At the Security, Privacy, and Intelligence for Edge Devices (SPEED) Lab , our vision is to drive transformative research in the domain of AI, federated learning, large language models, vision-language models, cybersecurity, and multi-modality. We strive to place strong emphasis on edge intelligence, tailoring the potential of distributed computing to enable efficient decision-making. We aspire to pioneer advancements that redefine the boundaries of AI and machine learning, while ensuring the security and privacy of distributed systems. Through our interdisciplinary research, we strive to develop robust, efficient, and intelligent solutions that enhance decision-making in edge environments, driving innovation that positively impacts society in an increasingly interconnected world.
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RELEASED A COMPREHENSIVE SURVEY PAPER ON DISTRIBUTED LLMS AND MULTIMODAL LARGE LANGUAGE MODELS: A SURVEY ON ADVANCES, CHALLENGES, AND FUTURE DIRECTIONS, LED BY FIU.
Released a survey on Distributed and Multimodal LLMs led by FIU.