Edward H Baik

59637064, Oct 5, 1999

Oct 23, 1997

8/956750

Edward Hyeen Baik - Laguna Hills CA

H02P 506

388804

The motor control system is operable with multi-phase bipolar parallel winding brushless DC motor. The motor control system includes multi-phase bipolar H-bridge circuits which change current flow direction as the output signal from motor encoder changes. The motor control system is responsive to the speed control circuit to control speed and to the fault detection circuit to give maximum safety and control. The motor control system provides controlled phase signal to individually enable each phase of the stator windings to selectively control the speed of the motor. The motor control system also has a conventional pulse width modulation driver for providing power to the motor. The motor control system of the present invention utilizes both modes to fully utilize the motor's capabilities and at the same time saves power and reduces loading in each of the H-bridges driving stator windings.

20190186939, Jun 20, 2019

Dec 20, 2017

15/848851

- San Jose CA, US
Gautam Muralidhar - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Edward H. Baik - Mountain View CA, US
Marzieh Parandehgheibi - San Jose CA, US
Abhishek Singhal - Santa Clara CA, US

G01C 21/34
G06N 99/00
G06N 5/04
G05D 1/00

Systems of an autonomous vehicle and the operations thereof are provided. The vehicle can predict a user's trip using his or her history of past trips, the relevant context, and the current environmental conditions. The navigation system of the vehicle can use historical GPS data, defined by the sequence of position measurements, of a given vehicle to determine frequently visited locations. Then, the navigation system may augment the learned knowledge of frequently visited locations and routes with the relevant context and environmental conditions to make recommendations on the locations the user is most likely to visit and the route most likely to drive on. More specifically, the navigation system can automatically cluster historical trips by similarity (e.g., trips with similar contexts and/or environmental conditions), while identifying, mitigating, and/or eliminating the potential for statistical outliers (trips taken by a driver that are infrequent and thus less useful for predicting future trips).

20190130038, May 2, 2019

Oct 30, 2017

15/797775

- San Jose CA, US
Christopher Li - Sunnyvale CA, US
Zhou Xing - San Jose CA, US
Marzieh Parandehgheibi - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Nilesh V. Kulkarni - Saratoga CA, US
Abhishek Singhal - Santa Clara CA, US
Edward H. Baik - Mountain View CA, US
Lisa E. Falkson - Los Altos CA, US

G06F 17/30
G06F 17/27

A network crawler crawls one or more media sites to extract a plurality of titles for information contained in the one or more media sites. For example, the network crawler may extract the titles on the one or more media sites by identifying different computer formats and converting the titles in the different computer formats into a common computer format for comparison. User profiles which, includes user's interest are stored in a user profile interest database. A novel personalized news recommendation engine recommends news similar to the interest specified in a user profile, where maximum weighted matching is applied to score the similarity of news against user interest in the word2vec space.

20180141568, May 24, 2018

Dec 30, 2016

15/395924

- San Jose CA, US
Gautam Muralidhar - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Edward H. Baik - Mountain View CA, US
Jonathan A. Cox - San Jose CA, US

B60W 50/08
B60W 40/09
G05D 1/00
G05D 1/02
B60W 50/00
A61B 5/18
A61B 5/16
A61B 5/024
A61B 5/08
A61B 5/01

Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The level of comfort with autonomous driving offered to the user and the parameters of operation of the autonomous vehicle might increase or decrease a driver's comfort (anxiety) with the vehicle. Sensors in the vehicle can detect a user's driving style, comfort level and may propose an autonomy level to the user and/or parameters of operation.

20180143639, May 24, 2018

Dec 30, 2016

15/395952

- San Jose CA, US
Gautam Muralidhar - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Edward H. Baik - Mountain View CA, US
Jonathan A. Cox - San Jose CA, US

G05D 1/02
G01C 21/34
G01C 21/36

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.