Search

Ling Liu Shen

from Lawrenceville, NJ
Age ~62
Get Report
Also known as:
Lin G Shen, Shen Ling, Ling Liu
Related to:
Yingyun Y Liu, 54
Connected to:
Aileen C Shen, 41Audrey S Shen, 88Bai Shen, 41Bao Z Shen, 74Beiyi Shen, 44Bella M Shen, 75Beverly G Shen, 41Billy Shen, 82Bingxin Shen, 41Caroline Shen, 74

Ling Shen Phones & Addresses

  • Lawrenceville, NJ
  • 736 Chanticleer, Cherry Hill, NJ 08003 (856) 751-1854
  • 736 Chanticleer APT 736, Cherry Hill, NJ 08003
  • Voorhees, NJ
  • Maple Shade, NJ
  • State College, PA
  • Plainsboro, NJ
  • 736 Chanticleer, Cherry Hill, NJ 08003

Resumes

Resumes

Ling Shen Photo 1

Ling Shen

View page
Position:
Engineer at Siemens Corporation, Corporate Technology
Location:
United States
Industry:
Industrial Automation
Work:
Siemens Corporation, Corporate Technology since Nov 1998
Engineer
Siemens Corporate Research 2009 - 2011
Software Engineer
Nanjing University Aug 1987 - May 1992
Instructor in Mathematics Department
Education:
Masters in Applied Mathematics, Nanjing University 1981 - 1984
Master of Arts, Partial Differential Equations
Ling Shen Photo 2

Ling Shen

View page
Location:
United States
Ling Shen Photo 3

Director At Spain

View page
Location:
United States
Industry:
Electrical/Electronic Manufacturing
Ling Shen Photo 4

Ling Shen

View page
Location:
United States
Ling Shen Photo 5

Ling Shen

View page
Ling Shen Photo 6

Ling Shen

View page

Publications

Us Patents

Method And System For Energy Control Management

View page
US Patent:
20140074306, Mar 13, 2014
Filed:
Sep 17, 2012
Appl. No.:
14/115888
Inventors:
Yan Lu - West Windsor NJ, US
Ling Shen - Cherry Hill NJ, US
Jianmin Zhu - Piscataway NJ, US
Assignee:
SIEMENS CORPORATION - Iselin NJ
International Classification:
G05B 13/04
G06F 17/50
US Classification:
700291, 703 2
Abstract:
In order to reduce computation time and cost involved with determining one or more optimal parameters for a pre-cooling strategy, for a modeled system, a two-step genetic algorithms is used to optimize energy consumption of the modeled system with respect to cost of the energy consumption. A first step of the two-step genetic algorithms determines a population of potential solutions that are used to initialize a second step of the two-step genetic algorithm. The second step of the two-step genetic algorithm determines the one or more optimal parameters for the pre-cooling strategy from the population output by the first genetic algorithm.

Big Automation Code

View page
US Patent:
20220198269, Jun 23, 2022
Filed:
Feb 5, 2019
Appl. No.:
17/425990
Inventors:
- Munich, DE
Palash Goyal - Los Angeles CA, US
Jason Vandeventer - Charlotte NC, US
Ling Shen - Cherry Hill NJ, US
International Classification:
G06N 3/08
G06F 8/30
G06F 8/41
Abstract:
A system and method to apply deep learning techniques to an automation engineering environment are provided. Big code files and automation coding files are retrieved by the system from public repositories and private sources, respectively. The big code files include examples general software structure examples to be utilized by the method and system to train advanced automation engineering software. The system represents the coding files in a common space as embedded graphs which a neural network of the system uses to learn patterns. Based on the learning, the system can predict patterns in the automation coding files. From the predicted patterns executable automation code may be created to augment the existing automation coding files.

Functional Visualization In System-Level Multi-Domain Simulators

View page
US Patent:
20150302640, Oct 22, 2015
Filed:
Apr 16, 2015
Appl. No.:
14/688189
Inventors:
- Leuven, BE
Ling Shen - Cherry Hill NJ, US
International Classification:
G06T 17/00
G06F 17/50
Abstract:
A functional visualization of high-level system variables is based on information from a simulation environment. A functional model is imported from the simulation environment, including function nodes and connections. Each function node includes a function name, an associated component from the simulated system, and an associated physical variable. Each connection includes source and destination functions and a connection type. Values for the physical variables are obtained via a subscription with the simulation environment. The functional visualization is created and displayed based on the functional model and the values.

On-Line Optimization Scheme For Hvac Demand Response

View page
US Patent:
20150253027, Sep 10, 2015
Filed:
Oct 10, 2013
Appl. No.:
14/433860
Inventors:
- Orlando FL, US
Ling Shen - Cherry Hill NJ, US
Jianmin Zhu - Piscataway NJ, US
Assignee:
Siemens Corporation - Orlando FL
International Classification:
F24F 11/00
G05B 13/02
Abstract:
A computer-implemented method of optimizing demand-response (DR) of a heating, ventilation, and air-conditioning (HVAC) system of a building, includes determining () a value of an objective function Fof a HVAC system for each of a plurality of DR strategies j for each of a plurality of weather patterns i that is a weighted sum of an energy cost of the HVAC system and a thermal comfort loss of the HVAC system, assigning () a likelihood score Lto each of a selected subset of near-optimal DR strategies j for each weather pattern i, and selecting () those near-optimal DR strategies with large overall likelihood scores Lto create an optimal strategy pool of DR strategies. An optimal strategy pool can be searched () in real-time for an optimal DR strategy for a given weather pattern.
Control profile
Ling Liu Shen from Lawrenceville, NJ, age ~62 Get Report