Professor at University of Florida; Informatics, Cobots and Intelligent Construction (ICIC) Lab. Robot, VR/AR/XR, human factors, and AI.

Gainesville, FL
Joined August 2009
Grateful to UF News for covering our research! AI with attitude? Engineering professor explores how AI performs in high-risk situations news.ufl.edu/2026/10/llm-ris…
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Excited to share that our paper “Benchmarking Risk Attitudes of Large Language Models” has been accepted to #NeurIPS2026! 🎉 Congrats to co-first authors Bowen Sun & Rui Min, and many thanks to collaborators Ryan Wang & Yang Ye! #LLM #AI #DecisionMaking
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Interviewed by WCJB ABC20 TV today about our FLL team winning 1st place in state championship and going to the World championship! Cool experience and thank you @WCJB20 !
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My 12 yo son recreated a video game (Neighbors) in one week. He taught himself Blender, Unity, and C# from online tutorials, and programmed the NPC AI himself. He said free ChatGPT wasn’t helpful for coding, so he did it on his own. Check it out: youtu.be/AjxtPCzL8Ec?si=b4Di…
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New paper out in Scientific Reports: “Opportunities, Challenges & Roadmap for Humanoid Robots in Construction.”nature.com/articles/s41598-0… We outline a 10-year path for humanoids in construction.
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“Am I real?” #Sora2
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Dreams come true #Sora2
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A dialogue across time. #Sora2
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Can LLMs pick the right priority for UAVs in urban winds? Yes! Our new IEEE Access paper “LLM-Driven Pareto-Optimal Multi-Mode RL for Adaptive UAV Navigation” shows 16% faster flights, 50% fewer collisions, 18% energy savings. ieeexplore.ieee.org/document… #AI #Drones #RL #UAV
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Grateful to the Buildings Best Paper Award committee for recognizing our work! 🎉 Congrats to my students 👏 for advancing LLM-driven sequence planning that helps robots adapt to complex, dynamic construction tasks. Proud of the team! 🚀 #ConstructionRobotics #AI
#2023BPA #bestpaper 5️⃣ Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT, by Hengxu You et al. ⭐ Keywords: #robotassembly; #sequentiallearning; #ChatGPT 🔗 Read for free at: mdpi.com/2384148
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Honored and humbled to receive the Steve and Wendy Blum Professorship. Deepest thanks to Mr. & Mrs. Blum for their extraordinary generosity and vision. This recognition reflects the efforts of many colleagues, students, and collaborators. @UF @UFESSIE
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Interviews ongoing with ABC/WCJB.
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Our new paper, "AI Generations: from AI 1.0 to AI 4.0," is out now! We map the evolution of AI from Information AI (1.0) to Agentic (2.0), Physical (3.0), and a speculative look at Conscious AI (4.0). A 70-year journey of algorithms, data, and compute. frontiersin.org/journals/art…
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It’s only been four months and 14 days.
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🌟 #EditorsChoice 🌟 Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT by Hengxu You, Yang Ye, Tianyu Zhou, Qi Zhu and Jing Du 🔗 Read for free at: mdpi.com/2384148 #robotassembly #ChatGPT
