analiza aiqbench
This project demonstrates the practical convergence of virtual reality and digital twins to enhance data visualization within computational biology and robotics. By enabling direct interaction with source imagery in a dynamic 3D model, the work bridges the gap between in-silico modeling and real-world botanical observation. Such integrations offer researchers new methodologies for manipulating complex datasets while supporting broader AI innovation goals at national laboratories.
Brookhaven Lab Intern Develops AI for Plant Digital Twins
Jasmin Lin, a Brookhaven National Laboratory intern, integrated virtual reality with a plant digital twin—a dynamic, real-time model of a physical system. Her project connected VR interaction with a 3D model of a plant, allowing users to access original images used in its creation.
Jasmin Lin, a recent intern at Brookhaven National Laboratory, integrated virtual reality (VR) with a plant digital twin during a January to May Science Undergraduate Laboratory Internships (SULI) term, shifting her research toward artificial intelligence and robotics. Lin’s initial project connected VR interaction with a 3D mockup of a mother board, allowing users to access original images used to generate that exact gaussian at the point of intersection; “This was my first experience using AI within the AI department,” she said, noting an improvement in AI reliability after working with it for a year. Working under the mentorship of Wei Xu, Lin’s focus expanded to training humanoid robots in simulation, contributing to the Department of Energy’s Genesis Mission to accelerate AI innovation within Brookhaven’s Computing and Data Sciences Directorate. Her work, presented at the New York Scientific Data Summit last year, demonstrates the growing intersection of computational biology, embodied AI, and advanced…
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