Shaoshan Liu | Academic Influence

Shaoshan Liu's AcademicInfluence.com Rankings

Shaoshan Liu

Computer Science

#11549

World Rank

#12249

Historical Rank

Machine Learning

#5516

World Rank

#5590

Historical Rank

Artificial Intelligence

#5958

World Rank

#6049

Historical Rank

Database

#9102

World Rank

#9572

Historical Rank

computer-science Degrees

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Computer Science

Shaoshan Liu's Degrees

PhD Computer Science Stanford University
Masters Computer Science Stanford University

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Why Is Shaoshan Liu Influential?

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According to Wikipedia, Shaoshan Liu is a US-based computer scientist, who is also the founder, chairman and CEO of PerceptIn. Presently, he is a senior member of IEEE, a member of ACM and a member of the editorial board of IT Professional. Additionally, he is the vice chair of IEEE Computer Society's Special Technical Community on Autonomous Driving Technologies.

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Shaoshan Liu's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Edge Computing for Autonomous Driving: Opportunities and Challenges (2019) (239)
Enabling Deep Learning on IoT Devices (2017) (118)
Creating Autonomous Vehicle Systems (2017) (106)
Computer Architectures for Autonomous Driving (2017) (100)
FPGA-based ORB feature extraction for real-time visual SLAM (2017) (56)
CAVBench: A Benchmark Suite for Connected and Autonomous Vehicles (2018) (45)
Minimizing partial reconfiguration overhead with fully streaming DMA engines and intelligent ICAP controller (abstract only) (2009) (45)
Trifo-VIO: Robust and Efficient Stereo Visual Inertial Odometry Using Points and Lines (2018) (41)
Building the Computing System for Autonomous Micromobility Vehicles: Design Constraints and Architectural Optimizations (2020) (39)
A Unified Cloud Platform for Autonomous Driving (2017) (36)
Energy Reduction with Run-Time Partial Reconfiguration (2009) (35)
Prefetching in Embedded Mobile Systems Can Be Energy-Efficient (2011) (32)
A Survey of FPGA-Based Robotic Computing (2020) (32)
PIRVS: An Advanced Visual-Inertial SLAM System with Flexible Sensor Fusion and Hardware Co-Design (2017) (31)
Achieving energy efficiency through runtime partial reconfiguration on reconfigurable systems (2013) (28)
Acceleration of XML Parsing through Prefetching (2013) (28)
Potential Impact of Value Prediction on Communication in Many-Core Architectures (2009) (28)
Speculative Execution on GPU: An Exploratory Study (2010) (26)
On energy efficiency of reconfigurable systems with run-time partial reconfiguration (2010) (25)
Achieving middleware execution efficiency: hardware-assisted garbage collection operations (2012) (25)
CAAD: Computer Architecture for Autonomous Driving (2017) (24)
Value Prediction and Speculative Execution on GPU (2011) (23)
Minimizing the runtime partial reconfiguration overheads in reconfigurable systems (2012) (22)
LoPECS: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services (2020) (19)
Autonomous vehicles lite self-driving technologies should start small, go slow (2020) (19)
A Container Based Edge Offloading Framework for Autonomous Driving (2020) (19)
Synchronization Mechanisms on Modern Multi-core Architectures (2007) (17)
π-SoC: Heterogeneous SoC Architecture for Visual Inertial SLAM Applications (2018) (17)
Eudoxus: Characterizing and Accelerating Localization in Autonomous Machines Industry Track Paper (2020) (16)
Hardware-assisted middleware: Acceleration of garbage collection operations (2010) (16)
Memory-Side Acceleration for XML Parsing (2011) (15)
Robotic Computing on FPGAs (2021) (15)
Autonomous Last-Mile Delivery Vehicles in Complex Traffic Environments (2020) (14)
Real-Time Spatio-Temporal LiDAR Point Cloud Compression (2020) (14)
PI-Edge: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services (2018) (14)
