CakeResume 找人才
進階搜尋
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
United States
就職中
全職 / 對遠端工作有興趣
10 到 15 年
National Tsing Hua University
・
Communication Engineering
Rabbi @Bend the Arc: Jewish Action in Southern California2007 ~ 現在
・
超過一年
Rabbi Aryeh Cohen Minneapolis Rabbi Aryeh Cohen, PhD, is a distinguished professor of Rabbinic Literature who has helped to shape the entire curriculum at the Ziegler School. In fact, he was Chair of the Rabbinics Department for over two decades. He created and taught most courses during his affiliation with the school. Aryeh Cohen is a Rabbi from Minneapolis . In this role, he organises the Jewish community around issues of immigration justice and restorative justice and mobilises a multi-faith community of clergy and laypeople to nonviolent direct action. His research , scholarship and teaching sit
兼職 / 對遠端工作有興趣
15 年以上
The School of Criticism and Theory at Dartmouth College
・
Advanced Judaic Studies
Senior Instructional Designer @Charter Communications2021 ~ 現在
・
Senior Instructional Designer
超過一年
mobile |address | 3150 Exacta Lane #734 Raleigh, NCemail | [email protected] Anthony Johnson Senior Instructional Designer Resourceful and innovative Instructional Designer with over 11 years of experience in e-learning and curriculum development for a wide variety of cultural and professional backgrounds. Offering insightful analysis of content and design to create value-added learning programs that achieve desired business outcomes. Strong communication and interpersonal skills to build relationships with stakeholders and assess learning needs. Anthony is recognized in Instructional Design, Needs Analysis, Adult Learning Theory, Curriculum Development etc. Raleigh, NC, USA Design Portfolio
全職 / 對遠端工作有興趣
10 到 15 年
Antonelli Institute
・
Art Education,Commercial ArtTeaching Assistant @Georgia Institute of Technology | The University of British Columbia2014 ~ 2019
・
PHD Student
超過一年
實習生 / 對遠端工作有興趣
6 到 10 年
The University of British Columbia
・
M.S. in GeophysicsHealth Economist/Process Improvement Specialist @Johns Hopkins Health System2019 ~ 現在
・
Senior Economist
超過一年
就職中
・
目前沒有興趣尋找新的機會
全職 / 對遠端工作有興趣
4 到 6 年
Johns Hopkins University
・
Business Analytics and Risk Managmenet, Health Care Management最輕量、快速的招募方案，數百家企業的選擇
搜尋履歷，主動聯繫求職者，提升招募效率。
- 瀏覽所有搜尋結果
- 每日可無限次數開啟陌生對話
- 搜尋僅開放付費企業檢視的履歷
- 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號，如果想濾掉中文字，需搭配雙引號使用 (-"人資")
UI designer -UX
職場能力評價定義
專業技能
該領域中具備哪些專業能力（例如熟悉 SEO 操作，且會使用相關工具）。
問題解決能力
能洞察、分析問題，並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對，並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法，且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序，有效運用時間，準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感，願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展，有效引領團隊採取行動，達成共同目標。
專業背景
目前狀態
求職階段
專業
產業
工作年資
管理經歷
技能
語言能力
求職偏好
希望獲得的職位
預期工作模式
期望的工作地點
遠端工作意願
接案服務
學歷
學校
主修科系
Chen LIU
Software Engineer at Microsoft
(+86) 15002933895
(+86) 59165119
Beijing, China
Skills
C/C++
Cosmos/C#/CX/Powershell/SQL
Algorithem/Data Structure/Design Pattern
Creative problem solving
Communication and Collaboration Skills
Education
Xidian University (2011 - 2014)
Master's Degree - Computer Software and Theory
Northwest University (2007 - 2011)
Bachelor's Degree - Computer Science and Technology
Experience
CHS Auto Correction on Mobile Device - Apr. 2014 - Jul. 2014
- A model could "guess" what key user may want to input on mobile device.
- The SIP(software input panel) on mobile is very small and user easily to mistype the key. Auto-Correction model is designed to address this problem.
- To achieve this goal, I set up this model based on some statistics result: the model was built based on TTR statistical data which record the position information of every user's input. Given a target key (a-z) on the SIP, I calculate the probabilities of every surrounding keys. I also give this model some capability of self-adaption to serve people who have different typing behaviour.
- This feature is default on in every windows mobile devices since Windows 10. Our telemetry data shows that this model improves the user's editing behaviour: higher selection rate and input speed, fewer deleting action.
CHS Shape Writing on Mobile Device - Aug. 2014 - Dec. 2014
- Code name "Blue Bird", provide a new input experience. User could swipe the input keys on the SIP to finish the input. It is different with hand writing, shape writing need to swipe all the keys on the Qwerty SIP. A group of people prefer to input via shape writing and they feel input this way could largely improve their typing speed.
- Chinese shape writing is different with Latin shape writing and it's more complex that Latin one. Chinese shape writing could input a word, a phrase and a sentence with only one gesture.
- This is the first version of CHS shape writing, I have no data to support such model. Thus, I build a rule-based model as our V1.0 Shape writing.
