Call for Presentation Proposals
Share Your Expertise on Practical Computer Vision and Physical AI
2027 Summit presentation proposals are due August 14, 2026. Space is limited, so submit your presentation idea now!
The Embedded Vision Summit is the premier conference for innovators incorporating computer vision and AI in products. It covers technologies and techniques for the entire spectrum of physical AI applications including consumer, automotive, healthcare, industrial, retail and more.
It attracts a unique audience of more than 1,400 product creators, entrepreneurs and business decision-makers who are creating and using vision and AI technology.
The 2027 Summit is a live, in-person event, taking place February 2-4, 2027 in San Francisco, California, as part of Photonics West, where it will be along side Vision Tech Forum and part of the Vision Tech Expo. The Summit is known for high-quality, relevant content, so it’s the ideal venue for sharing your insights and getting the word out about new technologies, techniques, applications, products and practical breakthroughs in computer vision and AI.
All Summit presentation proposals are evaluated for relevance to audience interests, quality of content and the presenter’s public speaking skills. Proposals will be considered until the agenda is full–submit early for your best chance at being accepted to speak at the Summit.
Important: Talks presented by companies that supply building-block technologies (such as processors, software tools, algorithms, sensors, camera modules and data labeling services) require a sponsorship fee if the topic of the session is related to the company’s products (for example, describing the technology underlying the product or a use case of the product). Please contact us for sponsorship details. (If you would like to give a presentation on a product that has not yet been announced, please contact us to discuss options for limiting the information that we will make public prior to the Summit.)
Presentation Content
Talks should be substantive, insightful and educational.
For the Technical Insights, Business Insights and Fundamentals tracks, presentations should deliver practical insights, data and techniques that attendees can put to use whether or not they use your company’s products. Sponsored, product-related presentations (Enabling Technologies track) cover commercially available components, algorithms and tools that product developers can use to incorporate computer vision or AI into systems, chips and applications. While a talk in this track can be about your company’s product, content should be educational rather than promotional in substance and tone.
Speakers and Logistics
We’re looking forward to hearing what you have to say!
Here are some important details about presentations:
- Speakers should have strong public speaking skills and subject matter expertise. The Technical Insights, Fundamentals and Enabling Technologies track talks should be presented by individuals in engineering or engineering management roles.
- We encourage joint presentations with customers and partners.
- Most presentations will comprise 20 minutes of prepared content and 5 minutes of Q&A. Selected presentations (especially in the Fundamentals track) will be 50 minutes long, plus 10 minutes for Q&A.
- All talks must use the Embedded Vision Summit PowerPoint template. The template includes a place for your company logo.
Presentation Topics
The Summit program covers a wide range of topics related to practical computer vision and AI. Included below is a selection of topics on which we especially welcome proposals.
Algorithms
- Vision-language models, large multimodal models, large language models and vision-language-action models
- Small language models, compact VLMs, model optimization, model compression, quantization, pruning, distillation and efficient edge inference
- World models and physical AI systems that perceive, reason, plan and act in real-world environments, including generative and joint-embedding predictive architecture (JEPA) approaches
- Approaches and advances in deep neural networks, including transformer-based networks, state-space models and neuromorphic algorithms such as spiking neural networks
- Conventional (non-ML based) algorithms, including signal/image processing, detection, classification
- Approaches and advances in object tracking
- Approaches and advances in event and action recognition (e.g., temporal neural networks)
- Improving neural network model accuracy in the real world
- Learning at the edge: few-shot learning, continuous learning
- 3D perception, including SLAM and scene understanding using depth sensors, radar, lidar, etc.
- Monocular depth estimation
- Sensor integration and fusion in ML-based systems—vision, depth, audio, haptic, etc.
Fundamental Techniques
- Introduction to ML for visual perception
- Introduction to CNNs
- Fundamentals of training AI models for computer vision applications
- Ensuring quality data for deep learning: data collection, curation and annotation
- Fixing training problems—insights, best practices
- Introduction to and survey of DNN-based object detectors and use cases
- Practical object tracking approaches
- Introduction to segmentation: semantic, instance, panoptic
- Introduction to transformers
- Introduction to large language models
- Introduction to vision-language models (and potentially other large multimodal models)
- Introduction to state-space sequence modeling
- Introduction to model compression approaches—quantization, pruning, sparsity, distillation, etc.