Implementing a Cloud Platform for Autonomous Driving (2017) (13)
Brief Industry Paper: The Matter of Time — A General and Efficient System for Precise Sensor Synchronization in Robotic Computing (2021) (13)
Archytas: A Framework for Synthesizing and Dynamically Optimizing Accelerators for Robotic Localization (2021) (13)
Teaching Autonomous Driving Using a Modular and Integrated Approach (2018) (13)
Packer: Parallel Garbage Collection Based on Virtual Spaces (2012) (13)
Pinned OS/Services: A Case Study of XML Parsing on Intel SCC (2013) (13)
Energy reduction with run-time partial reconfiguration (abstract only) (2010) (12)
CoCoPIE: Making Mobile AI Sweet As PIE -Compression-Compilation Co-Design Goes a Long Way (2020) (12)
A Theoretical Framework for Value Prediction in Parallel Systems (2010) (11)
Engineering Autonomous Vehicles and Robots (2020) (11)
Enabling Embedded Inference Engine with ARM Compute Library: A Case Study (2017) (10)
iELAS: An ELAS-Based Energy-Efficient Accelerator for Real-Time Stereo Matching on FPGA Platform (2021) (10)
Π-RT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Vision Applications on Heterogeneous Architectures (2021) (10)
CoCoPIE: enabling real-time AI on off-the-shelf mobile devices via compression-compilation co-design (2021) (9)
Computer, Drive My Car! (2017) (9)
Communication Challenges in Infrastructure-Vehicle Cooperative Autonomous Driving: A Field Deployment Perspective (2022) (8)
Invited: Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunities (2021) (8)
Real-Time Robot Localization, Vision, and Speech Recognition on Nvidia Jetson TX1 (2017) (8)
Workload characterization of cryptography algorithms for hardware acceleration (2011) (8)
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System (2022) (7)
Rise of the Autonomous Machines (2021) (7)
EHA: The Extremely Heterogeneous Architecture (2012) (7)
An Energy-Efficient Quad-Camera Visual System for Autonomous Machines on FPGA Platform (2021) (7)
Oops! It's Too Late. Your Autonomous Driving System Needs a Faster Middleware (2021) (6)
Power-Efficient Schemes via Workload Characterization on the Intel's Single-Chip Cloud Computer (2012) (6)
Towards Fully Intelligent Transportation through Infrastructure-Vehicle Cooperative Autonomous Driving: Challenges and Opportunities (2021) (6)
Engineering Education in the Age of Autonomous Machines (2021) (6)
Hardware-assisted security mechanism: The acceleration of cryptographic operations with low hardware cost (2010) (6)
An Energy-Efficient and Runtime-Reconfigurable FPGA-Based Accelerator for Robotic Localization Systems (2022) (5)
Distributed Simulation Platform for Autonomous Driving (2017) (5)
PIRT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Applications on Heterogeneous Architectures (2018) (5)
An Energy and Performance Efficient DVFS Scheme for Irregular Parallel Divide-and-Conquer Algorithms on the Intel SCC (2014) (5)
Energy-Efficient Data Caching Framework for Spark in Hybrid DRAM/NVM Memory Architectures (2019) (4)
Dataflow Accelerator Architecture for Autonomous Machine Computing (2021) (4)
Space-and-Time Efficient Parallel Garbage Collector for Data-Intensive Applications (2011) (4)
Autonomous Vehicles Digital Twin: A Practical Paradigm for Autonomous Driving System Development (2022) (3)
Enabling Level-4 Autonomous Driving on a Single 1 Off-the-Shelf Card (2021) (3)
Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities (2022) (3)
A Task-Aware Fine-Grained Storage Selection Mechanism for In-Memory Big Data Computing Frameworks (2020) (3)
Brief Industry Paper: Enabling Level-4 Autonomous Driving on a Single $1k Off-the-Shelf Card (2022) (3)
Enabling Commercial Autonomous Robotic Space Explorers (2020) (3)
Embedded Systems Architecture for SLAM Applications (2017) (3)
4C: A Computation, Communication, and Control Co-Design Framework for CAVs (2021) (3)
Creating Autonomous Vehicle Systems, Second Edition (2020) (3)
Rise of the Automotive Health-Domain Controllers: Empowering Healthcare Services in Intelligent Vehicles (2022) (3)
