Attend a seminar on Domain-Aware Multimodal Learning for Integrated Engineering, Aug. 28

About

Fatemeh Elhambakhsh is a doctoral student in the data science, analytics and engineering program at Arizona State University. She earned a Master of Science in industrial engineering with a concentration in systems optimization from Iran University of Science and Technology.

Her research focuses on generative AI and multimodal learning for engineering design and manufacturing. She is particularly interested in developing domain-aware AI methods that integrate diverse engineering data and representations to support intelligent design, manufacturing and decision-making across the product lifecycle.

Elhambakhsh has gained industry research experience through internships at Siemens and Autodesk, where she worked on AI-driven solutions for engineering applications. She is currently a senior research intern at Siemens, conducting research on generative AI for next-generation engineering systems. Her long-term goal is to advance AI technologies that bridge engineering design and manufacturing, enabling more intelligent, efficient and reliable engineering workflows.

Abstract

Modern manufacturing systems generate diverse engineering data throughout the product life cycle, from conceptual design and process planning to manufacturing and reverse engineering. Engineering design provides a rich foundation for these data through complementary representations, including functional descriptions, computer-aided design models and manufacturing process information. Although these representations are created to define product functionality and geometry, they also provide valuable knowledge for downstream manufacturing applications. This talk explores how multimodal engineering design data can be combined with domain-aware machine learning methods to solve manufacturing challenges across the engineering life cycle. Recent advances include the use of large language models for functional reasoning in conceptual design, diffusion models for generative computer-aided design reconstruction in reverse engineering and graph transformer models for manufacturing process planning. Together, these approaches demonstrate how integrating engineering knowledge with artificial intelligence enables more intelligent, efficient and adaptable solutions throughout engineering design and manufacturing.

Domain-Aware Multimodal Learning for Integrated Engineering seminar
Friday, Aug. 28, 2026
10:30 a.m.–noon
Interdisciplinary Science and Technology Building 12 (ITSB 12) room 215, Polytechnic campus [map]