Search

Masoud Abbaszadeh

from Clifton Park, NY
Age ~47
Get Report
Also known as:
Masoud D
Phone and address:
2 Dawson Ln, Clifton Park Center, NY 12065
Connected to:
Ali A Abbaszadeh, 69Hamid Abbaszadeh, 60Shirin Abbaszadeh, 51Francis P Abbatangelo, 49Kristin Abbatantuono, 43Adrienne Abbate, 50Alice D Abbate, 58Ann A Abbate, 89April Abbate, 46Charlotte A Abbate, 84

Masoud Abbaszadeh Phones & Addresses

  • 2 Dawson Ln, Clifton Park, NY 12065
  • Glenville, NY
  • Manchester, CT

Work

Company: Ge research May 2020 Position: Principal research engineer

Education

Degree: Doctorates, Doctor of Philosophy School / High School: University of Alberta 2004 to 2008

Skills

Simulations • Control Systems Design • Simulink • Signal Processing • Matlab • Mathematical Modeling • Algorithms • Numerical Analysis • Optimization • Programming • Embedded Systems • Robotics • Latex • Process Control • Control Theory • Instrumentation • Automation • R&D • Dynamical Systems • Electrical Engineering • Software Development • Systems Engineering • Electronics • Maple • C • Machine Learning • Digital Signal Processors • Testing • Labview • Plc • Modeling • Fortran • Mathematica • System Automation • Optimizations • Kalman Filtering • Image Processing • Sensors • Applied Mathematics • Xilinx • Computer Vision • Artificial Intelligence • Mechatronics • Estimation • Filtering • Computation • Content Filtering • Project Estimation • Pattern Recognition • Symbolic Computation

Ranks

Certificate: Cpr & Aed

Interests

Civil Rights and Social Action • Education • Science and Technology • Human Rights • Health

Industries

Research

Resumes

Resumes

Masoud Abbaszadeh Photo 1

Principal Research Engineer

View page
Location:
Schenectady, NY
Industry:
Research
Work:
Ge Research
Principal Research Engineer
Ieee
Associate Editor - Ieee Transactions on Control Systems Technology
Ge Global Research
Senior Research Scientist - Technical Lead
Ge Global Research Feb 2013 - Apr 2019
Lead Control Systems Engineer
Ieee Feb 2013 - Apr 2019
Conference Editorial Board Member - Ieee Control Systems Society
Education:
University of Alberta 2004 - 2008
Doctorates, Doctor of Philosophy Sharif University of Technology 2000 - 2002
Master of Science, Masters Amirkabir University of Technology - Tehran Polytechnic 1996 - 2000
Bachelors, Bachelor of Science, Electronics
Skills:
Simulations
Control Systems Design
Simulink
Signal Processing
Matlab
Mathematical Modeling
Algorithms
Numerical Analysis
Optimization
Programming
Embedded Systems
Robotics
Latex
Process Control
Control Theory
Instrumentation
Automation
R&D
Dynamical Systems
Electrical Engineering
Software Development
Systems Engineering
Electronics
Maple
C
Machine Learning
Digital Signal Processors
Testing
Labview
Plc
Modeling
Fortran
Mathematica
System Automation
Optimizations
Kalman Filtering
Image Processing
Sensors
Applied Mathematics
Xilinx
Computer Vision
Artificial Intelligence
Mechatronics
Estimation
Filtering
Computation
Content Filtering
Project Estimation
Pattern Recognition
Symbolic Computation
Interests:
Civil Rights and Social Action
Education
Science and Technology
Human Rights
Health
Certifications:
Cpr & Aed
First Aid
Lean Six Sigma Green Belt Dmaic-Dfss
Jet Engine and Propulsion Systems For Engineers
American Heart Association
Ge Global Research

