H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 31 Citations 3,528 199 World Ranking 7699 National Ranking 3620

Overview

What is he best known for?

The fields of study he is best known for:

  • Computer network
  • Quantum mechanics
  • Artificial intelligence

His primary areas of investigation include Computer network, Scheduling, Algorithm, Decoding methods and Electronic engineering. His Cellular network study, which is part of a larger body of work in Computer network, is frequently linked to Function, bridging the gap between disciplines. The various areas that he examines in his Scheduling study include Graph, Distributed computing, Latency, Telecommunications network and Transmitter.

His Algorithm study combines topics in areas such as Tensor, Proportionally fair, Matrix decomposition, Channel allocation schemes and Base station. Vaneet Aggarwal has researched Decoding methods in several fields, including Relay channel, Relay, Communication channel and Topology. His Electronic engineering study combines topics from a wide range of disciplines, such as Physical layer, Throughput, Orthogonal frequency-division multiplexing, Backward compatibility and Signal.

His most cited work include:

  • Design and Characterization of a Full-Duplex Multiantenna System for WiFi Networks (443 citations)
  • Design and Characterization of a Full-duplex Multi-antenna System for WiFi networks (233 citations)
  • Iterative Dynamic Water-Filling for Fading Multiple-Access Channels With Energy Harvesting (100 citations)

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

Vaneet Aggarwal mainly focuses on Computer network, Algorithm, Communication channel, Scheduling and Mathematical optimization. As part of one scientific family, he deals mainly with the area of Computer network, narrowing it down to issues related to the Wireless network, and often Network topology. His research in Algorithm intersects with topics in Matrix, Rank and Tensor.

His Communication channel study also includes fields such as

  • Transmitter that intertwine with fields like Interference and Upper and lower bounds,

  • Relay which is related to area like Gaussian. His Scheduling research includes elements of Latency, Distributed computing and Server. His Mathematical optimization research also works with subjects such as

  • Bandwidth allocation together with Throughput,

  • Convex optimization together with Solver.

He most often published in these fields:

  • Computer network (21.94%)
  • Algorithm (16.81%)
  • Communication channel (16.81%)

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

  • Artificial intelligence (8.26%)
  • Reinforcement learning (5.98%)
  • Distributed computing (9.12%)

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

Vaneet Aggarwal mostly deals with Artificial intelligence, Reinforcement learning, Distributed computing, Machine learning and Mathematical optimization. His Artificial intelligence research includes themes of State space and Computer vision. His studies deal with areas such as Latency, Distributed ledger, Blockchain and Erasure as well as Distributed computing.

His study in Mathematical optimization is interdisciplinary in nature, drawing from both Server, Gaussian process and Job shop scheduling. In his study, which falls under the umbrella issue of Erasure code, Scheduling is strongly linked to Video quality. His research in Computer network is mostly concerned with Quality of experience.

Between 2019 and 2021, his most popular works were:

  • GADMM: Fast and Communication Efficient Framework for Distributed Machine Learning (27 citations)
  • Low-Tubal-Rank Tensor Completion Using Alternating Minimization (19 citations)
  • Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning (15 citations)

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

  • Computer network
  • Artificial intelligence
  • Quantum mechanics

His primary areas of study are Artificial intelligence, Machine learning, Network topology, Topology and Server. His biological study spans a wide range of topics, including Scale and Gaussian process. Vaneet Aggarwal interconnects Distributed computing, Wireless network, Edge device and Star network in the investigation of issues within Network topology.

Within one scientific family, Vaneet Aggarwal focuses on topics pertaining to Aggregate under Redundancy, and may sometimes address concerns connected to Algorithm. He studied Algorithm and Dynamic bandwidth allocation that intersect with Quality of experience and Optimization problem. His Quality of experience study is concerned with the field of Computer network as a whole.

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

Design and Characterization of a Full-Duplex Multiantenna System for WiFi Networks

Melissa Duarte;Ashutosh Sabharwal;Vaneet Aggarwal;Rittwik Jana.
IEEE Transactions on Vehicular Technology (2014)

550 Citations

Design and Characterization of a Full-duplex Multi-antenna System for WiFi networks

Melissa Duarte;Ashutosh Sabharwal;Vaneet Aggarwal;Rittwik Jana.
arXiv: Networking and Internet Architecture (2012)

361 Citations

Prometheus: toward quality-of-experience estimation for mobile apps from passive network measurements

Vaneet Aggarwal;Emir Halepovic;Jeffrey Pang;Shobha Venkataraman.
workshop on mobile computing systems and applications (2014)

154 Citations

Modeling web quality-of-experience on cellular networks

Athula Balachandran;Vaneet Aggarwal;Emir Halepovic;Jeffrey Pang.
acm/ieee international conference on mobile computing and networking (2014)

132 Citations

Iterative Dynamic Water-Filling for Fading Multiple-Access Channels With Energy Harvesting

Zhe Wang;Vaneet Aggarwal;Xiaodong Wang.
IEEE Journal on Selected Areas in Communications (2015)

123 Citations

Exploiting mobility in proportional fair cellular scheduling: measurements and algorithms

Robert Margolies;Ashwin Sridharan;Vaneet Aggarwal;Rittwik Jana.
IEEE ACM Transactions on Networking (2016)

104 Citations

Joint Latency and Cost Optimization for Erasure-Coded Data Center Storage

Yu Xiang;Tian Lan;Vaneet Aggarwal;Yih-Farn R. Chen.
IEEE ACM Transactions on Networking (2016)

103 Citations

Efficient Low Rank Tensor Ring Completion

Wenqi Wang;Vaneet Aggarwal;Shuchin Aeron.
international conference on computer vision (2017)

92 Citations

Wide Compression: Tensor Ring Nets

Vaneet Aggarwal;Wenlin Wang;Brian Eriksson;Yifan Sun.
computer vision and pattern recognition (2018)

88 Citations

Adaptive Sampling of RF Fingerprints for Fine-Grained Indoor Localization

Xiao-Yang Liu;Shuchin Aeron;Vaneet Aggarwal;Xiaodong Wang.
IEEE Transactions on Mobile Computing (2016)

84 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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