Our innovative platform centralizes customer communications across multiple channels including WhatsApp, Messenger, Instagram, and the web. We empower businesses to enhance their sales by removing friction from message-driven transactions and offering an AI-driven personalized shopping experience, powered by our own in-house proprietary LLMs.

Strava is the home of your active life. We strive to connect athletes to what motivates them and help them find their personal best. As its CTO, I am responsible for the technical efforts with a strong focus on data and ML to achieve our mission and vision. Managing teams of infrastructure, platform, geo, productivity, data, machine learning, analytics, and data science. Scaling the business through a strong vision and engineering foundation. Scaling teams through processes, hiring and coaching.

As a senior member of the leadership team, running R&D teams of 300 people at NetEase Media Group. NetEase is a publicly-traded company(NASDAQ:NTES).Heading 4 areas: AI, News Feed, Data Infra, and Growth. Our flagship news aggregate product NetEase News serves 25 million+ users daily/70 million+ monthly across the globe and offers the most personalized experience backed by technologies such as NLP, Computer Vision, Deep Learning, Machine Learning, Big Data, and system work.I divide our work into the following categories:- Content understanding: leverage NLP & CV to blacklist, filter, re-arrange, classify & enhance our content (e.g. auto remove commercial content, enhance low-res videos, porn/unsafe identification, etc).- User understanding: building user profiles of demographics & content preferences data.- Machine/Deep Learning platform: model management & scalability.- Data platform: raw data turned into warehouse & facts (BI). AB Test.- Architecture: how we scale globally.- Dev/User experience: tools for developers. Not only for system development(Automation & CI) but also experience development (end user experience and bad case debugging).- Product engineering: mobile/web work for News Feed, Videos, Search, Ads, etc.- Growth. Organic, Paid, Referral, Partnership, etc.And growing the team from 80 to 150 in one year. Set the engineering bar & best practices. Mentoring core team members. Responsible for all core business metrics.

Leading the architecture development of Machine Learning Platform(known as Michelangelo) at Uber. Our platform manages 1 billion+ records with choices of various learning algorithms for Regression, Ranking, Classification, Clustering, Time Series learning, Deep Learning, etc., powering critical ML modes with extremely high QPS for Eats Recommendation, Pricing, ETA prediction, Self-Driving Cars, and many more.Initially worked on Driver Growth team concentrating on the hyper growth of Uber with various engineering/ML approaches. Projects include: - Global Background Check management for Uber: manage the very sophisticated background check statuses/schedules for millions of drivers; hard complex system architecture/implementation - Intelligent Interactive Driver Onboarding to bring artificial intelligence to Uber's global onboarding process: Document classification, Image blurriness Detection, OCR, Natural Language UnderstandingSkill sets include ML, Python/Tornado, Java/Scala, SQL/Cassandra/Kafka, Hadoop/Spark, etc

Working in Yahoo! Labs on search ranking models(Yahoo Shopping, Yahoo News, etc).

Yahoo Research: Machine learning in computational advertising (see my WSDM '12 paper).Microsoft Research: Real-time question answering system. CHI 2011 Best Paper Award winner. Work has been released by Microsoft (http://go.microsoft.com/fwlink/?LinkId=213950).