Publications

Us Patents

System And Method For Cyberattack Detection In A Wind Turbine Control System

View page
US Patent:
20220345468, Oct 27, 2022
Filed:
Apr 21, 2021
Appl. No.:
17/236638
Inventors:
- Schenectady NY, US
Zhaoyuan Yang - Schenectady NY, US
Masoud Abbaszadeh - Clifton Park NY, US
Fernando Javier D'Amato - Niskayuna NY, US
Hema Kumari Achanta - Schenectady NY, US
International Classification:
H04L 29/06
G06N 20/00
G06N 5/04
Abstract:
A method for detecting a cyberattack on a control system of a wind turbine includes providing a plurality of classification models of the control system. The method also includes receiving, via each of the plurality of classification models, a time series of operating data from one or more monitoring nodes of the wind turbine. The method further includes extracting, via the plurality of classification models, a plurality of features using the time series of operating data. Each of the plurality of features is a mathematical characterization of the time series of operating data. Moreover, the method includes generating an output from each of the plurality of classification models and determining, using a decision fusion module, a probability of the cyberattack occurring on the control system based on a combination of the outputs. Thus, the method includes implementing a control action when the probability exceeds a probability threshold.

Systems And Methods For Controlling An Industrial Asset In The Presence Of A Cyber-Attack

View page
US Patent:
20220334540, Oct 20, 2022
Filed:
Apr 14, 2021
Appl. No.:
17/229934
Inventors:
- Schenectady NY, US
Mustafa Tekin Dokucu - Latham NY, US
Kalpesh Singal - Ballston Spa NY, US
Masoud Abbaszadeh - Clifton Park NY, US
Karla Kvaternik - Schenectady NY, US
Georgios Boutselis - Niskayuna NY, US
International Classification:
G05B 15/02
G06F 21/55
G06F 9/455
G06N 20/00
Abstract:
Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.

Systems And Methods For Controlling An Industrial Asset In The Presence Of A Cyber Attack

View page
US Patent:
20230126087, Apr 27, 2023
Filed:
Oct 25, 2021
Appl. No.:
17/509159
Inventors:
- Schenectady NY, US
Fernando Javier D'Amato - Niskayuna NY, US
Masoud Abbaszadeh - Clifton Park NY, US
International Classification:
G06F 21/55
G05B 19/045
Abstract:
Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, an interceptor module receives a state-change instruction from a state module that directs a change from a first state condition to a second state condition. The first and second state conditions direct modes of operation of at least one sub module of the controller of the industrial asset. The interceptor module then correlates the state-change instruction to a state-change classification. Based on the state-change classification, the interceptor module identifies an indication of a mode-switching attack. In response to the identification of the mode-switching attack, at least one mitigation response is implemented.

Systems And Methods For Node Selection And Ranking In Cyber-Physical Systems

View page
US Patent:
20230093713, Mar 23, 2023
Filed:
Sep 20, 2021
Appl. No.:
17/479370
Inventors:
- Schenectady NY, US
Masoud ABBASZADEH - Clifton Park NY, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
G06F 21/57
G06F 16/2457
Abstract:
The present application describes techniques for node selection and ranking for, e.g., attack detection and localization in cyber-physical systems, without relying on digital twins, computer models of assets, or operational domain expertise. The described techniques include obtaining an input dataset of values for a plurality of nodes (e.g., sensors, actuators, controllers, software nodes) of industrial assets, computing a plurality of principal components (PCs) for the input dataset according to variance of values for each node, computing a set of common weighted PCs based on the plurality of PCs according to variance of each PC, and ranking each node based on the node's contribution to the set of common weighted PCs.

