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Jaime Lien

from Mountain View, CA
Age ~41
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Also known as:
Jamie Lien
Phone and address:
1514 Canna Ct, Mountain View, CA 94043
Related to:
Larry J Mckee, 64
Connected to:
Andrew J Lien, 49Anh P Lien, 63Augustine Y Lien, 80Bich N Lien, 72Bryan D Lien, 39Cassandra C Lien, 47Chindy Lien, 36Clinton S Lien, 41Daniela Lien, 38Diana T Lien, 39

Jaime Lien Phones & Addresses

  • 1514 Canna Ct, Mountain View, CA 94043
  • Stanford, CA
  • Pasadena, CA
  • Cambridge, MA
  • Manhattan Beach, CA

Work

Company: Google Jul 2014 Position: Lead research engineer, project soli

Education

Degree: Doctorates, Doctor of Philosophy School / High School: Stanford University 2009 to 2016 Specialities: Electrical Engineering, Philosophy

Industries

Research

Resumes

Resumes

Jaime Lien Photo 1

Lead Research Engineer, Project Soli

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Location:
San Francisco, CA
Industry:
Research
Work:
Google
Lead Research Engineer, Project Soli
Stanford University 2009 - 2014
Graduate Research Fellow
Nasa Jet Propulsion Laboratory 2007 - 2009
Member of Technical Staff
Massachusetts Institute of Technology (Mit) 2005 - 2007
Graduate Research Assistant
Education:
Stanford University 2009 - 2016
Doctorates, Doctor of Philosophy, Electrical Engineering, Philosophy Massachusetts Institute of Technology 2005 - 2007
Masters, Master of Engineering, Electrical Engineering, Electrical Engineering and Computer Science, Computer Science, Engineering Massachusetts Institute of Technology 2001 - 2005
Bachelors, Bachelor of Science, Electrical Engineering

Publications

Us Patents

Cooperative Localization For Wireless Networks

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US Patent:
20080268873, Oct 30, 2008
Filed:
Oct 25, 2007
Appl. No.:
11/977754
Inventors:
Henk Wymeersch - Boston MA, US
Moe Z. Win - Framingham MA, US
Jaime Lien - Pasadena CA, US
International Classification:
H04Q 7/20
US Classification:
4554566
Abstract:
A system and corresponding method using a cooperative localization technique for self identifying a location of a wireless device in a wireless network is presented. The system may estimate an arbitrary signal metric as a function of a signal received by the wireless device from the at least one other wireless device in the wireless network. The system may also convert at least one belief representing a distribution of at least one possible location of the at least one other wireless device to generate at least one converted belief. The system may further determine a self-belief as a function of the at least one converted belief and identify a self location, as a function of the self-belief, within the wireless network.

Human And Gesture Sensing In A Computing Device

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US Patent:
20220302576, Sep 22, 2022
Filed:
Jun 24, 2020
Appl. No.:
17/616059
Inventors:
- Mountain View CA, US
David J. Weber - San Carlos CA, US
Jiang Zhu - Cupertino CA, US
Maryam Tabesh - San Francisco CA, US
Arnold Feldman - San Francisco CA, US
Jaime Lien - Mountain View CA, US
International Classification:
H01Q 1/24
G06F 3/01
H01Q 1/44
G01S 13/88
Abstract:
Devices are provided that include radar circuits arranged to send and receive radar signals that can be used to, for example, detect gestures performed in the vicinity of the device. Arrangements of the circuits and associated antennas allow for the device to have no bezel or a minimal bezel.

Radar-Enabled Sensor Fusion

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US Patent:
20210365124, Nov 25, 2021
Filed:
Aug 4, 2021
Appl. No.:
17/394241
Inventors:
- Mountain View CA, US
Carsten C. Schwesig - San Francisco CA, US
Jaime Lien - Mountain View CA, US
Patrick M. Amihood - San Francisco CA, US
Ivan Poupyrev - Sunnyvale CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 3/01
G01S 7/41
G01S 13/56
G01S 13/86
H04Q 9/00
G06K 9/00
G06K 9/62
G01S 13/88
G06F 21/32
G06F 3/0481
G01S 7/40
H04W 4/80
G06N 20/00
H04W 16/28
G01S 13/90
G06F 16/245
G06F 21/62
A63F 13/21
A63F 13/24
G01S 13/66
Abstract:
This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.

User-Customizable Machine-Learning In Radar-Based Gesture Detection

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US Patent:
20210326642, Oct 21, 2021
Filed:
Jun 29, 2021
Appl. No.:
17/361824
Inventors:
- Mountain View CA, US
Jaime Lien - Mountain View CA, US
Patrick M. Amihood - Palo Alto CA, US
Ivan Poupyrev - Los Altos CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06K 9/62
G06K 9/00
G06F 3/01
Abstract:
Various embodiments dynamically learn user-customizable input gestures. A user can transition a radar-based gesture detection system into a gesture-learning mode. In turn, the radar-based gesture detection system emits a radar field configured to detect a gesture new to the radar-based gesture detection system. The radar-based gesture detection system receives incoming radio frequency (RF) signals generated by the outgoing RF signal reflecting off the gesture, and analyzes the incoming RF signals to learn one or more identifying characteristics about the gesture. Upon learning the identifying characteristics, the radar-based gesture detection system reconfigures a corresponding input identification system to detect the gesture when the one or more identifying characteristics are next identified, and transitions out of the gesture-learning mode.