- Introduction to recent neural networks for the edge, such as SAM3, YOLO26, EdgeViT, LL-ViT, RT-DETR
- Fundamentals of optics and image sensors
- Camera selection and image quality metrics
- Fundamentals of depth sensors: time-of-flight, lidar, stereo, structured light
- Fundamentals of radar for machine perception
- A survey of commonly used sensors—vision and non-vision—for edge machine perception
- Introduction to SLAM
Advanced AI and Vision System Design Techniques and Components
- Real-world case studies of end-to-end vision- and AI-based solutions: pitfalls, trade-offs and insights
- Practical trade-offs in deploying AI models on constrained devices: memory, latency, throughput, power, thermal limits and cost
- Robustness, safety, trustworthiness and security for deployed vision AI
- Identifying and mitigating bias in AI-based systems
- Building practical applications with vision-language models, large multimodal models, large language models, small language models, and vision-language-action models
- Insights and best practices for fine-tuning task-specific LMMs, VLMs, SLMs and VLAs
- Use cases of products incorporating agentic AI
- Real-world performance metrics for developing and maintaining AI-based products
- Cloud-edge tradeoffs
- End-to-end system optimization
- Event-based and neuromorphic sensors and processors
- Selecting cameras, image sensors and optics; understanding image quality metrics, depth sensing, event-based vision, sensor fusion, calibration and spatial perception
- Image and non-image sensors and processing techniques: lidar, radar, time-of-flight, stereo, audio
- Insights and best practices in selecting AI/CV technologies and techniques for real-world products
- Low-power, low-cost vision and AI components—SoCs, NPUs, etc.
- Training data, synthetic data, collection, curation, annotation, generation, augmentation, edge-case coverage and validation for vision/AI systems
- MLOps—training a model, best practices, insights
- MLOps—deploying and maintaining models in production
- MLOps—testing a model in the lab vs. in the wild, best practices, insights and explainability
- Standards, data privacy and regulatory compliance
- Tools, frameworks and techniques for developing and deploying AI-based products
- Top-to-bottom software stacks for AI-based systems and applications
Applications
- Agriculture
- Augmented and virtual reality
- Automotive
- Autonomous machines
- Construction
- Consumer
- Defense and aerospace
- Distribution and logistics
- Entertainment and sports
- Healthcare
- Industrial and manufacturing
- Retail
- Robotics
- Security and surveillance
- Smart spaces
- Transportation
Who Can Present
Anyone with relevant expertise is welcome to propose a presentation. Presentations by companies that supply building-block technologies on topics related to the company’s products are available only to Edge AI and Vision Alliance Member companies.
For information about sponsoring a presentation, an exhibit booth or other elements of the Summit, please contact our team below.
Information Needed to Apply
For your convenience, below is a list of information needed to propose a presentation.
Company information
- Company name (as you want it to appear in the program)
- Company website
Speaker information
- Name and job title (as you want it to appear in the program)
- Email address
- Business phone number and postal address
- Mobile phone number (not for publication)
- Speaker bio (<150 words)
- Social media
- Speaker head-and-shoulders photo (1000×1000 pixels)
Additional contact person information (optional)
- Name and job title
- Email address
- Business phone number
- Mobile phone number (not for publication)
Presentation information
- Presentation title
- Abstract: Describe the scope and depth of the talk, including key examples (<150 words)
- Detailed outline
- Description of target audience (job function, experience level)
- Purpose: What will the audience gain from this talk (<25 words)
- Relationship between the presentation topic and the speaker’s company’s products or services (<50 words)?
- Have you previously presented at the Summit?
If your presentation is accepted, you commit to the following:
- Appearing at the Summit to present (no substitute speakers)
- Using the official Embedded Vision Summit slide template design
- Submitting and revising slides according to the schedule in your acceptance letter
- Updating your slides in response to feedback from the organizers
- Allowing your slides and a video and/or audio recording of your presentation to be distributed after the event
- Following the Speaker Guidelines, which will be sent to speakers upon acceptance into the program
- Complying with the Summit Attendee Registrant Terms and Conditions
If you have questions regarding submitting a proposal, please contact our program team.
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