H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 40 Citations 7,642 157 World Ranking 4429 National Ranking 104

Overview

What is he best known for?

The fields of study he is best known for:

  • Algorithm
  • Statistics
  • Artificial intelligence

Christoph Studer mainly investigates MIMO, Electronic engineering, Algorithm, Artificial intelligence and Telecommunications link. His MIMO research includes themes of Very-large-scale integration and Detector. His Detector research is multidisciplinary, incorporating perspectives in Decoding methods and Chip.

His research integrates issues of Orthogonal frequency-division multiplexing, Throughput, Base station and Transmitter in his study of Electronic engineering. He interconnects Dimension, Minification, Image processing, Noise and Real-time computing in the investigation of issues within Algorithm. Christoph Studer has included themes like Machine learning, Key, Greedy algorithm and Computer vision in his Artificial intelligence study.

His most cited work include:

  • Visualizing the Loss Landscape of Neural Nets (420 citations)
  • Soft-output sphere decoding: algorithms and VLSI implementation (349 citations)
  • Adversarial training for free (268 citations)

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

His scientific interests lie mostly in MIMO, Electronic engineering, Multi-user MIMO, Algorithm and Artificial intelligence. The concepts of his MIMO study are interwoven with issues in Multiplexing, Telecommunications link, Detector and Orthogonal frequency-division multiplexing. His Electronic engineering study incorporates themes from Transmitter and 3G MIMO.

The various areas that Christoph Studer examines in his Multi-user MIMO study include Baseband, Computer hardware, Spectral efficiency and Equalization. His Algorithm research incorporates themes from Estimator, Signal and Communications system. The Artificial intelligence study combines topics in areas such as Machine learning, Computer vision and Pattern recognition.

He most often published in these fields:

  • MIMO (43.53%)
  • Electronic engineering (26.50%)
  • Multi-user MIMO (23.97%)

What were the highlights of his more recent work (between 2018-2021)?

  • MIMO (43.53%)
  • Communication channel (15.14%)
  • Multi-user MIMO (23.97%)

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

Christoph Studer mainly focuses on MIMO, Communication channel, Multi-user MIMO, Algorithm and Electronic engineering. His MIMO study incorporates themes from Multiplexing, Telecommunications link, Base station and Orthogonal frequency-division multiplexing. His work on Channel state information as part of general Communication channel research is frequently linked to Process, bridging the gap between disciplines.

He has included themes like Detector, Equalization, Throughput, Spectral efficiency and Bandwidth in his Multi-user MIMO study. His studies deal with areas such as Wireless, Estimator, Noise reduction and Field-programmable gate array as well as Algorithm. His study explores the link between Electronic engineering and topics such as Antenna that cross with problems in Wiener filter.

Between 2018 and 2021, his most popular works were:

  • Adversarial training for free (268 citations)
  • Deep Unfolding for Communications Systems: A Survey and Some New Directions (51 citations)
  • Transferable Clean-Label Poisoning Attacks on Deep Neural Nets (41 citations)

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

  • Statistics
  • Artificial intelligence
  • Algorithm

Christoph Studer focuses on Artificial neural network, MIMO, Artificial intelligence, Communication channel and Machine learning. His work carried out in the field of Artificial neural network brings together such families of science as CMOS and Cryptography. His MIMO research includes themes of Converters, Throughput and Detector.

His Communication channel study combines topics in areas such as Wireless, Data mining and Dimensionality reduction. His Transfer of learning and Dropout study in the realm of Machine learning interacts with subjects such as Lifelong learning and Transferability. The various areas that Christoph Studer examines in his Multi-user MIMO study include Telecommunications link, Orthogonal frequency-division multiplexing and Equalization.

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

Visualizing the Loss Landscape of Neural Nets

Hao Li;Zheng Xu;Gavin Taylor;Christoph Studer.
neural information processing systems (2018)

494 Citations

Soft-output sphere decoding: algorithms and VLSI implementation

C. Studer;A. Burg;H. Bolcskei.
asilomar conference on signals, systems and computers (2008)

426 Citations

Adversarial training for free

Ali Shafahi;Mahyar Najibi;Mohammad Amin Ghiasi;Zheng Xu.
neural information processing systems (2019)

391 Citations

Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations

Michael Wu;Bei Yin;Guohui Wang;Chris Dick.
IEEE Journal of Selected Topics in Signal Processing (2014)

319 Citations

ASIC Implementation of Soft-Input Soft-Output MIMO Detection Using MMSE Parallel Interference Cancellation

C. Studer;S. Fateh;D. Seethaler.
IEEE Journal of Solid-state Circuits (2011)

282 Citations

Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs

Sven Jacobsson;Giuseppe Durisi;Mikael Coldrey;Ulf Gustavsson.
IEEE Transactions on Wireless Communications (2017)

260 Citations

PAR-Aware Large-Scale Multi-User MIMO-OFDM Downlink

C. Studer;E. G. Larsson.
IEEE Journal on Selected Areas in Communications (2013)

222 Citations

MIMO transmission with residual transmit-RF impairments

Christoph Studer;Markus Wenk;Andreas Burg.
international itg workshop on smart antennas (2010)

216 Citations

Soft–Input Soft–Output Single Tree-Search Sphere Decoding

Christoph Studer;Helmut Bölcskei.
IEEE Transactions on Information Theory (2010)

214 Citations

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

Ali Shafahi;W. Ronny Huang;Mahyar Najibi;Octavian Suciu.
neural information processing systems (2018)

199 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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