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Received this in my email this morning. A top 0.5% scholar 👓
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🚀 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗶𝘀 𝘁𝗵𝗲 𝗡𝗲𝘅𝘁 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗟𝗲𝗮𝗽 𝗳𝗼𝗿 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗗𝗿𝗶𝘃𝗶𝗻𝗴—𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗛𝗶𝘁𝗰𝗵𝗵𝗶𝗸𝗲𝗿'𝘀 𝗚𝘂𝗶𝗱𝗲 𝗬𝗼𝘂’𝘃𝗲 𝗕𝗲𝗲𝗻 𝗪𝗮𝗶𝘁𝗶𝗻𝗴 𝗙𝗼𝗿! 🚀 We're thrilled to share our most comprehensive, 128-page survey, "𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗳𝗼𝗿 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗗𝗿𝗶𝘃𝗶𝗻𝗴: 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿𝘀 𝗮𝗻𝗱 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀," developed collaboratively by 23 institutions, including universities like #TAMU, #UCRiversie, #Purdue, #UMich, #UFL, hashtag#ASU, #Columbia, #Stanford, etc., and industry leaders such as #NVIDIA, #Bosch, #TTI, #Adobe, to name a few. 🔥 This isn't merely another overview; it’s an in-depth exploration that synthesizes breakthroughs, analyzes state-of-the-art technologies, and charts a clear, detailed roadmap for the future of autonomous driving and intelligent mobility. 🧩 𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗱𝗲𝗲𝗽𝗲𝗿 𝗹𝗼𝗼𝗸 𝗶𝗻𝘁𝗼 𝘄𝗵𝗮𝘁 𝘄𝗲’𝘃𝗲 𝗰𝗼𝘃𝗲𝗿𝗲𝗱: 🔹 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 𝗼𝗳 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜: Clear overview of VAEs, GANs, Diffusion Models, NeRF, and LLMs. 🔹 𝗖𝘂𝘁𝘁𝗶𝗻𝗴-𝗘𝗱𝗴𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗗𝗿𝗶𝘃𝗶𝗻𝗴: 𝘚𝘦𝘯𝘴𝘰𝘳 𝘋𝘢𝘵𝘢 𝘎𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯; 𝘛𝘳𝘢𝘫𝘦𝘤𝘵𝘰𝘳𝘺 𝘢𝘯𝘥 𝘔𝘰𝘵𝘪𝘰𝘯 𝘗𝘳𝘦𝘥𝘪𝘤𝘵𝘪𝘰𝘯; 𝘖𝘤𝘤𝘶𝘱𝘢𝘯𝘤𝘺 𝘢𝘯𝘥 𝘚𝘤𝘦𝘯𝘦 𝘜𝘯𝘥𝘦𝘳𝘴𝘵𝘢𝘯𝘥𝘪𝘯𝘨; 𝘚𝘤𝘦𝘯𝘦 𝘌𝘥𝘪𝘵𝘪𝘯𝘨 𝘢𝘯𝘥 𝘊𝘶𝘴𝘵𝘰𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯. 🔹 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀: 𝘌𝘯𝘥-𝘵𝘰-𝘌𝘯𝘥 𝘈𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘚𝘺𝘴𝘵𝘦𝘮𝘴; 𝘚𝘺𝘯𝘵𝘩𝘦𝘵𝘪𝘤 𝘋𝘢𝘵𝘢 𝘞𝘰𝘳𝘬𝘧𝘭𝘰𝘸; and 𝘋𝘪𝘨𝘪𝘵𝘢𝘭 𝘛𝘸𝘪𝘯𝘴 𝘢𝘯𝘥 𝘚𝘮𝘢𝘳𝘵 𝘛𝘳𝘢𝘯𝘴𝘱𝘰𝘳𝘵𝘢𝘵𝘪𝘰𝘯 𝘕𝘦𝘵𝘸𝘰𝘳𝘬𝘴. 🔹 𝗕𝗿𝗼𝗮𝗱𝗲𝗿 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗘𝗺𝗯𝗼𝗱𝗶𝗲𝗱 𝗔𝗜 𝗮𝗻𝗱 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀: Cross-domain transfer methods for robotics and drones, to Embodied AI, and more. 🔹 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗮𝗻𝗱 𝗢𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀: generalization, safety, ethics, environment, and regulation. Strategic research paths in theoretical assurances, trust metrics, V2X cooperation, and urban integration. 🔹 𝗙𝘂𝘁𝘂𝗿𝗲 𝗢𝘂𝘁𝗹𝗼𝗼𝗸 𝗮𝗻𝗱 𝗩𝗶𝘀𝗶𝗼𝗻: dataset diversity, model robustness, theoretical foundations, computational scalability, human-AI collaborative frameworks. 📖 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝘀𝘂𝗿𝘃𝗲𝘆: arxiv.org/abs/2505.08854 🔗 E𝘅𝗽𝗹𝗼𝗿𝗲 𝗰𝗼𝗱𝗲: lnkd.in/gvcZh3Ka 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗶𝘀 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝗹𝘆 𝗿𝗲𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗳𝘂𝘁𝘂𝗿𝗲 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁𝗮𝘁𝗶𝗼𝗻. Our detailed survey equips 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿𝘀, 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀, 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗹𝗲𝗮𝗱𝗲𝗿𝘀, 𝗮𝗻𝗱 𝗽𝗼𝗹𝗶𝗰𝘆𝗺𝗮𝗸𝗲𝗿𝘀 with the tools to navigate this transformative intersection. 🌟 The future of mobility is 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲. Let’s build it together! 🌟 #GenAI #AutonomusDriving #Autonomy #Drone #USDOT #USA #Diffusion #LLM #VLM #Collaboration #Research #Innovation #AI #CVPR #Publication #Overview
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