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Note - this section below is enhanced by LinkedIn AI Assistant. As the Director of Engineering of Search, Recommendations and Personalization at UberEats, I lead several teams that work on cutting-edge machine learning and artificial intelligence solutions for feed relevance, recommendation systems, search relevance, semantic retrieval, query/document understanding, checkout recommendation, multi-objective optimization, multi-tasking deep learning, natural language processing, and more. Our mission is to support the hyper growth of Uber's multi-vertical delivery business, such as Eats, Grocery, Alcohol, Prescription, and others, by providing a more efficient and personalized three-sided delivery marketplace and a more data-driven business strategy.I have over 15 years of experience in applying state-of-the-art machine learning and artificial intelligence technology to solve challenging large-scale real-world problems across various domains, such as transportation, e-commerce, social media, and hospitality. I am passionate about building high-performance engineering teams, architecting scalable and reliable technical solutions, and delivering delightful customer experiences. I have successfully led and shipped several end-to-end products that have had a significant impact on millions of users and generated substantial business value. I am always eager to learn new skills, explore new opportunities, and collaborate with diverse and talented people.
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Vp Of Engineering, Machine LearningUpwork Jun 2024 - PresentSan Francisco, California, UsUpwork's mission is to create economic opportunities so people have better lives. As a result, we’ve become the world’s work marketplace where every day businesses of all sizes and independent talent from around the globe meet here to accomplish incredible things.I am supporting Search, Discovery, Personalization, Ads, and Trust & Safety at Upwork. -
Director Of EngineeringUber Mar 2021 - May 2024San Francisco, California, UsEngineering lead of Search, Recommendations and Personalization at UberEats.Build and grow high-performance engineering teams to empower a personalized and delightful customer experience across many product surfaces (Feed/Search/Storefront/Checkout) on UberEats, deliver significant business and engineering impact, design a reliable, efficient, and simplified ranking foundation, and catalyze the state-of-the-art ML/AI innovation at Uber.I support several teams working on cutting-edge machine learning and artificial intelligence solutions for feed relevance, recommendation systems, search relevance, GenAI/LLM-based UberEats Shopping Assistant, semantic retrieval, query/document understanding, checkout recommendation, multi-objective optimization, multi-tasking deep learning, natural language processing, and more. Our mission is to support the hyper growth of Uber's multi-vertical delivery business, such as Eats, Grocery, Alcohol, Prescription, and others, by providing a more personalized and delightful delivery experience. -
Vp Of Applied Machine LearningPostmates By Uber Aug 2019 - Mar 2021San Francisco, California, UsPostmates was acquired by Uber.Reported to the Co-founder and CTO. Built the Applied Machine Learning team comprised of both ML Data Scientists and Engineers from ground up. Led the company’s strategy and roadmap of building an intelligent decision engine for a more efficient and personalized three-sided delivery marketplace and transforming the company to be a more data-driven business by Personalization and Discovery, Dynamic Pricing Optimization, Intelligent Growth and Incentives, ETA prediction and Dispatching optimization etc.In addition, co-founded and co-led the Pricing team (Product, Engineering, Data Science, etc) primarily focused on Postmates’ top line economics & monetization across all sides of the marketplace. -
Engineering Lead Of Machine Learning At Marketplace DynamicsAirbnb Apr 2017 - Aug 2019San Francisco, Ca, UsLed two world-class engineering teams to build business-critical end-to-end machine learning based dynamic pricing systems as well as marketplace dynamics data platform.Supported the Pricing Modeling team to launch many ML-based dynamic pricing strategies in production, which significantly increased nights booked, booking value and host revenue.Founded the Marketplace Intelligence team which has been recognized as the true north of understanding marketplace dynamics of supply, demand, special events, and competitive intelligence across Airbnb. Initiated and led collaboration between Marketplace Intelligence and Guest and Host teams to significantly boost Airbnb growth by integrating marketplace intelligence data and models (e.g.,, supply and demand forecasting, LTV, events modeling, competitive intelligence, etc).Advised the team to file 3 US patents and publish a dynamic pricing modeling paper at KDD 2018. -
