I am a resident of Taiwan that has a work visa in Hong Kong. Recently work in Taiwan for my former boss because of the Coronavirus outbreak. I have comprehensive experience in the IT industry, including more than 10 years of experience in C# and Python programming, 2 years of experience in education, and more than 5 years of experience in technical and product management. Expert in Blockchain, Conversational AI, Recommender System, Backend Development, Statistics and Data Analysis; experienced in Smart Contract, Chatbot, E-commerce, Streaming Media.
http://www.lionethan.com (My tech blog)
Taipei / Hong Kong / Shanghai
+886 986102885 / +852 59413067 / +86 18616532885
Company profile: We provide enterprises with a series of blockchain services, including smart contracts, platform development, and technical support. Focus on the research and development of decentralized financial solutions on Ethereum. And continue to introduce applications into various industries and diversified scenarios. Then provide safe and convenient decentralized financial applications for enterprises and the public with a friendly user interface and experience.
Reports to: Shareholder
See more: https://greendoge.dog/
Company profile: Xiaoi Robot is a leading developer of artificial intelligence technology and industry application platform. The company’s business cover communication, finance, government affairs, legal and medical services, and manufacturing, etc. The company’s clients include nearly one thousand large- and medium-sized enterprises and government institutions, hundreds of thousands of small enterprises and developers and more than 800 million end-users across the globe.
Job description: Serving as the head of the R&D team in Shanghai and Hong Kong (Asia Pacific Headquarters). The main products of the company are the Chinese version of iBot(chatbot framework). I am responsible for leading the team, applying Natural Language Processing and Deep Learning and integrating resources at the head office to develop iBot International (the multi-language version of iBot), iBot Express (the Chinese market version of iBot International), recommendation modules, support projects, and develop international standards ISO/IEC DIS 30150-1 Information technology - Affective computing user interface (AUI) - Part 1: Model.
Reports to: General Manager of Product R&D Center (Shanghai).
Company profile: M17 Entertainment and 17 Media were founded in 2017 and 2015, respectively. The companies are committed to enabling users around the world to host and watch live streaming. More than 50 million users worldwide have subscribed to the services.
Job description: Responsible for managing the Product Development Department of the E-Commerce Business Group; With the former head of operations of Shopee introduced and implemented KOL e-commerce to the live streaming. I established a Product Development Department (including PM, QA, SRE, Backend, Frontend, iOS, Android teams) cooperating with the former dozens of member grassroots entrepreneurship team of Shopee on developing and operating short video enhanced e-commerce, and researching the optimization and monetization of the recommender system. The E-Commerce Business Group was disbanded and downsizing company later in August due to the company’s failure to get listed on the NYSE in June.
Reports to: SVP
Company profile: LigerTech, a lean start-up Software company, was invested by the Shanghai film investment group in December 2015. GameTube, a game video enhanced e-commerce, was separated from its parent company LigerTech into an independent entity in May 2016.
Job description: Led a team and several contract remote staff to develop games, video enhanced e-commerce platforms, and recommender systems. From January to May 2017, assisted Xiaoi Robot to establish its Xiaoi Research institution in Taiwan, during which development was suspended and only maintained existing products. As a game video enhanced e-commerce company, GameTube developed a system that automatically crawled videos (including PVs and comments) from external sources, generated a lot of shopping pages with video, share those shopping pages to social networks, and sent legal cd-key of games when the user purchases. Originating from an internal project of LigerTech, the system allowed players to watch game videos and buy digital games offered by Steam, Origin, Uplay, Battle.net, Xbox, and PSN, etc.
Reports to: Board of directors
Company profile: Established in November 2013, IJOING Inc. is the first innovative mobile game company in Taiwan. The company is committed to resource integration of various mobile games and the cross-industry support for digital contents, as well as creating innovative services that cater to the needs of mobile game companies.
Job description: Responsible for leading a 6-member technical team and managing more than a dozen contracted game and app development teams, comprised of 50 to 100 members, to develop 2 apps, 5 games, 4 SDKs and a platform with recommender systems.
Reports to: CEO
Reports to: Partners, clients
See more: https://1drv.ms/f/s!Ah8lSEbxC5uwoulKUX-Y5hWbrfS0zA
A Context-aware and Social Graph based Restaurant Recommender System for Mobile Devices, 2012
With the increasing popularity of mobile devices and mobile networks, people can get a soaring amount of information, anywhere, anytime. How to solve the problem of the current information overload and provide personalized recommendation services is an important research topic. This thesis exploits the check-ins of Facebook Open Graph to design a mobile restaurant recommender system, which is based on collaborative filtering. The system summarizes the group preferences from individual users check-in in order to provide group recommendation services. Furthermore, the system considers social graph and contextual information to enhance the recommendation quality. This contextual information includes location, distance, age, sex index, time of day, weekday, month, number of companion and type of companion. In this thesis, we also proposed a method to evaluate the impact of location and distance context. Our experimental data is collected from the 69 volunteers in Facebook, which includes the 8264 check-ins. These check-ins are contributed by 3928 users in 2691 different restaurants from 2010/8/15 to 2012/4/30. The experimental results reveal that the accuracy of our system can be increased by approximately 38% while suggesting restaurants within the area of 3-5 km radius, compared to the popularity-based recommendation. It means that the proposed system can provide better recommendations than popularity-based recommendations if the user asks for a restaurant suggestion in a larger area.
Puzzle Dungeon mobile game, 2014
Addictive and New match-3 puzzle gameplay with classic dungeon crawling 3D RPG fun! Adventure in mystic dungeon, collect items and resources, and connect adjacent balls to fight with skeleton soldiers. Apply corresponding skills based on various circumstances will increase the chance to win. Legend has it that by defeating the final Skeleton King can you acquire the world's most valuable treasure. This game is developed by one person independently using Unity engine and C# language. The artist resources are purchased from stores such as Assets Store, and modified accordingly.
Information technology — Affective computing user interface (AUI) — Part 1: Model, 2019
ISO/IEC DIS 30150-1
Responsible for managing Dr. Hui Wang and other team members to develop the first international standard for Affective Computing. Affective computing individualizes user experience based on user needs and characteristics to achieve better outcomes.
It is important to consider affective characteristics of humans in the design and presentation of human-computer interactions. Affective computing builds a harmonious human-computer environment by enabling computing-based systems to recognize, interpret, and simulate human affects. Affective applications promise new insights into what people are feeling and can better serve their needs.
Limitations on affective computing include diverse affective characteristics currently used and the way to interpret and reply to these affective characteristics.
A general, standardized and systematic model is needed to facilitate applying affective computing within human-computer interaction regarding usability and accessibility.
This document presents a systematically defined model for affective computing user interfaces (AUI) and topics for AUI standardization. This can be important to eliminate obstacles lying between users and computing-based systems, and establish the core and foundation of affective computing user interface and its applications.