The model use Fréchet Distance to calculate the position similarity between user's gesture and standard one. Using cosine-based vector to calculate the shape similarity. Gain the probabilities of each calculated words path, put penalty to each syllable and do some pruning, finally get the ranked best path and phrases as the output to users.
Windows 10 upgrade in China - Dec. 2014 - Oct. 2015
- This is the top priority project in WDGC(Windows Device Group China) at that time. We called up as a virtual team to work together. The goal of this project is: the more devices upgrade to Windows 10 in China, the more we achieved.
- We cooperated with some local influential companies, like Tencent, Qihu360 and Baidu to help to promote the Windows 10. Basically, we provide the core solution and APIs to our partners, and they provide the user experience.
- Besides, we also need the manner to control the whole upgrade process, like enable/disable one partner, allot upgrade quota and online key distribution. To achieve this, I set up a azure cloud service to control the whole upgrade to make it safer and easily control. At last, I need to build a telemetry system in this whole procedure, not only collecting the numbers/categories, but also the dump/log files which could help us analyze the failure.
- This was a challenging project and very different with other projects we experienced. We all learn a lot from it.
Taihang Project - Oct. 2014 - Nov. 2015
- Code name "Taihang" is an updated version of "Kunlun". This is the core component of an IME, data source(DS). The DS is in charge of the conversion from Pinyin letters to Chinese characters.
- Before this project, we have two version of the main DS, one is in mobile and another is in desktop. This increase the maintaining and development cost. "Taihang" project is target to converge the DS from different planform and apply to all SKUs.
- The challenge here is: 1) apply one DS to different input stacks; 2) performance tuning; 3) feature parallel.
TSF2.0 IME stabilization - Dec. 2015 - Apr. 2016
- In this period, I mainly focused on the toughest issues in our products, most of them are performance or compatibility issues. This kind of bugs don't have solid reproduce steps or dump file to help analysis, basically, these came from user's feedback.
- To address them, need to add data points to collect more information, flight the build contained these data point and analysis the collected data to approach the root cause.
- Most of the issues were hidden in the system layer and finally, we addressed the pain points for users.
Live Sticker - Apr. 2016 - Oct. 2016
- Live sticker is a brand new concept to our IME which including the rich content and online service.
- Live Sticker provide to user the ability to input images(GIF, PNG, etc.) based on the context. IME retrieve the context from the edit control and query the online service to get the most popular images associate with the query string, display the result to user and insert into the edit control by clicking the picture.
- Additionally, to minimize the risk of this new thing, I add the cloud control to give us the capability to enable/disable this feature on specific applications.
TSF3.0 IME - Oct. 2016 - Nov. 2017
- TSF(Text Service Frame) is the layer between application, system and IME. Currently, Microsoft Chinese IME are built based on TSF2.0 on desktop and based on TSF2.9 on Mobile (close to TSF3.0, but not exact same). TSF3.0 is the next version of input stack and we are moving to this new framework. Our team is the pioneer on this because of some historical reasons and I was the driver on this project.
- A lot of communication across teams to discuss the design of the API, framework and dependencies, like what's the API surface looks like, how components communicate to each other, what's is the best sequences for each API call, etc. I need to build prototypes and verify different design to identify the potential risk earlier. Design and implement the API, host the IME, deploy it to different SKUs and make it self-hostable. We are currently at this stage.
Bing Advertisement Delivery Engine - Nov. 2017 - Present
- Delivery Engine (DE) is a large scale system including thousands of machines with different roles. It is the core component in the Bing Ads system. It's responsible for select the best ads which fits the user's queries.
- Building the distribution system which have the capability to handle the large amount of queries within quite low latency and stable performance.
- Design and implement advertiser and algorithm feature with high quality.
- Profiling and optimizing the system performance, including the memory, latency and capacity.
- Design and implement the machine function to calculate the relevance between query and keyword as a platform to improve the latency and accuracy.
- Re-architect the "dynamic ads" workflow which doubles the system capacity and reduce the latency.
- Design and implement the "Vertical ads" workflow to provide brand new user experience on Bing ads for Event, Tours and activities scenarios.
Self-Evaluation
- Enjoy learning new things and taking challenge
- Have passion on technology and learn quickly
- Happy to sharing and help others
Chen LIU
Software Engineer at Microsoft
(+86) 15002933895
(+86) 59165119
Beijing, China
Skills
C/C++
Cosmos/C#/CX/Powershell/SQL
Algorithem/Data Structure/Design Pattern
Creative problem solving
Communication and Collaboration Skills
Education
Xidian University (2011 - 2014)
Master's Degree - Computer Software and Theory
Northwest University (2007 - 2011)
Bachelor's Degree - Computer Science and Technology
Experience
CHS Auto Correction on Mobile Device - Apr. 2014 - Jul. 2014
- A model could "guess" what key user may want to input on mobile device.
- The SIP(software input panel) on mobile is very small and user easily to mistype the key. Auto-Correction model is designed to address this problem.
- To achieve this goal, I set up this model based on some statistics result: the model was built based on TTR statistical data which record the position information of every user's input. Given a target key (a-z) on the SIP, I calculate the probabilities of every surrounding keys. I also give this model some capability of self-adaption to serve people who have different typing behaviour.
