Pengju (PJ) Shang

Pengju (PJ) Shang is an associate in the Intellectual Property Practice Group in the firm's Silicon Valley office.

Areas of Practice

PJ works on a variety of intellectual property matters, including patent prosecution, strategic portfolio development and client counseling. With his academic and industrial experience, PJ prepares and prosecutes patent applications covering a wide range of technology fields, including microprocessor architecture, hardware and software solutions for accelerating Al training and inferencing, sparse Al accelerators, GNN accelerators, Al-based drug discovery, machine learning, artificial intelligence, blockchain, cloud computing, distributed filesystem, storage system, social media, and Internet communication.

In his previous career as a software engineer, PJ was trained to design and develop complex technical inventions during his tenure at Google with cloud/platform team, and at EMC with storage filesystem team. As an inventor, PJ received numerous granted patents from United States Patent & Trademark Office (USPTO).

PJ’s academic background includes a Ph.D degree in Computer Engineering and Computer Architecture in the US. During his Ph.D study, PJ authored a list of conference publications and journal publications covering research fields including large-scale data management, cloud, database, file/storage system, machine learning, power efficient and high-performance computing.

Articles

Intellectual Property Law Blog Posts

• "Protecting Semiconductor Chip Design under the Semiconductor Chip Protection Act of 1984 (SCPA) – Part II (Infringement and Defense)," January 11, 2023

• "Protecting Semiconductor Chip Design under the Semiconductor Chip Protection Act of 1984 (SCPA) – Part I (Registration and Inspection)," January 11, 2023
• "Patent Protection on AI Inventions," August 30, 2021

Publications

• Co-Author, "TRAID: Exploiting Temporal Redundancy and Spatial Redundancy to Boost Transaction Processing Systems Performance," IEEE Transactions on Computers, Vol. 61, No. 4, pp 517-530, April 2012
• Co-Author, "Supporting HPC Analytics Applications with Access Patterns using Data restructuring and Data-centric scheduling techniques in MapReduce," IEEE Transactions on Parallel and Distributed Systems, March 7, 2012. IEEE Computer Society Digital Library.
• Co-Author, "A New Placement-ideal Layout for Multi-way Replication Storage System," IEEE Transactions on Computers 60(8): 1142-1156, 2011
• Co-Author, "A Novel Power management for CMP Systems in Data-intensive Environment," The 25th IEEE International Parallel & Distributed Processing Symposium (IPDPS) May 16-20, 2011, Anchorage (Alaska) USA. (Acceptance rate 20% 112/571)
• Co-Author, "A Scalable Reverse Lookup Scheme using Group-based Shifted Declustering Layout," The 25th IEEE International Parallel & Distributed Processing Symposium May 16-20, 2011, Anchorage (Alaska) USA. (Acceptance rate 20% 112/571).
• Co-Author, "Nexus: A Novel Weighted-Graph-based Prefetching Algorithm for Metadata Servers in Large Scale Storage Systems," IEEE transactions on computers, Vol. 59, No. 1, pp1-15, January 2010
• Co-Author "Concentric Layout, a New Scientific Data Distribution Scheme in Hadoop File System," IEEE International Conference on Networking, Architecture, and Storage (NAS'2010). pp.231~239
• Co-Author, "Record - Based Block Distribution (RBBD) and Weighted Set Cover Scheduling (WSCS) in MapReduce" Accepted by Journal of Internet Services and Applications
• Co-Author, "Co-located Compute and Binary File Storage in Data-intensive Computing"
• Co-Author, "Exploiting the Overlap Between Temporal Redundancy and Spatial Redundancy in Storage System (Poster)," 7th USENIX Conference on File and Storage Technologies (FAST ‘09)
• Co-Author, "Fast Recovery Using Optimal and Near-Optimal Parallelism in Data-Intensive Computing," 3rd Petascale Data Storage Workshop Supercomputing '08, Held in conjunction with SC08 and sponsored by the DOE SciDACPetascale Data Storage Institute (PDSI)