Ashwin R.

Background

About Ashwin R.

As Chief AI Officer at FaceCake, I lead the design, development, and deployment of advanced AI solutions that power immersive augmented reality shopping experiences. I bring a deep foundation in machine learning and computer vision, combining technical expertise with strategic leadership to deliver scalable, personalized, and interactive solutions for the commerce sector. My work includes the development of AI-driven recommendation systems, AR try-on platforms, and conversational AI Agents that enhance the way users discover and interact with products. I led the creation of AVA, an AI and AR-powered personal shopping assistant and stylist that delivers real-time product suggestions and virtual try-ons through natural language interaction. Built on Google Cloud’s Vertex AI and large language models, AVA was introduced at Google Cloud Next '24 as a first-of-its-kind shopping advisor. I started my career as an award-winning researcher at the University of Southern California, where I earned a master’s degree in Electrical Engineering focused on computer vision and machine learning. My early research explored how machines interpret visual and sensory data, a foundation that now informs my approach to AI innovation in visual commerce. With over 15 years of experience across academic and industry settings, I have delivered intelligent systems that bridge AI theory and practical application. I continue to guide the integration of machine learning models with real-time AR platforms, collaborating closely with product and design teams to align AI strategy with business growth. Technical Skills • Areas of Expertise: Machine Learning (ML), Computer Vision (CV), Natural Language Processing (NLP), Reinforcement Learning (RL), Generative AI, and Augmented Reality (AR). • Programming & Development: Python, C++; proficient in developing scalable algorithms and data pipelines, with experience in both research prototyping and production-grade coding. • AI/ML Frameworks: PyTorch, TensorFlow 2.x, scikit-learn, Keras, JAX; extensive use of Hugging Face Transformers and other libraries for LLMs and generative AI. • Computer Vision & AR Tools: OpenCV and deep learning vision frameworks; 3D modeling and depth-sensing techniques; AR/VR development with Unity3D, ARCore/ARKit for interactive try-on experiences. • Cloud & MLOps: Google Cloud Platform (Vertex AI, Google BigQuery, AutoML Vision) and AWS SageMaker; containerization and orchestration with Docker & Kubernetes; CI/CD pipelines and ML Ops best practices for deploying and scaling AI solutions