On Designing Computing Systems for Autonomous Vehicles: a PerceptIn Case Study (2020) (3)
An Energy-Efficient High Definition Map Data Distribution Mechanism for Autonomous Driving (2020) (2)
CoCoPIE (2021) (2)
Introducing the Extremely Heterogeneous Architecture (2012) (2)
The potential of fine-grained value prediction in enhancing the performance of modern parallel machines (2008) (2)
Brief Industry Paper: An Edge-Based High-Definition Map Crowdsourcing Task Distribution Framework for Autonomous Driving (2021) (2)
The Performance Analysis and Hardware Acceleration of Crypto-computations for Enhanced Security (2010) (2)
Prototyping Virtual Cancer Therapist (VCT): A Software Engineering Approach (2006) (2)
Practical models for energy-efficient prefetching in mobile embedded systems (2013) (1)
Braum: Analyzing and Protecting Autonomous Machine Software Stack (2022) (1)
Energy-Aware Automatic Tuning of Many-Core Platform via Gradient Descent (2018) (1)
Packer: An innovative space-time-efficient parallel garbage collection algorithm based on virtual spaces (2009) (1)
Memory-Side Acceleration for XML Parsing in Cloud Computing Environments (2011) (1)
Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search (2021) (1)
Application of Autonomous Driving Technologies in the presence of COVID-19: to reduce occupational exposure and potential nosocomial infections of care workers, during transportation in Emergency Medical Service (EMS) (2021) (1)
Space-and-time efficient garbage collectors for parallel systems (2009) (1)
Streaming Data Priority Scheduling Framework for Autonomous Driving by Edge (2021) (1)
Achieving middleware execution efficiency: hardware-assisted garbage collection operations (2010) (0)
Workload characterization of cryptography algorithms for hardware acceleration (abstracts only) (2011) (0)
Factor Graph Accelerator for LiDAR-Inertial Odometry (2022) (0)
A KNN Query Method for Autonomous Driving Sensor Data (2021) (0)
π-Map: A Decision-Based Sensor Fusion with Global Optimization for Indoor Mapping (2020) (0)
Affordable and Reliable Autonomous Driving Through Modular Design (2019) (0)
Abstract only: workload characterization of cryptography algorithms for hardware acceleration (2011) (0)
The Promise of Dataflow Architectures in the Design of Processing Systems for Autonomous Machines (2021) (0)
A Task-Aware Fine-Grained Storage Selection Mechanism for In-Memory Big Data Computing Frameworks (2020) (0)
Co-Design Framework for CAVs (2021) (0)
Programming Autonomous Machines (2022) (0)
Learn-Memorize-Recall-Reduce A Robotic Cloud Computing Paradigm (2017) (0)
Numerical Simulation of Asynchronous Ignition Time Series with Multi-gas Generator (2020) (0)
A Distributed Pricing Strategy for Edge Computation Offloading Optimization in Autonomous Driving (2022) (0)
OCP: Offload Co-Processor for energy efficiency in embedded mobile systems (2013) (0)
INTERNEURON: A Middleware with Multi-Network Communication Reliability for Infrastructure Vehicle Cooperative Autonomous Driving (2022) (0)
π-Learner: A Lifelong Roadside Learning Framework for Infrastructure Augmented Autonomous Driving (2022) (0)
A DAG Refactor Based Automatic Execution Optimization Mechanism for Spark (2019) (0)
AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments (2022) (0)
Enabling Commercial Autonomous Space Robotic Explorers (2019) (0)
Accelerating Lattice Quantum Chromodynamics Simulations with Value Prediction (2017) (0)
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators (2022) (0)
Programming Autonomous Machines : Special Session Paper (2022) (0)
Brief Industry Paper: An Infrastructure-Aided High Definition Map Data Provisioning Service for Autonomous Driving (2021) (0)

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Other Resources About Shaoshan Liu

en.wikipedia.org

What Schools Are Affiliated With Shaoshan Liu?

Shaoshan Liu is affiliated with the following schools:

Stanford University