Weikuan Yu awarded a new grant from LLNL on Data Reduction

Published: | 8:08 am | Posted in: News

Weikuan Yu, Professor and Chair in the FSU Department of Computer Science, has been awarded a grant of $85K for research on Data Reduction for Efficient Checkpoint/Restart of LLM applications from Lawrence Livermore National Lab (LLNL). This project aims to develop data-reduction capabilities, such as compression and deduplication, for large-scale LLM checkpoints to substantially reduce […]

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Bofan Li publishes a paper on WiFi-Based Respiration Authentication in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)

Published: | 9:54 am | Posted in: Student Recognition

Bofan Li, a PhD student in the Computer Science Department, has published a paper titled “MURAL-Fi: Multi-User Respiration Authentication Leveraging WiFi” in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). This work is done under the guidance of Dr. Weikuan Yu in collaboration with Dr. Xin Liu and other colleagues. […]

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iCR: Intent-Driven Checkpoint/Restart (Mar 10)

Published: | 9:50 am | Posted in: Events

Speaker: Olga Kogiou Date: March 10, 11:45 – 12:45 pm Abstract: High Performance Computing applications have evolved from monolithic simulations to interdependent tasks that form heterogeneous workflows. These workflows rely on Checkpoint/Restart (C/R) mechanisms to enable continuity in their execution. However, the workflow heterogeneity demands adaptability from the underlying C/R solution. Our examination reveals that, […]

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ATOMIC: Attention Reallocation to Mitigate Irrelevant Context in Small Language Models (Mar 3)

Published: | 12:28 pm | Posted in: Events

Speaker: Bolin Shen Date: March 3, 11:45 – 12:45 pm Abstract: Small language models have recently gained increasing attention due to their strong cost efficiency, computational efficiency, and competitive performance across a wide range of reasoning tasks. However, when reasoning inputs contain irrelevant context, SLMS are substantially more vulnerable to distraction than large language models, […]

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Robust Machine Learning on the Edge (Feb 27)

Published: | 9:09 am | Posted in: Events

Speaker: Stratis Ioannidis Date: Feb 27, 11:15 – 12:15 pm Abstract: Adversarial robustness, i.e., the ability of a machine learning (ML) algorithm to maintain its predictive power under input perturbations, is an important property for many safety-critical applications. It is even more important in edge deployments of ML algorithms, where inference is performed in a […]

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ReAD: Reinforcement-Guided Capability Distillation (Feb 24)

Published: | 10:58 am | Posted in: Events

Speaker: Xueqi Cheng Date: Feb 24, 11:45 – 12:45 pm Abstract: Knowledge distillation (KD) compresses a large model into a smaller one that preserves the capabilities needed for a downstream task, yet existing methods assume that capabilities can be optimized independently…

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Deep Learning for 3D Scene Modeling & AI-Enhanced Healthcare (Feb 20)

Published: | 9:53 am | Posted in: Events

Speaker: Andy Duan Date: Feb 20, 11:45 – 12:45 pm Abstract: 3D scene modeling is fundamental in many applications including Virtual Reality, Augmented Reality, Autonomous Driving, Robotics, Telehealth, etc. In this talk, I will first discuss some of our recent works in 3D scene modeling including: 1) PanoDepth: a deep learning based omnidirectional depth estimation […]

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Computer Science Student Seminars (Feb 3rd – Semester End)

Published: | 1:57 pm | Posted in: Upcoming

Dear Colleagues and CS Graduate Students, We are excited to announce that our computer science Student Seminars at Florida State University are starting again this spring semester! This weekly seminar series provides a great opportunity for students to share their research, practice presentation skills, and engage with peers and faculty members. Location: Room 353, LOV […]

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Dr. Guang Wang’s Lab has two papers accepted by AAAI 2026

Published: | 10:07 am | Posted in: News

Dr. Guang Wang, Assistant Professor in the Department of Computer Science, has had two papers from his lab accepted to the 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026). The first paper titled “GeoGen: A Two-stage Coarse-to-Fine Framework for Fine-grained Synthetic Location-based Social Network Trajectory Generation”, which is led by his PhD student Rongchao […]

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