Systems And Methods For Cyber-Fault Detection

View page
US Patent:
20230071394, Mar 9, 2023
Filed:
Aug 19, 2021
Appl. No.:
17/406205
Inventors:
- Schenectady NY, US
Masoud ABBASZADEH - Clifton Park NY, US
Georgios BOUTSELIS - Niskayuna NY, US
Joel MARKHAM - Niskayuna NY, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
G05B 23/02
G06F 16/23
G08B 29/18
Abstract:
The present disclosure relates to techniques for detecting cyber-faults in industrial assets. Such techniques may include obtaining an input dataset from a plurality of nodes of industrial assets and predicting fault nodes in the plurality of nodes by inputting the input dataset to a one-class classifier. The one-class classifier may be trained on normal operation data obtained during normal operations of the industrial assets. Further, the cyber-fault detection techniques may include computing a confidence level of cyber fault detection for the input dataset using the one-class classifier and adjusting decision thresholds based on the confidence level for categorizing the input dataset as normal or including cyber-faults. The predicted fault nodes and the adjusted decision thresholds may be used for detecting cyber-faults in the plurality of nodes of the industrial assets.

Systems And Methods For Self-Adapting Neutralization Against Cyber-Faults

View page
US Patent:
20230075736, Mar 9, 2023
Filed:
Aug 19, 2021
Appl. No.:
17/406246
Inventors:
- Schenectady NY, US
Masoud ABBASZADEH - Clifton Park NY, US
Georgios BOUTSELIS - Niskayuna NY, US
Joel MARKHAM - Niskayuna NY, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
G06F 21/54
G06F 21/55
G06F 21/57
G05B 19/048
Abstract:
The present disclosure provides techniques for implementing self-adapting neutralization against cyber-faults within industrial assets. The disclosed neutralization techniques may include obtaining an input dataset from a plurality of nodes of industrial assets and reconstructing compromised nodes in the plurality of nodes to neutralize cyber-faults detected based on the input dataset. A confidence metric may be computed for the reconstruction of the compromised nodes, e.g., using inductive conformal prediction. Based on the confidence metric and the reconstruction of the compromised nodes, input signals from the reconstruction of the compromised nodes may be transformed, or configuration parameters for a controller of the industrial assets may be tuned.

Graceful Neutralization Of Industrial Assett Attack Using Cruise Control

View page
US Patent:
20210211455, Jul 8, 2021
Filed:
Jan 6, 2020
Appl. No.:
16/734499
Inventors:
- Schenectady NY, US
Masoud Abbaszadeh - Clifton Park NY, US
Mustafa Tekin Dokucu - Latham NY, US
International Classification:
H04L 29/06
Abstract:
A procedure for neutralizing an attack on a control system of an industrial asset includes detecting an anomaly in a first sensor node associated with a first unit operating in a first operational mode, and receiving time series data associated with the first sensor node. A subset of the time series data is provided to each of a plurality of virtual sensor models A first virtual sensor model is selected from among a plurality of virtual sensor models based upon the subset of the time series data received by each of the plurality of virtual sensor models. A first confidence level of the first virtual sensor is determined. Responsive to determining that the first confidence level is below a first confidence level threshold, the first unit is transferred to a second operational mode using sensor readings associated with a second sensor node of a second unit of the industrial asset.

Virtual Sensor Supervised Learning For Cyber-Attack Neutralization

View page
US Patent:
20210126943, Apr 29, 2021
Filed:
Oct 29, 2019
Appl. No.:
16/666807
Inventors:
- Schenectady NY, US
Masoud Abbaszadeh - Clifton Park NY, US
Mustafa Tekin Dokucu - Latham NY, US
International Classification:
H04L 29/06
G06K 9/62
Abstract:
An industrial asset may have monitoring nodes that generate current monitoring node values. A dynamic, resilient estimator may split a temporal monitoring node space into normal and one or more abnormal subspaces associated with different kinds of attack vectors. According to some embodiments, a neutralization model is constructed and trained for each attack vector using supervised learning and the associated abnormal subspace. In other embodiments, a single model is created using out-of-range values for abnormal monitoring nodes. Responsive to an indication of a particular abnormal monitoring node or nodes, the system may automatically invoke the appropriate neutralization model to determine estimated values of the particular abnormal monitoring node or nodes (e.g., by selecting the correct model or using out-of-range values). The series of current monitoring node values from the abnormal monitoring node or nodes may then be replaced with the estimated values.
Control profile
Masoud Abbaszadeh from Clifton Park, NY, age ~47 Get Report