPGAs, CPUs, and GPUs to solve computational problems with critical timing requirements. My research sits at the intersection of hardware-software co-design, real-time machine learning inference, and scalable systems for scientific and edge applications.

I am actively seeking research or industry internships in the US for Summer/Fall 2026, particularly in AI, edge computing, heterogeneous computing, and high-performance AI. Feel free to reach out!

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  /  Twitter / X  /  Photos

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News

  • 03/2025: One paper accepted at ACM QSys 2025 (in conjunction with ACM MobiSys 2025).
  • 03/2025: One paper 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.
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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 Computing Systems for Superconducting Qubits: Challenges and Opportunities
Vu Le, Neel Vora, Devanshu Brahmbhatt, Yilun Xu, Gang Huang, Phuc Nguyen
ACM QSys 2025   (in conjunction with ACM MobiSys 2025)
paper

An overview of quantum control systems for superconducting qubits, highlighting the importance of precise control for fault-tolerant quantum computing. This work emphasizes the advantages of open-source platforms and outlines key research directions, including scalable control, high-precision readout, and leakage suppression.

blind-date Detection and Tracking of Drone Swarms using LiDAR
Tasnim Azad Abir, Vu Le, Endrowednes Kuantama, Pranjol Sen Gupta, Austin Copley, Judith Dawes, Mohammad Islam, Richard Han, Phuc Nguyen
ACM MobiSys 2025,   (A* conference)
paper

LiSWARM is a low-cost LiDAR system for accurate 3D tracking and recognition of drones in large swarms. Using point cloud processing, clustering, and neural networks, it achieves up to 98% accuracy and scales to 15,000 drones—enabling applications in airspace security, drone shows, and sensitive area monitoring.

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 research, I'm an experienced software and DevOps engineer who enjoys building scalable backend systems. Outside of work, I'm an avid adventurer — I've hiked national parks across the American Southwest (Grand Canyon, Zion, Death Valley, Horseshoe Bend, Joshua Tree), hiked the White Mountains in New Hampshire, and traveled across the US with camera in hand. I shoot with a Sony A6400 and a collection of Sigma and Sony lenses. Check out my photo gallery.

Thanks Jon Barron for the website template.  ·  Polished with Claude  ·  Hosted on Cloudflare Pages  ·  Photos on Cloudflare R2