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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

About me

Posts

Future Blog Post

less than 1 minute read

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

publications

eXpressSFU: Toward Super-Scalable Video Conferencing with SmartNICs

Published in USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2026

A WebRTC SFU that offloads the media data plane — SRTP crypto, packet forwarding, and simulcast/SVC layer selection — onto the Arm cores of an NVIDIA BlueField-2 SmartNIC, cutting media-packet latency 8× and serving 3× more concurrent users than the software baseline.

Recommended citation: T. Tran, S. M. H. Hosseini, S. Kim, K. Lee, N. Bui, D. Grunwald, S. Ha. "eXpressSFU: Toward Super-Scalable Video Conferencing with SmartNICs." USENIX NSDI, 2026. https://www.usenix.org/conference/nsdi26/presentation/tran

DeepSFU: Scalable Deepfake Detection for Video Conferencing

Published in ACM SIGCOMM, 2026

Real-time deepfake detection as a native SFU service: detects deepfake onsets directly on the encoded VP9 bitstream and offloads crypto and NIC-to-GPU frame movement to a BlueField-3 DPU — ~144× lower per-frame processing latency and 26× more concurrent conferences at 95.8% precision.

Recommended citation: T. Tran, S. Ebadi, S. M. H. Hosseini, W. Shin, E. Ram, Y. Son, S. Kim, N. Bui, K. Lee, E. Keller, S. Ha. "DeepSFU: Scalable Deepfake Detection for Video Conferencing." ACM SIGCOMM, 2026. https://dl.acm.org/doi/10.1145/3789240.3829184