AI-driven CAD modeling can enhance efficiency, but hurdles remain
Peer-Reviewed Publication
Updates every hour. Last Updated: 30-Oct-2026 04:16 ET (30-Oct-2026 08:16 GMT/UTC)
3D CAD, even with the assistance of software, can be a laborious and time-consuming process. A group of researchers recently wrote a comprehensive review article outlining the current AI-driven 3D CAD state of the art and described challenges that must be overcome to increase the practicality of AI model use in 3D CAD workflows.
Two outstanding scientists have been awarded the annual Nano Research Award which is sponsored by Tsinghua University Press (TUP). Professor Xiangfeng Duan is the Distinguished Professor at University of California, Los Angeles. Professor Akira Fujishima is the Professor at Institute of Photochemistry and Photofunctional Materials, University of Shanghai for Science and Technology.
Neural radiance fields (NeRFs) are a powerful form of artificial intelligence (AI) that utilizes 2D images to synthesize a 3D scene and “learn” what a realistic 3D representation of the base information would look like. While NeRFs initially revolutionized computer vision in the early 2020s, a new method called Gaussian Splatting quickly overtook NeRFs. In this comprehensive review, researchers explore some of the differences between these two methods and their applications in the hopes of better informing future computer vision practitioners.
Advances in foundation models (FM) have opened the gates to an advanced use of artificial intelligence for healthcare. FMs are an AI system with a great ability to perform accurately on new sets of data or tasks, instead of just memorizing the material it was trained with. Vision-language foundation models (VLFM) are particularly of interest to clinicians as a means to aid in report generation and question answering, with vision-language agents (VLAs) being representative of the next frontier for AI acting in a healthcare space.
Large AI model training data sets often require a significant amount of human labor to annotate and/or format prior to model training. Researchers recently wrote a review paper highlighting self-supervised learning methods for 3D pre-training and provide a unified perspective on comparison and prediction techniques.
About 25 million people in the U.S. — roughly eight out of 100 — are diagnosed with asthma. Allergens, air pollution, extreme weather conditions, or other irritants can cause chronic lung inflammation, leading to coughing, wheezing, or shortness of breath.
One lesser-studied side effect: Asthma attacks induce mechanical forces that permanently alter airway tissue — damage that occurs independently of inflammation alone. New research led by Binghamton University used leading-edge lung-on-a-chip technology to show that the repeated mechanical stress from asthma attacks causes overproduction of proteins for the extracellular matrix that joins cells together.
For a paper published in Nature Biomedical Engineering, Assistant Professor Jungwook “Jay” Paek — a faculty member at the Thomas J. Watson College of Engineering and Applied Science’s Department of Electrical and Computer Engineering — collaborated with colleagues at Binghamton as well as the University of Pennsylvania, the University of Toledo, and the Pacific Northwest National Laboratory.
The new paper continues postdoctoral research that Paek did at Penn with his advisor, Professor Dan Huh, before coming to Binghamton in 2023.
“This is the first time that anyone has demonstrated the effect of a mechanical process on tissue remodeling — including both fibrosis and angiogenesis — in asthma patients,” he said. “It’s groundbreaking, and that’s why a prestigious journal like Nature BME is publishing it.”
Organ-on-a-chip uses microfabrication techniques borrowed from the semiconductor industry to reproduce conditions in the human body with just a small culture of cells.
For this study, the researchers built the microfluidic device so that the tissue could undergo structural deformation by pressurizing or evacuating a connecting chamber. As part of their observations, they tested the potential for medication delivery to modulate the cells’ activity, laying the foundation for possible future asthma treatments.
“This technology is at the intersection of biological science, biomedical engineering, electrical engineering, and mechanical engineering,” Paek said.
Binghamton doctoral student Anika Alim contributed to the research as part of Paek’s project team. As an electrical engineering student, she had little experience with bioengineering principles or lab work, but she got up to speed quickly.
“I started to learn about organ-on-a-chip on the very basic level,” she said. “Then I did a dive deep into how it can replicate human physiology. With this technology, we can see how our human body actually functions when asthma attacks happen.”
She appreciates how the research expands her base of knowledge and experience, as well as Paek’s mentorship through the research: “When I first started, he showed me everything himself — it was a very collaborative experience. I had no idea how to work with cells, but he was there at every step. I'm very grateful.”
Paek’s current research at Binghamton centers on Parkinson's and other neurodegenerative diseases, including a study published earlier this year about how those conditions affect blood circulation and a National Institutes of Health grant to investigate how protein aggregates called Lewy bodies contribute to neurological breakdown.
“Focusing on how neurons are electrically active within the human body leans more toward electrical engineering principles based in biological science,” he said.
About Binghamton University
Binghamton University offers students a broad, interdisciplinary education with an international perspective and one of the most vibrant research programs in the nation. The campus, recognized as an R1 institution for very high research activity by the Carnegie Classification of Institutions of Higher Education, recorded $87.3 million in research expenditures in 2024-25, its best year ever.
As humanity's exploration of the Earth's internal structure deepens, Earth's free oscillations, serving as crucial "fingerprints" for revealing the large-scale structure and dynamic processes within the Earth, have always been a core subject in geophysics. Ground-based station observations are currently the mainstream method for measuring Earth's free oscillations. With the advancement of space technology, high-precision inter-satellite distance measurement holds the potential to become a novel method for detecting these oscillations.