Speaker: Dr. Saeed Vahidian, Postdoctoral Scholar, Duke University
Topic: “Generative AI for Explainable, Robust, and Trustworthy Edge Intelligence”
Abstract: The proliferation of edge devices has created a vast, distributed, and privacy-sensitive data ecosystem—the new frontier for AI. However, this opportunity intersects with a fundamental constraint: the AI community is entering a "peak-data" era, where the supply of high-quality web data is becoming exhausted. Major AI labs including Google, OpenAI, Anthropic, and Meta are already integrating synthetic data into their training pipelines, but translating this capability to real-world edge environments introduces significant system-level challenges. This talk presents a new paradigm for Trustworthy Edge Intelligence, using Generative AI and Robust Learning as core primitives to create efficient, trustworthy, and scalable AI systems.
Dr. Vahidian’s research addresses three critical challenges through integrated solutions: engineering generative AI to grow synthetic corpus coverage without exploding GPU, memory, or communication usage on constrained edge intelligence systems; using robust learning to diagnose and correct failures on underrepresented subgroups of data; and developing protocols that enable collaboration without raw data movement where data is siloed at the edge. These solutions bring together efficient and explainable generative AI for synthetic data pipelines, robust learning that targets domain shift and model failures on underrepresented data subgroups in edge intelligence systems where data lives—using federated learning, where I introduced the first exploration of federated instruction tuning (FedIT) for LLMs , with resource-efficient protocols for heterogeneous devices. Conducted within the NSF AI Institute for Edge Computing (Athena), our works integrate hardware-aware safeguards, advancing a future where edge devices collaboratively create and refine models using generative AI—ensuring robust performance without compromising privacy.
Biography: Dr. Saeed Vahidian conducted his Postdoctoral research at Duke University, with Prof. Yiran Chen, Director of the NSF AI Institute for Edge Computing (Athena) —one of the 27 National AI Institutes established by the U.S. National Science Foundation with $20,000,000 in federal funding. He received his Ph.D. in Electrical and Computer Engineering from the University of California San Diego (UCSD). His research sits at the intersection of Generative AI and Efficient Edge Intelligence, developing hardware-aware algorithms, robust learning methods, and synthetic data generation for vision-language, multimodal, and video pipelines. He has collaborated with Qualcomm AI and academic institutions across the U.S., Canada, and Europe—efforts that led to an invitation from NASA to contribute to a project on Edge Intelligence. His publications appear in NeurIPS, ICLR, CVPR, ECCV, ICCV, UAI, IEEE Transactions on AI, and JMLR. He has served as Chair at CVPR workshops and as a reviewer for ICML, NeurIPS, CVPR, etc.
The Research Presentation is open to the public free of charge.
*For further information, please contact Dr. Liudong Xing
Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Liudong Xing
5089998883
lxing@umassd.edu