Schedule

The Core Value of the Student Seminars at Florida State University is to foster a seminar series as a dynamic intellectual hub dedicated to introducing and advancing the cutting-edge of computer science for the students at the academic community of FSU, with a particular focus on artificial intelligence, machine learning, and related emerging technologies. This regular seminar serves as a platform for faculty and students to share groundbreaking discoveries, innovative methodologies, and critical insights across the rapidly evolving landscape of computational sciences. By promoting interdisciplinary dialogue and collaboration, this seminar aims to catalyze innovation and cross-pollination of ideas spanning various domains within and beyond traditional computer science boundaries. It offers an essential opportunity for participants to engage with the latest advancements, challenge conventional paradigms, and inspire novel research directions.

2025

  • 11/04/2025 - Research Paper Presentation (by Lin Jiang): Uncertainty-aware Predict-Then-Optimize Framework for Equitable Post-Disaster Power Restoration [20251104_Video]
  • 10/28/2025 - Research Paper Presentation (by Xueqi Cheng): SOMA: Efficient Multi-turn LLM Serving via Small Langugae Model [20251028_Video]
  • 10/21/2025 - Research Paper Presentation (by Bolin Shen): CREDIT: Certified Defense of Deep Neural Networks against Model Extraction Attacks [20251021_Video]
  • 10/14/2025 - Research Paper Presentation (by Yanfeng Zhao): Textro: A Prototyping Toolkit for Solderless and Chipless Smart Textile Interfaces [20251014_Video]
  • [Invited Talk] 04/04/2025 - Research Paper Presentation (by Prof. Ahana Roy Choudhury ): Applications of Deep Learning in Medical Imaging.
  • 04/01/2025 - Research Paper Presentation (by Yichao Wang): Wi-Mesh: A WiFi Vision-based Approach for 3D Human Mesh Construction [20250401_Paper]
  • 03/25/2025 - Research Paper Presentation (by Debanjan Goswami): Active Learning for Video Classification with Frame Level Queries [20250325_Paper]
  • 03/18/2025 - Research Paper Presentation (by Liting Zhang): SCCNAInfer: a robust and accurate tool to infer the absolute copy number on scDNA-seq data
  • 02/25/2025 - Research Paper Presentation (by Bofan Li): Unlocking Vital Signs Monitoring for Healthcare and Security
  • 02/18/2025 - Research Paper Presentation (by Bolin Shen): AGDN: Solving Traveling Salesman Problem with Anisotropic Multi-hop Attention Graph Diffusion Network [20250218_Paper]
  • 02/11/2025 - Research Paper Presentation (by Junyuan "Jason" Hong): Harmonizing, Understanding, and Deploying Ethical AI [20250211_Paper]

2024

Target Audience

Anyone who are in the research of computer science, especially artificial intelligence, machine learning, and data mining. All students and faculty members are warmly welcomed to attend. We prepare Free Lunch and drink during every seminar for you. Faculty members, Students, and Staffs within Department of Computer Science will receive regular Email notification about the Seminar. If you are outside computer science and also wish to receive Email notification about the seminar, please contact Lincan (Kelsey) Li via Email.

Committee Members

Yushun Dong

Dr. Yushun Dong is an assistant professor with the Computer Science Department at Florida State University. He received Ph.D. degree in Electrical and Computer Engineering at the University of Virginia in 2024. His research interest mainly lies in achieving responsible AI to further advance social good such as facilitating inclusive decision-making. He has abundant research works under related topics with a particular focus on relational data, including 30+ published research papers in the areas of explainability, algorithmic fairness, AI Security, and AI/ML + X (Applications). He is the recipient of multiple prestigious awards including Louis T. Rader Graduate Research Award, Endowed Fellowship, and Best Poster at Doctoral Forum of SDM 2022.

Shangqian Gao

Dr. Gao joined the Department of Computer Science as an assistant professor in the fall of 2024. He earned his Ph.D. from the University of Pittsburgh in 2024, under the guidance of Prof. Heng Huang. Before his academic appointment, Dr. Gao spent a year as a research scientist at Samsung Research America (SRA), where his work on improving the efficiency of Large Language Models received the Presidential Award from SRA. His research interests span a broad range of topics in AI and machine learning, including efficient machine learning, cross-modal learning, reinforcement learning, and optimization methods. Recently, his research has focused on solving constrained optimization problems to reduce the size of large models, such as Large Language Models, Vision-Language models, and Diffusion models.

