H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 39 Citations 6,029 233 World Ranking 4637 National Ranking 2300


What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Quantum mechanics

Yanzhi Wang mostly deals with Artificial intelligence, Energy storage, Distributed computing, Electronic engineering and Artificial neural network. His Artificial intelligence research incorporates elements of Machine learning and Pattern recognition. His Energy storage research integrates issues from Electricity generation, Stand-alone power system, Electrical engineering and Electric potential energy.

His Distributed computing study incorporates themes from Wireless, Scheduling, Energy consumption and Mobile cloud computing. His Electronic engineering study also includes

  • Control reconfiguration which intersects with area such as Series and parallel circuits,
  • Power together with Voltage and Energy. His Artificial neural network study integrates concerns from other disciplines, such as Matrix and Algorithm, Fast Fourier transform, Random number generation.

His most cited work include:

  • GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2 (1948 citations)
  • Thermal transport through a one-dimensional quantum spin-1/2 chain heterostructure: The role of three-site spin interaction (213 citations)
  • CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices (144 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Artificial intelligence, Electronic engineering, Artificial neural network, Pruning and Computer engineering. His research in Artificial intelligence intersects with topics in Machine learning and Pattern recognition. His Electronic engineering study combines topics from a wide range of disciplines, such as Power and Electronic circuit, Electrical engineering, Voltage.

Yanzhi Wang combines subjects such as Battery and Energy storage with his study of Electrical engineering. Yanzhi Wang interconnects Computation and Speedup in the investigation of issues within Pruning. His Computer engineering study also includes fields such as

  • Efficient energy use which intersects with area such as Computational complexity theory and Energy consumption,
  • Scalability most often made with reference to Stochastic computing.

He most often published in these fields:

  • Artificial intelligence (21.59%)
  • Electronic engineering (16.36%)
  • Artificial neural network (15.68%)

What were the highlights of his more recent work (between 2019-2021)?

  • Pruning (13.18%)
  • Artificial intelligence (21.59%)
  • Artificial neural network (15.68%)

In recent papers he was focusing on the following fields of study:

Yanzhi Wang focuses on Pruning, Artificial intelligence, Artificial neural network, Computer engineering and Inference. The various areas that he examines in his Pruning study include Recurrent neural network, Overhead, Edge device, Data mining and Speedup. His Artificial intelligence research includes themes of Machine learning and Pattern recognition.

His Artificial neural network research is multidisciplinary, incorporating perspectives in Dram, Distributed computing, Filter, Redundancy and Computation. His studies deal with areas such as Range and Resource allocation as well as Distributed computing. Yanzhi Wang has researched Inference in several fields, including Optimizing compiler and Algorithm.

Between 2019 and 2021, his most popular works were:

  • AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. (37 citations)
  • Adversarial T-shirt! Evading Person Detectors in A Physical World (31 citations)
  • PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices. (30 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Quantum mechanics
  • Algorithm

His primary areas of investigation include Pruning, Artificial intelligence, Inference, Speedup and Computer engineering. His Pruning research is multidisciplinary, incorporating elements of Recurrent neural network, Overhead and Crossbar switch. He has included themes like Machine learning, Computation and Pattern recognition in his Artificial intelligence study.

His studies examine the connections between Computation and genetics, as well as such issues in Artificial neural network, with regards to Energy consumption and Process. His Inference research incorporates themes from Optimizing compiler and Algorithm. His studies in Computer engineering integrate themes in fields like Matrix multiplication and Performance improvement.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2

B. P. Abbott;R. Abbott;T. D. Abbott;F. Acernese.
Physical Review Letters (2017)

2071 Citations

Thermal transport through a one-dimensional quantum spin-1/2 chain heterostructure: The role of three-site spin interaction

H. Wu;Y. Wang;W. J. Gong;Y. Han.
European Physical Journal B (2013)

349 Citations

Task Scheduling with Dynamic Voltage and Frequency Scaling for Energy Minimization in the Mobile Cloud Computing Environment

Xue Lin;Yanzhi Wang;Qing Xie;Massoud Pedram.
IEEE Transactions on Services Computing (2015)

177 Citations

Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach

Jing Wang;Jian Tang;Zhiyuan Xu;Yanzhi Wang.
international conference on computer communications (2017)

176 Citations

CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices

Caiwen Ding;Siyu Liao;Yanzhi Wang;Zhe Li.
international symposium on microarchitecture (2017)

172 Citations

Deep Reinforcement Learning for Building HVAC Control

Tianshu Wei;Yanzhi Wang;Qi Zhu.
design automation conference (2017)

167 Citations

A deep reinforcement learning based framework for power-efficient resource allocation in cloud RANs

Zhiyuan Xu;Yanzhi Wang;Jian Tang;Jing Wang.
international conference on communications (2017)

164 Citations

Adaptive Control for Energy Storage Systems in Households With Photovoltaic Modules

Yanzhi Wang;Xue Lin;Massoud Pedram.
IEEE Transactions on Smart Grid (2014)

149 Citations

A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers

Tianyun Zhang;Shaokai Ye;Kaiqi Zhang;Jian Tang.
european conference on computer vision (2018)

145 Citations

Hybrid electrical energy storage systems

Massoud Pedram;Naehyuck Chang;Younghyun Kim;Yanzhi Wang.
international symposium on low power electronics and design (2010)

138 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Yanzhi Wang

Massoud Pedram

Massoud Pedram

University of Southern California

Publications: 47

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