Dr. Grigory Fedyukovich has a paper accepted at PLDI
Published: | 1:24 pm | Posted in: News
Dr. Grigory Fedyukovich has a paper accepted at the 2025 ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI). PLDI is a flagship conference in programming languages. The paper, titled “Exact Loop Bound Analysis”, is authored by Dr. Grigory Fedyukovich and his PhD student Daniel Riley. The paper presents ELBA, a novel tool for […]
Dr. Yushun Dong has two papers accepted at leading conferences in artificial intelligence and machine learning
Published: | 10:33 am | Posted in: News
The first paper, “Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective,” led by Dr. Yushun Dong, is accepted by International Conference on Learning Representations (ICLR 2025) and will be presented during the conference on April 24–28, 2025.
Dr. Shangqian Gao Has Two Papers Got Accepted by Top Conference
Published: | 10:32 am | Posted in: News
Dr. Shangqian Gao of Florida State University has a paper accepted by the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) and coauthored a paper accepted by the 38th Conference on Neural Information Processing Systems (NeurIPS 2024).
Towards Smarter, Healthier, and Secure Lives Through Intelligent Wearable Sensing
Published: | 3:56 pm | Posted in: Events
Speaker: Yang Liu
Date: Apr 4, 11:45am-12:45pm
Abstract: In today’s technology-driven world, the ubiquity of wearable devices offers unparalleled opportunities to monitor and enhance human well-being. However, a substantial gap remains in their ability to intuitively understand and respond to individual needs.
Deploying Web Honeypots to Evaluate the Efficacy of Online Systems Against Phishing and Fraud Attacks
Published: | 10:02 am | Posted in: Events
Speaker: Bhupendra Acharya
Date: Mar 27, 11:45am-12:45pm
Abstract: Phishing and fraud attacks remain the predominant class of social engineering attacks despite two decades of their existence. Most cyberattacks begin with a social engineering attack, finding the weakness in human fallibilities.
Dr. Kai Zhao has a paper accepted at The 2025 ACM SIGMOD International Conference on Management of Data.
Published: | 3:24 pm | Posted in: News
Dr. Kai Zhao has a paper accepted at The 2025 ACM SIGMOD International Conference on Management of Data. SIGMOD is a flagship conference in data management. The paper, titled “LCP: Enhancing Scientific Data Management with Lossy Compression for Particles,” is authored by Dr. Kai Zhao, his PhD student Longtao Zhang, Ruoyu Li, and collaborators from several universities and national […]
Dr. An-I Andy Wang has a paper accepted by the 23rd USENIX Conference on File and Storage Technologies (USENIX FAST)
Published: | 3:22 pm | Posted in: News
Dr. An-I Andy Wang has a paper accepted by the 23rd USENIX Conference on File and Storage Technologies (USENIX FAST), the flagship conference on file systems and storage. The paper is titled “Silhouette: Leveraging Consistency Mechanisms to Detect Bugs in Persistent Memory-Based File Systems” and was coauthored by Dr. Ashvin Goel at the University of […]
Artificial General Intelligence for Society
Published: | 11:04 am | Posted in: Events
Speaker: Tianming Liu
Date: Feb 21, 11:45am-12:45pm
Abstract: Multimodal large language models (LLMs), foundation models (FMs), and generative artificial intelligence (GenAI) have transformed many domains of our society.
Building Adaptable and Reliable AI with Probabilistic Modeling
Published: | 12:44 pm | Posted in: Events
Speaker: Jake Snell
Date: Feb 19, 11:45am-12:45pm
Abstract: How can we build AI systems that produce more reliable outputs while consuming less data? In this talk, I will show how to answer this question by combining deep learning with tools from probabilistic modeling.
AI for Actionable Healthcare: Treatment Effect Estimation on Real-world Patient Data
Published: | 11:11 am | Posted in: Events
Speaker: Ruoqi Liu
Date: Feb 17, 11:45am-12:45pm
Abstract: Estimating causal effects from observational data is a fundamental problem in many fields that face challenges (e.g., expensive, time-consuming, or even unethical) in running randomized control trials.