Join our in-person meetup to hear talks from experts on cutting-edge topics across AI, ML, and computer vision. View more CV events here.

This talk will explore practical workflows for building, evaluating, and improving modern computer vision systems. We’ll dive into real-world approaches to dataset curation, model analysis, multimodal AI workflows, and production-ready vision pipelines using open-source technologies.

The session is designed for engineers, researchers, and AI practitioners looking to better understand how teams are developing and scaling computer vision applications today. Expect practical demos, technical insights, and discussions around the evolving AI tooling ecosystem.

This talk covers detecting, segmenting, and analyzing nanoparticles in microscopic images — including YOLO models, Classical CV, and Gradio.

Vision-language models are becoming powerful general-purpose tools, but their real value often appears when they are adapted to domain-specific tasks. In this talk, I will present practical strategies for fine-tuning VLMs on specialized data, from dataset design and annotation quality to model selection, evaluation, and deployment constraints. I will discuss common challenges such as limited data, visual ambiguity, domain shift, hallucinations, and maintaining robustness in production. The session will focus on applied lessons for building reliable VLM systems that go beyond demos and solve concrete business or research problems.