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Expanding product discovery with ML-powered image similarity search
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Mar 28, 2025 4:00 PM EDT
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Eugene Steinberg

Eugene Steinberg

Dr. Eugene Steinberg, a Founding engineer and VP of Technology at Grid Dynamics, spearheads key technology practices in commerce, search, and AI. As a Principal Architect, he has guided numerous significant programs from inception to production, aligning business requirements with technological capabilities. His achievements include leading the first industry implementation of Google Retail Search's alpha version, implementing pioneering visual search and recommendation systems using deep learning, architecting microservices-based commerce platforms and custom search engines, and pioneering distributed in-memory computing for fraud detection. Dr. Steinberg's expertise spans digital commerce platforms, AI/ML applications, information retrieval, enterprise search, natural language processing, computer vision, and scalable distributed systems. As a thought leader, he has been instrumental in developing the Grid Dynamics - Google partnership, spoken at conferences on various tech topics, and advised startups and VC firms. Dr. Steinberg continues to drive innovation in digital commerce and related technologies, contributing to Grid Dynamics' reputation for engineering excellence and emerging technology expertise.

Blog posts:

March 14, 2025 Agentic AI: The next evolution in enterprise automation
May 30, 2023 Revolutionizing product visualization with generative AI
April 10, 2023 Applications of generative AI in digital commerce part 1: Content
December 27, 2022 Driving differentiation in e-commerce marketplace search
September 09, 2022 The future of commerce is composable
August 16, 2022 Semantic search for the chemicals B2B marketplace: A Knowde case study
June 07, 2022 Achieving business flexibility with composable commerce
May 19, 2022 Accelerate integration of Google Cloud retail search
May 03, 2022 Launching Google Discovery Solutions starter kit for Commercetools
January 31, 2022 Evolution of omnichannel digital commerce: What’s new in 2022
January 31, 2022 Visual search for the world’s largest dinnerware retailer
September 23, 2021 Semantic query parsing with Lucidworks Fusion: Key to understanding your search queries
May 28, 2021 Street-to-shop: Is the future of fashion visual search?
January 14, 2021 How to recognize coins with deep learning visual model
December 15, 2020 Virtual backgrounds: Real-time deep semantic segmentation on mobile devices
October 15, 2020 Building a question answering system for online store
September 16, 2020 Semantic query parsing blueprint
September 04, 2020 Vector space retrieval model for e-commerce
July 20, 2020 Industrial label recognition made easy with AutoML
June 23, 2020 High-performance auto parts search: Moving from Endeca to Elasticsearch
April 07, 2020 How to replatform Endeca rules to Solr
March 13, 2020 Boosting product discovery with semantic search
March 12, 2020 Smart autocomplete for Replacements.com drives revenue
March 03, 2020 Tiered machine learned ranking improves relevance for the retail search
February 28, 2020 Relevant facets: How to select and promote facets with deep learning
February 22, 2020 Understanding search query intent with deep learning
February 18, 2020 How to replatform Endeca rules to Elasticsearch
January 23, 2020 Not your father’s search engine: A brief history of retail search
January 09, 2020 Semantic vector search: The new frontier in product discovery
September 25, 2019 How deep learning improves recommendations for 80% of your catalog
September 11, 2019 A visual search for dinnerware patterns with Replacements.com
December 06, 2018 How automated merchandising tools can improve online product discovery
November 15, 2018 Art.com helps customers find art they love with visual search
August 14, 2018 How to implement multi-select faceting for nested documents in Solr
June 20, 2018 Grid Genie: The beginning of conversational commerce
May 30, 2018 Expanding product discovery with ML-powered image similarity search
December 12, 2016 Why e-commerce search engines must be aware of inventory
July 19, 2016 Advanced Solr/Lucene topics: High-performance nested search for e-commerce applications

Eugene Steinberg

Dr. Eugene Steinberg, a Founding engineer and VP of Technology at Grid Dynamics, spearheads key technology practices in commerce, search, and AI. As a Principal Architect, he has guided numerous significant programs from inception to production, aligning business requirements with technological capabilities. His achievements include leading the first industry implementation of Google Retail Search's alpha version, implementing pioneering visual search and recommendation systems using deep learning, architecting microservices-based commerce platforms and custom search engines, and pioneering distributed in-memory computing for fraud detection. Dr. Steinberg's expertise spans digital commerce platforms, AI/ML applications, information retrieval, enterprise search, natural language processing, computer vision, and scalable distributed systems. As a thought leader, he has been instrumental in developing the Grid Dynamics - Google partnership, spoken at conferences on various tech topics, and advised startups and VC firms. Dr. Steinberg continues to drive innovation in digital commerce and related technologies, contributing to Grid Dynamics' reputation for engineering excellence and emerging technology expertise.

Eugene Steinberg