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Sheng YangChicago, IL

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Chicago, IL

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Resumes

Sheng Yang Photo 46

Senior Quantitative Strategist At Kapital Trading Llc

Location:
Greater Chicago Area
Industry:
Investment Management
Sheng Yang Photo 47

Sheng Yang

Work:
College of Saint Benedict and Saint John’s University
Csb Media Services Student Employee Mcdonald's Corporation Jun 2015 - Aug 2015
Crew Member College of Saint Benedict and Saint John’s University Aug 2014 - May 2015
Gorecki Dining Service Student Employee Supervalu Aug 2014 - May 2015
Education:
Saint John's University 2014 - 2018
Bachelors, Political Science and Government, Political Science, Government Saint Paul, Central High School 2010 - 2014
Skills:
Microsoft Office, Management, Microsoft Excel, Leadership, Microsoft Word, Powerpoint, Research, Training, Social Listening, Critical Thinking, Strategic Planning, Analysis, Creativity Skills, Cultural Awareness, Wordpress, Imovie, Sony Camcorders, Sony Hdv, Canon Cameras, Customer Service
Interests:
Children
Civil Rights and Social Action
Politics
Environment
Education
Poverty Alleviation
Human Rights
Animal Welfare
Arts and Culture
Health
Languages:
English
Mandarin
Sheng Yang Photo 48

Sheng Chuen Yang

Sheng Yang Photo 49

Sheng Yang

Sheng Yang Photo 50

Sheng Yang

Location:
United States
Sheng Yang Photo 51

Sheng Yang

Location:
United States
Sheng Yang Photo 52

Accounting Professional

Location:
Greater Chicago Area
Industry:
Accounting
Education:
Loyola University of Chicago - Graduate School of Business

Publications & IP owners

Us Patents

Scheduling Jobs On Interruptible Cloud Computing Instances

US Patent:
2022037, Nov 24, 2022
Filed:
May 19, 2021
Appl. No.:
17/324692
Inventors:
- San Jose CA, US
Sunav Choudhary - Kolkata, IN
Sheng Yang - Evanston IL, US
Kanak Vivek Mahadik - San Jose CA, US
Samir Khuller - Silver Spring MD, US
Assignee:
Adobe Inc. - San Jose CA
International Classification:
G06F 9/50
G06F 9/48
Abstract:
Techniques are provided for scheduling multiple jobs on one or more cloud computing instances, which provide the ability to select a job for execution from among a plurality of jobs, and to further select a designated instance from among a plurality of cloud computing instances for executing the selected job. The job and the designated instance are each selected based on a probability distribution that a cost of executing the job on the designated instance does not exceed the budget. The probability distribution is based on several factors including a cost of prior executions of other jobs on the designated instance and a utility function that represents a value associated with a progress of each job. By scheduling select jobs on discounted cloud computing instances, the aggregate utility of the jobs can be maximized or otherwise improved for a given budget.

Possible Relatives

David Yang  A Yang  Deborah L Yang  Daniel P Yang  Dee T Yang  Denise K Yang  Danny W Yang  Sheng Q Ling  Sheng J Lo  Sheng Thao 

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