MeetupOnline

Aug 4 - Visual AI in Manufacturing

AUG4
21:30 · Asia / Kolkata
  • This virtual meetup features talks by experts on the application of AI, machine learning, and computer vision in manufacturing.
  • It is intended for professionals interested in how visual AI technologies can improve manufacturing processes.
  • Attendees will gain insights into the intersection of AI and industrial production.

About this event

Join our virtual meetup to hear talks from experts on cutting-edge topics at the intersection of manufacturing, AI, ML, and computer vision.

Date, Time and Location

Aug 04, 2026
9:00 AM - 11:00 AM PST
Online. Register for the Zoom!

Enabling Multimodal Agents on the Edge

The next generation of AI agents is moving beyond cloud-based text-only models and will interact with the physical multimodal world in real-time. For example in the vision domain, AI agents rely on Vision-Language Models (VLMs) in their backbone. However, deploying massive VLMs with billions of parameters on the edge devices remains a significant engineering hurdle.

Drawing on our recent ICML and CVPR research papers, this session explores advancements in agentic model optimizations, specifically how distillation and pruning transform 'heavyweight' models into lean, edge-ready engines. Lastly, I present our UI agent running on the actual phone that is being developed by our lab's team.

About the Speaker

Denis Gudovskiy is a Distinguished AI Engineer at Panasonic North America where he conducts R&D activities of various core AI methods, including multimodal and hardware-efficient agents, supervised and RL training pipelines, and robustness to out-of-distribution scenarios.

When the Camera Can’t Be Trusted: Health-Aware Visual AI for Reliable Near-Miss Detection

Near-miss detection systems are often evaluated as though every camera frame is equally trustworthy, even though blur, poor exposure, occlusion, contamination, and changing lighting can silently degrade the visual evidence used to make safety decisions. This talk presents an online camera-health framework that estimates visual reliability before downstream perception performance significantly deteriorates.

I will discuss how camera-health signals can support condition-aware evaluation, prioritize human review, reduce unreliable alerts, and trigger appropriate fallback behavior. Drawing from research in safety-critical visual perceptio

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