David vonThenen
AI/ML Engineer | Keynote Speaker | Building Scalable AI Architectures & ML Solutions | Python, Go, C++
Long Beach, California, United States
Actions
David is a Senior AI/ML Engineer within the Office of the CTO at NetApp, where he’s dedicated to empowering developers to build, scale, and deploy AI/ML solutions in production environments. He brings deep expertise in building and training models for applications like NLP, vision, real-time analytics, and even models to classify diseases in a medical setting. His mission is to help users build, train, and deploy AI models efficiently, making advanced machine learning accessible to users of all levels.
Before NetApp, he was heavily involved in the AI/ML community, specifically in conversational AI solutions and driving AI platform growth in a DevRel and pre-sales role. David frequently shares his insights at industry conferences and events, offering hands-on guidance for implementing AI/ML in cloud environments. David's prior experience includes contributing to the Kubernetes and CNCF ecosystems, working hands-on with VMware virtualization, implementing backup/recovery solutions, and developing hardware storage adapter firmware and drivers.
Area of Expertise
Topics
The Future of UI/UX: AI-Generated Interfaces Tailored Just-in-Time
Imagine a world where every user interface is crafted uniquely for you—optimized in real-time based on your behavior, interests, and history. This talk explores the cutting edge of AI-driven Just-In-Time (JIT) UI/UX design, where user interfaces are no longer static but dynamic entities that adapt to each user's preferences and context. By leveraging advanced machine learning models, behavioral analytics, and predictive algorithms, this approach promises to revolutionize user experiences across applications, from e-commerce to productivity tools.
In this session, we'll delve into the tools and frameworks enabling JIT design, such as AI-powered behavior prediction, dynamic content rendering, and reinforcement learning models for UI adaptation. Attendees will witness the future of UI/UX design through a live demonstration of a personalized, real-time adaptive interface, showcasing how AI can craft and deliver unique experiences for individual users. Join us to uncover how these innovations are shaping a new era of hyper-personalized digital interaction.
API Security for the AI Era: Detecting and Preventing Adversarial Manipulation
In a digital landscape dominated by APIs and AI, security threats from adversarial manipulation have become critical risks. This session explores the intersection of APIs, AI security, and adversarial attacks. We'll dissect how adversaries manipulate APIs feeding data to machine learning models—by injecting noise, crafting misleading inputs, and exploiting data obfuscation techniques—to compromise model integrity and security. Attendees will gain insights into real-world adversarial scenarios, learn practical defensive techniques, and understand the implications for privacy, model fairness, and data reliability.
The session will provide practical examples and live demonstrations showcasing how adversarial strategies can exploit API vulnerabilities to undermine AI models. We'll examine defensive frameworks and best practices for securing APIs against adversarial attacks, ensuring data integrity, maintaining privacy compliance, and reinforcing ethical AI usage. By the end, attendees will be equipped with strategies for hardening their AI-driven APIs, proactively identifying vulnerabilities, and deploying robust security measures to mitigate adversarial threats.
Confuse, Obfuscate, Disrupt: Using Adversarial Techniques for Better AI and True Anonymity
In a world where algorithms dictate what we see, buy, and believe, understanding how to disrupt and manipulate them is as powerful as knowing how to build them. This session dives into adversarial techniques that challenge the assumptions of AI/ML models. By introducing noise, obfuscating data, and exploiting algorithmic learning cycles, we can uncover hidden biases and vulnerabilities in AI systems. These techniques push the boundaries of ML training, offering developers a toolkit for crafting more resilient models.
Beyond improving AI, these techniques offer a unique avenue for achieving digital anonymity. Whether you want to obfuscate your online footprint or prevent data collectors from profiling you, adversarial inputs provide a practical path forward. In this session, attendees will learn how adversarial methods can transform vision and NLP models, empower individuals to take control of their privacy, and showcase live demonstrations of these disruptive strategies in action.
API World 2025 Sessionize Event Upcoming
WeAreDevelopers World Congress 2025 Sessionize Event Upcoming
DevBcn 2025 Sessionize Event Upcoming
Render (RenderATL) 2025 Sessionize Event Upcoming
Open Data Science Conference
Workshop: Adaptive RAG Systems with Knowledge Graphs: Building Reinforcement-Learning-Driven AI Applications
Devoxx UK
The Rise of Agentic AI: Harnessing Open Source for Dynamic Decision-Making
Devoxx France
Explaining the Unexplainable: Python Tools for AI Transparency using Captum
All Things Open AI
Leveraging Knowledge Graphs for RAG: A Smarter Approach to Contextual AI Applications
NVIDIA GTC 2025
Crack the AI Black Box: Practical Techniques for Explainable AI
Southern California Linux Expo (SCaLE) 22x
Training Multi-Modal ML Classification Models for Real-Time Detection of Debilitating Disease
Southern California Linux Expo (SCaLE) 22x
Demystifying Building Natural Language Processing ML Models and How to Leverage Them By Example
Developer Week 2025
KEYNOTE: The Sound of Innovation: Why Voice Cloning Will Redefine Human-Computer Interaction
Developer Week 2025
Navigating the Edge-Cloud Bridge: Building Resource-Optimized IoT/Edge Assistants with LLMs
Open Data Science Conference 2024
Workshop: Building Multiple Natural Language Processing Models to Work In Concert Together
Real Time Communications Conference & Expo 2024
KeyNote: Training Machine Learning Classification Models for Creating Real-Time Data Points of Medical Conditions
Video: https://youtu.be/YgeinCCUBCk
Real Time Communications Conference & Expo 2024
Session: Building Multiple Natural Language Processing Models to Work In Concert Together
Video: https://youtu.be/0DHHS17mn_o
AI DevSummit 2024 Sessionize Event
SCaLE 21x (2024)
Title: Voice-Activated AI Collaborators: A Hands-On Guide Using LLMs in IoT & Edge Devices
Video: https://youtu.be/9Nj4hKy70yQ
IEEE RTC Conference
Title: Enhancing Real-Time WebRTC Conversation Understanding Using ChatGPT
Video: https://youtu.be/u-Q2TdzS7d8
IEEE RTC Conference
Title: Edge Devices as Interactive Personal Assistants: Unleashing the Power of Generative AI Agents
Video: https://youtu.be/ctyWBG-x9y8
Nexus x TPF GenAI Rush 2023
Title: Streamlining Communication Workflows
Video: https://www.youtube.com/watch?v=8gfWnN_hwGk
API World 2022
Title: Enabling Untapped Use Cases in ML/AI : Edge, Memory-Constrained, and Server-side Use Cases
Video: https://youtu.be/XYQPIHazMK8
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top