🔹Main contributor to BigDL and Analytics Zoo to build large-scale AI applications for distributed big data- GitHub: https://github.com/intel-analytics/BigDL- Website: https://bigdl.readthedocs.io/🔹Successfully helped customers (MasterCard, Yahoo! JAPAN, Dangdang, China Telecom, Burger King, Microsoft Azure, Tencent, IQIYI, Glodwind etc.) work out end-to-end AI solutions (Recommendation, Natural Language Processing, Time Series Forecast, etc.) on big data platforms.🔹Selected Session Talks:- "Use Intel Analytics Zoo to build an intelligent QA Bot for Microsoft Azure" at Shanghai Spark+AI 15th meetup- "Real-time product recommendations leveraging deep learning on Apache Spark in Office Depot" at O'Reilly AI Conference Beijing 2019- "Analytics Zoo - Building Unified Big Data Analytics and AI Pipelines" at WAIC Developer Day 2019.- "Running Emerging AI Applications on Big Data Platforms with Ray On Apache Spark" at Spark + AI Summit 2020- "Context-aware Fast Food Recommendation with Ray on Apache Spark at Burger King" at Data + AI Summit Europe 2020- "Project Orca: Easily scaling Python AI pipelines on big data platforms" at PyConChina 2020- "Offer Recommendation System with Apache Spark at Burger King" at Data + AI Summit 2021- "Mobile Order Click-Through Rate (CTR) Recommendation with Ray on Apache Spark at Burger King" at Ray Summit 2021🔹Publications:BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster: https://arxiv.org/abs/2204.01715Context-Aware Drive-thru Recommendation Service at Fast Food Restaurants: https://arxiv.org/abs/2010.06197BigDL: A Distributed Deep Learning Framework for Big Data: https://arxiv.org/abs/1804.05839

• Independently developed an online demo system "C-Explorer" using JSP and Servlet under the supervision of Dr. Reynold C.K. Cheng in the Department of Computer Science.• "C-Explorer" supports community visualization and exploration on large attributed graphs as well as comparison analysis on different community retrieval algorithms.• VLDB Paper Demo Stream: http://www.vldb.org/pvldb/vol10/p1885-fang.pdf• Project website: http://cexplorer.cs.hku.hk:8080/Demo/ (Unfortunately this is not maintained any further...)

• Established a fully-functional web platform independently based on PHP Symfony framework according to business requirements to greatly simplify, record, trace and enhance the process of big data cleaning.• Encapsulated a Java API for data cleaning to identify whether an input field in Chinese is a name, organization or location by leveraging Stanford NLP libraries.• Conducted a presentation on JUnit usage summary.• Worked with the entire team to settle down the solution to further improve the existing software services and platforms.