- This feature is default on in every windows mobile devices since Windows 10. Our telemetry data shows that this model improves the user's editing behaviour: higher selection rate and input speed, fewer deleting action.
CHS Shape Writing on Mobile Device - Aug. 2014 - Dec. 2014
- Code name "Blue Bird", provide a new input experience. User could swipe the input keys on the SIP to finish the input. It is different with hand writing, shape writing need to swipe all the keys on the Qwerty SIP. A group of people prefer to input via shape writing and they feel input this way could largely improve their typing speed.
- Chinese shape writing is different with Latin shape writing and it's more complex that Latin one. Chinese shape writing could input a word, a phrase and a sentence with only one gesture.
- This is the first version of CHS shape writing, I have no data to support such model. Thus, I build a rule-based model as our V1.0 Shape writing.
The model use Fréchet Distance to calculate the position similarity between user's gesture and standard one. Using cosine-based vector to calculate the shape similarity. Gain the probabilities of each calculated words path, put penalty to each syllable and do some pruning, finally get the ranked best path and phrases as the output to users.
Windows 10 upgrade in China - Dec. 2014 - Oct. 2015
- This is the top priority project in WDGC(Windows Device Group China) at that time. We called up as a virtual team to work together. The goal of this project is: the more devices upgrade to Windows 10 in China, the more we achieved.
- We cooperated with some local influential companies, like Tencent, Qihu360 and Baidu to help to promote the Windows 10. Basically, we provide the core solution and APIs to our partners, and they provide the user experience.
- Besides, we also need the manner to control the whole upgrade process, like enable/disable one partner, allot upgrade quota and online key distribution. To achieve this, I set up a azure cloud service to control the whole upgrade to make it safer and easily control. At last, I need to build a telemetry system in this whole procedure, not only collecting the numbers/categories, but also the dump/log files which could help us analyze the failure.
- This was a challenging project and very different with other projects we experienced. We all learn a lot from it.
Taihang Project - Oct. 2014 - Nov. 2015
- Code name "Taihang" is an updated version of "Kunlun". This is the core component of an IME, data source(DS). The DS is in charge of the conversion from Pinyin letters to Chinese characters.
- Before this project, we have two version of the main DS, one is in mobile and another is in desktop. This increase the maintaining and development cost. "Taihang" project is target to converge the DS from different planform and apply to all SKUs.
- The challenge here is: 1) apply one DS to different input stacks; 2) performance tuning; 3) feature parallel.
TSF2.0 IME stabilization - Dec. 2015 - Apr. 2016
- In this period, I mainly focused on the toughest issues in our products, most of them are performance or compatibility issues. This kind of bugs don't have solid reproduce steps or dump file to help analysis, basically, these came from user's feedback.
- To address them, need to add data points to collect more information, flight the build contained these data point and analysis the collected data to approach the root cause.
- Most of the issues were hidden in the system layer and finally, we addressed the pain points for users.
Live Sticker - Apr. 2016 - Oct. 2016
- Live sticker is a brand new concept to our IME which including the rich content and online service.
- Live Sticker provide to user the ability to input images(GIF, PNG, etc.) based on the context. IME retrieve the context from the edit control and query the online service to get the most popular images associate with the query string, display the result to user and insert into the edit control by clicking the picture.
- Additionally, to minimize the risk of this new thing, I add the cloud control to give us the capability to enable/disable this feature on specific applications.
TSF3.0 IME - Oct. 2016 - Nov. 2017
- TSF(Text Service Frame) is the layer between application, system and IME. Currently, Microsoft Chinese IME are built based on TSF2.0 on desktop and based on TSF2.9 on Mobile (close to TSF3.0, but not exact same). TSF3.0 is the next version of input stack and we are moving to this new framework. Our team is the pioneer on this because of some historical reasons and I was the driver on this project.
- A lot of communication across teams to discuss the design of the API, framework and dependencies, like what's the API surface looks like, how components communicate to each other, what's is the best sequences for each API call, etc. I need to build prototypes and verify different design to identify the potential risk earlier. Design and implement the API, host the IME, deploy it to different SKUs and make it self-hostable. We are currently at this stage.
Bing Advertisement Delivery Engine - Nov. 2017 - Present
- Delivery Engine (DE) is a large scale system including thousands of machines with different roles. It is the core component in the Bing Ads system. It's responsible for select the best ads which fits the user's queries.
- Building the distribution system which have the capability to handle the large amount of queries within quite low latency and stable performance.
- Design and implement advertiser and algorithm feature with high quality.
- Profiling and optimizing the system performance, including the memory, latency and capacity.
- Design and implement the machine function to calculate the relevance between query and keyword as a platform to improve the latency and accuracy.
- Re-architect the "dynamic ads" workflow which doubles the system capacity and reduce the latency.
- Design and implement the "Vertical ads" workflow to provide brand new user experience on Bing ads for Event, Tours and activities scenarios.
Self-Evaluation
- Enjoy learning new things and taking challenge
- Have passion on technology and learn quickly
- Happy to sharing and help others