About
Activity
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Amazing day at #SIGGRAPH getting to see Jensen interviewing Zuck!
Amazing day at #SIGGRAPH getting to see Jensen interviewing Zuck!
Liked by Edward Mehr
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Why is it hard to improve US manufacturing? Think of high-mix manufacturing as a complex web of interdependent operations. Each part can improve with…
Why is it hard to improve US manufacturing? Think of high-mix manufacturing as a complex web of interdependent operations. Each part can improve with…
Shared by Edward Mehr
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If you’ve been paying attention to our engine tests, you probably noticed this already, but very excited we can now talk about this! WAAM on…
If you’ve been paying attention to our engine tests, you probably noticed this already, but very excited we can now talk about this! WAAM on…
Liked by Edward Mehr
Experience & Education
Licenses & Certifications
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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
Credential ID C7SRBY89JL7L
Patents
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Part forming using intelligent robotic system
Issued US11865716B2
A system forms a part in an initial geometry (e.g., a sheet) into a desired geometry. The system includes a robot arm with an end effector, a model and a controller. The model receives an input geometry and an input parameter value indicating an interaction between the part and the end effector. The model determines an output geometry of the part based on the input geometry and the input parameter value. The controller receives the initial and desired geometries; applies the model to the…
A system forms a part in an initial geometry (e.g., a sheet) into a desired geometry. The system includes a robot arm with an end effector, a model and a controller. The model receives an input geometry and an input parameter value indicating an interaction between the part and the end effector. The model determines an output geometry of the part based on the input geometry and the input parameter value. The controller receives the initial and desired geometries; applies the model to the initial geometry and to different input parameter values; based on output geometries of the model, determines a set of parameter values for controlling the robot arm; and controls the robot arm according to the determined set of parameter values to form the part into the desired geometry using the end effector.
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Real-time adaptive control of additive manufacturing processes using machine learning
Filed US US20180341248A1
Machine learning-based methods and systems for automated object defect classification and adaptive, real-time control of additive manufacturing and/or welding processes.
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Method and apparatus for geographic location based electronic security management
Filed US US20170195339A1
Systems, methods and computer readable media for facilitating an authentication process validating the location of a first device, for example, using a second device, before authorizing an action An example apparatus may be configured to receive a request to cause an action from a first device, cause the first device to communicate with a second device to verify a proximity of the first device and the second device, receive verification of the proximity, receive a first identifying data string,…
Systems, methods and computer readable media for facilitating an authentication process validating the location of a first device, for example, using a second device, before authorizing an action An example apparatus may be configured to receive a request to cause an action from a first device, cause the first device to communicate with a second device to verify a proximity of the first device and the second device, receive verification of the proximity, receive a first identifying data string, receive a second identifying data string, and upon confirmation of a match of the first identifying data string and the second identifying data string, authorizing the action.
Languages
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English
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Persian
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Arabic
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More activity by Edward
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🙏 Thanks to Jim Beretta and the Robot Industry Podcast for bringing on our CEO Saman Farid as a guest to discuss the exciting changes that are…
🙏 Thanks to Jim Beretta and the Robot Industry Podcast for bringing on our CEO Saman Farid as a guest to discuss the exciting changes that are…
Liked by Edward Mehr
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