Research Scientist at Meta.
Dr. Wang received his B.E. degree in Electrical Engineering from Shanghai Jiao Tong University in 2008 and his M.S. degree in Electrical and Computer Engineering from UT Austin in 2010.
He obtained his Ph.D. from the University of Texas at Austin in 2013, under the supervision of Dr. John X.J. Zhang at the Laboratory of Micro and Nano-scale Manipulation, Imaging and Sensing.
Patent №: 12253668 – Two-axis scanning mirror using piezoelectric drivers and looped torsion springs.
Embodiments provide a scanning mirror assembly with a 2D MEMS scanning mirror. It includes two pairs of piezoelectric electrodes connected via looped torsion springs, enabling rotation around two orthogonal axes.
Senior VP Equity Sales and Trading.
Patent №: 12254393 – Risk assessment of a container build.
An AI platform enables selective replacement of image layers in a container build. It processes a metadata file using NLP to generate vector representations, which are evaluated by ANNs for compliance, operability, and similarity. Non-compliant vectors are selectively replaced with compliant ones before provisioning the metadata file.
Wireless Technologies at Apple Inc.
Patent №: 12256357 – Multi-SIM UE capability indications and band conflict resolution.
Devices and methods for operating a DSDS UE with two SIMs are disclosed. The UE sends a connection request with capability indications over a first network. Upon receiving a connection accept message with network capability indications, the UE communicates with the base station accordingly.
Staff Research Engineer.
Mehdi Salehifar (Member, IEEE) received the B.Sc. degree in electrical and computer engineering from the University of Tehran, Tehran, Iran, in 2012, and the M.Sc. and Ph.D. degrees in electrical and computer engineering from the University of California, Santa Barbara, Santa Barbara, CA, USA, in 2014 and 2017, respectively.
Patent №: 12256103 – Image coding method based on secondary transform and device therefor. An image decoding method includes deriving transform coefficients via inverse quantization, applying inverse RST to obtain modified coefficients, and generating a reconstructed picture using an inverse primary transform. The modified coefficients are derived by applying a transform kernel matrix to 8 transform coefficients in a 4×4 block, yielding 16 modified coefficients.
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