Head Of Intelligence PlatformDidi Aug 2015 - Apr 2017Global, CnGrew the team from 3 senior managers to 6 directors/senior managers and from 40+ to 100+ machine learning engineers, data scientists, backend/frontend engineers and product managers to build Didi's next-gen machine learning models and infrastructure, feature store, user profiling, experimentation platform, as well as the batch and real-time big data platform. -
Engineering Manager, Machine LearningLinkedin Nov 2014 - Aug 2015Sunnyvale, Ca, UsManaged a brilliant team of data scientists and engineers to classify, inference and extract entities in the LinkedIn Economic Graph. Built online Samza streaming and offline Hadoop machine learning pipelines to classify and inference entities. Trained the large-scaled Logistic Regression classifiers with ADMM in Hadoop. The normalized and inferred entities have been widely integrated with LinkedIn search engine and many recommendation systems. -
Senior Architect | Tech LeadWalmart Global Tech Oct 2011 - Nov 2014Bentonville, Arkansas, UsLed a 10+ person team developing Walmart's 1st end-to-end Product Categorization Services (PCS), automatic product classification, and automatic product attribute extraction and normalization from scratch. Built the next-gen product knowledge graph. Integrating the Maximum Entropy model and rule-based extractors to extract key product attributes from product titles and descriptions, and search queries.Our machine learning & rules based in-house classification system classified a product with 93% precision and 94% recall given a product title and description.Built the Map/Reduce pipeline in Hadoop to normalize and extract attributes for millions of products on walmart.com. The pipeline ran 10X faster and provided 4X more coverage than the previous one. Developed the data analytics platform to analyze the user behavior with facets search and browse (Left hand navigation refinements). -
Founder And CeoTano Technology Jan 2010 - Sep 2011Next-gen large-scale machine learning pipelines and cloud computing infrastructure
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Assistant ProfessorCity University Of New York Sep 2007 - Dec 2009New York, Ny, UsResearch Interest: Transportation Networking Analysis and Optimization, Machine Learning, Data Mining, Intelligent Transportation Systems, etc.- Developed the network-based travel time and origin-destination estimates based on incomplete traffic sensor data.- Modeled the traveler’s dynamic adjustment process to the online traffic information. Proposed effective congestion pricing schemes to balance the transportation System Optimal and traveler’s User Optimal.- Developed the database to store, index and query real-time traffic information system. - Researched the multi-objective optimization algorithm to solve the large-scale online vehicle scheduling and dispatching problem. -
Research Scientist, Transportation And LogisticsEsri Jan 2005 - Jul 2007Redlands, Ca, UsDeveloped efficient combinatorial optimization (Tabu search) algorithm to solve large-scale online vehicle scheduling and allocation problems. For instance, provided dynamic online real-time fleeting scheduling solution for Orkin's day-to-day nationwide operations - over 400 branches, 3,000 technicians, and 1.6 million customers. -
Adjunct ProfessorUniversity Of Southern California Jan 2006 - Dec 2006Los Angeles, Ca, UsDeveloped and taught a graduate level course in Transportation Network Modeling and Optimization.
Frank Yang Skills
Frank Yang Education Details
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University Of Wisconsin-MadisonIntelligent Transportation Systems -
University Of Wisconsin-MadisonComputer Science
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Tsinghua UniversityBachelor Of Engineering (Be)
Frequently Asked Questions about Frank Yang
What company does Frank Yang work for?
Frank Yang works for Upwork
What is Frank Yang's role at the current company?
Frank Yang's current role is VP of Machine Learning at Upwork.
What is Frank Yang's email address?
Frank Yang's email address is fr****@****bnb.com
What is Frank Yang's direct phone number?
Frank Yang's direct phone number is +141580*****
What schools did Frank Yang attend?
Frank Yang attended University Of Wisconsin-Madison, University Of Wisconsin-Madison, Tsinghua University.
What skills is Frank Yang known for?
Frank Yang has skills like Information Retrieval, Distributed Systems, Linux, Algorithms, Hadoop, Natural Language Processing, Artificial Intelligence, Java, Big Data, Search Engine Marketing, Scalability, C++.
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