Shibo Li

Dr. Shibo Li is an assistant professor with the Computer Science Department at Florida State University. He obtained his Ph.D. degree in Computer Science from The Kahlert School of Computing (SoC) at The University of Utah. His primary research area, AI for Science, integrates physical system analysis with machine learning methodologies. Computational physics, developed over centuries, is essential for understanding the universe and creating new technologies. Meanwhile, AI has revolutionized many sectors. Though these fields may seem distinct, they are complementary: physical insights improve data-driven methods' efficacy, and data-driven methods capture physical laws flexibly. Leveraging abundant data, these methods provide statistical insights, augment traditional research, and offer efficient computing infrastructure for enhanced efficiency.

Xin Liu

Dr. Xin Liu is an Assistant Professor at FSU Computer Science starting from Fall 2024. Prior to this, he served for two years as a Postdoctoral Scholar at The Ohio State University. He earned his Ph.D. in Computer Engineering from the University of Maryland, Baltimore County, in 2022. Dr. Liu’s research focuses on leveraging machine learning to enhance the performance and security of next-generation wireless networks, with a particular emphasis on IoT, 6G, and autonomous vehicles. He has co-authored 15 papers in top-tier conferences, including SIGCOMM, NSDI, and USENIX Security. Beyond research, Dr. Liu is deeply committed to mentoring and community engagement. He co-chaired the AI-EDGE SPARKS initiative and has mentored numerous undergraduate research, fostering interdisciplinary collaboration and innovation in wireless networking and AI.

Mulong Luo

Dr. Mulong Luo is an Assistant Professor in Department of Computer Science at Florida State University, where he leads the Trustworthy Machines & Learning Lab (TML²). He earned his Ph.D. in Computer Engineering from Cornell University in 2023. Previously, he received an M.S. degree from UC San Diego and a B.S. degree from Peking University. His work spans trustworthy machine learning and security, and he has been recognized with honors such as the CPS Rising Star Award and a Top Picks in Hardware and Embedded Security finalist distinction. He actively serves the research community as a proposal reviewer for NSF SaTC and a technical program committee member for top venues including ACM CCS, IEEE S&P, and USENIX Security.

Yifang Wang

Yifang Wang is a tenure-track Assistant Professor in the Department of Computer Science at Florida State University. Her research lies at the intersection of Data Visualization, Human-AI Collaboration, and Human-Computer Interaction, with a focus on advancing scientific understanding and supporting decision-making in studies of human behavior and societal dynamics. Her work has been published in top-tier venues such as Nature, IEEE VIS, IEEE TVCG, and ACM CHI. Before joining FSU, she was a Post-Doctoral Fellow at Kellogg School of Management, Northwestern University. She obtained Ph.D. degree in Department of Computer Science and Engineering from The Hong Kong University of Science and Technology.

Yang Liu

Yang Liu is an Assistant Professor in the Department of Computer Science at Florida State University. Her research focuses on wearable sensing, mobile computing, and artificial intelligence, with an emphasis on developing human-centered mobile and wearable systems. Yang Liu received her Ph.D. in Computer Science from City University of Hong Kong and her bachelor’s degree in Software Engineering from Xi'an Jiaotong University. Before joining FSU, she was an Affiliated Lecturer in the Department of Computer Science and Technology at the University of Cambridge. Her research has been published in top-tier venues such as ACM MobiSys, SenSys, IMWUT/UbiComp, CHI, and IEEE INFOCOM.

Organization Committee

Lincan (Kelsey) Li

Lincan (Kelsey) Li is a 2nd-year PhD student in Computer Science at Florida State University, advised by Dr. Yushun Dong in RAI Lab. Her research centers on Trustworthy AI, Large Language Model (LLM) Security, and Spatial-Temporal Intelligence. Lincan is also deeply interested in leveraging spatial-temporal deep learning and LLM-based approaches for AI for Science, including climate and natural disaster forecasting. Lincan's research has led to 15+ publications in top venues and journals such as KDD 26', KDD 25', SIGSPATIAL 25', ICASSP 24', etc, including a Best Paper Award at ACM SIGSPATIAL 2025. She have also contributed to open-source projects like TyphoFormer, STG-Mamba, and PyGIP, and served as the lead presenter at KDD 2025 tutorial. Beyond research, Lincan actively serve as a reviewer for top-tier AI conferences/Journals.

Yanfeng Zhao

Yanfeng Zhao is a second-year PhD student from Department of Computer Science at Florida State University, where he is advised by Dr. Te-yen Wu. Yanfeng's research interest includes human-computer interaction, wearable technology and ubiquitous computing. Yanfeng's recent work focus on smart textile applications in real-world scenarios.

Contact

Powered by Dr. Yushun Dong (yd24f@fsu.edu).