Mobile Device-Based Radar System For Providing A Multi-Mode Interface

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US Patent:
20210088643, Mar 25, 2021
Filed:
May 20, 2019
Appl. No.:
16/771647
Inventors:
- Mountain View CA, US
Vignesh Sachidanandam - Redwood City CA, US
Leonardo Giusti - San Francisco CA, US
Jaime Lien - Mountain View CA, US
Patrick M. Amihood - Palo Alto CA, US
Ivan Poupyrev - Los Altos CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G01S 13/42
G01S 13/88
G06F 3/01
Abstract:
This document describes techniques and systems that enable a mobile device-based radar system () for providing a multi-mode interface (). A radar field () is used to enable a user device () to accurately determine a presence or threshold movement of a user near the user device. The user device provides a multi-mode interface having at least first and second modes and providing a black display or a low-luminosity display in the first mode. The user device detects, based on radar data and during the first mode, a presence or threshold movement by the user relative to the user device and responsively changes the multi-mode interface from the first mode to the second mode. Responsive to the change to the second mode, the user device provides visual feedback corresponding to the implicit interaction by adjusting one or more display parameters of the black display or the low-luminosity display.

Low-Power Radar

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US Patent:
20210072375, Mar 11, 2021
Filed:
Nov 11, 2020
Appl. No.:
17/095558
Inventors:
- Mountain View CA, US
Abhijit Shah - Foster City CA, US
Jaime Lien - Mountain View CA, US
Hakim Kader Bhai Raja - San Francisco CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G01S 13/88
H04W 52/02
G01S 13/04
G01S 13/18
G01S 13/58
G01S 7/02
G01S 7/40
Abstract:
Techniques and apparatuses are described that enable low-power radar. The described techniques enable a radar system to reduce overall power consumption, thereby facilitating incorporation and utilization of the radar system within power-limited devices. Power consumption is reduced through customization of the transmission or processing of radar signals within the radar system. During transmission, different duty cycles, transmit powers, or framing structures can be utilized to collect appropriate data based on detected activity in an external environment. During processing, different hardware or different radar pipelines can be utilized to appropriately analyze the radar data. Instead of disabling the radar system, the described techniques enable the radar system to continuously monitor a dynamic environment and maintain responsiveness while conserving power.

Smart-Device-Based Radar System Detecting Human Vital Signs In The Presence Of Body Motion

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US Patent:
20200397310, Dec 24, 2020
Filed:
Feb 28, 2019
Appl. No.:
16/957991
Inventors:
- Mountain View CA, US
Jaime Lien - Mountain View CA, US
Jian Wang - Cupertino CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
A61B 5/0205
G01S 7/41
A61B 5/00
A61B 5/11
Abstract:
Techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting human vital signs in the presence of body motion. In particular, a radar system includes a body-motion filter module that employs machine learning to filter body motion from a received radar signal and construct a filtered signal that includes information regarding a user's vital signs. With machine learning, the radar system can filter the body motion without relying on data from other sensors to determine the body motion. Furthermore, the body-motion filter module can be trained to compensate for a variety of different types of body motions, such as those that occur while a user sleeps, exercises, drives, works, or is treated by a medical professional. By filtering the body motion, the radar system can accurately determine the user's vital signs and provide non-contact human vital-sign detection.

Smart-Device-Based Radar System Detecting User Gestures In The Presence Of Saturation

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US Patent:
20200400811, Dec 24, 2020
Filed:
Feb 28, 2019
Appl. No.:
16/772566
Inventors:
- Mountain View CA, US
Jaime Lien - Mountain View CA, US
Nicholas Edward Gillian - Palo Alto CA, US
Jian Wang - Cupertino CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G01S 13/58
G01S 13/62
G01S 13/08
G01S 7/48
G01S 7/41
G06F 3/01
Abstract:
Techniques and apparatuses are described that implement a smart-device-based radar system capable of detecting user gestures in the presence of saturation. In particular, a radar system employs machine learning to compensate for distortions resulting from saturation. This enables gesture recognition to be performed while the radar system 's receiver is saturated. As such, the radar system can forgo integrating an automatic gain control circuit to prevent the receiver from becoming saturated. Furthermore, the radar system can operate with higher gains to increasing sensitivity without adding additional antennas. By using machine learning, the radar system 's dynamic range increases, which enables the radar system to detect a variety of different types of gestures having small or large radar cross sections, and performed at various distances from the radar system
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Jaime Lien from Mountain View, CA, age ~41 Get Report