Ashutosh Sabharwal

Electrical and Electronic Engineering · 2002–2022

A researcher in the Science corpus: 13 papers; trusts 346 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 50 citations into it; #452 of 16,539 by trust here, #3,369 by citations
• Computer Networks and Communications — 44 citations into it; #1,541 of 9,886 by trust here, #984 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #17,094 of 21,575 by trust here, #19,310 by citations
• Artificial Intelligence — 24 citations into it; #27,834 of 35,345 by trust here, #30,347 by citations
• Representation & Self-Supervised Learning — 16 citations into it
• Radiology, Nuclear Medicine and Imaging — 6 citations into it; #2,133 of 3,265 by trust here, #2,914 by citations

Whom Ashutosh Sabharwal trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Marco F. Duarte
2. Achaleshwar Sahai
3. Jung Il Choi
4. Karen Simonyan
5. Geoffrey E. Hinton
6. Taneli Riihonen
7. Alex Krizhevsky
8. Mayank Jain
9. Kaiming He
10. Yoshua Bengio

Who trusts Ashutosh Sabharwal overall

1. Dongkyu Kim
2. Dani Korpi
3. Gang Liu
4. Zhongshan Zhang
5. Achaleshwar Sahai
6. D. J. Love
7. Haesoon Lee
8. Evan Everett
9. Haq Nawaz
10. Elsayed Ahmed

Papers from Ashutosh Sabharwal's perspective

Ordered by how strongly the researchers Ashutosh Sabharwal trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Webly Supervised Learning Meets Zero-shot Learning: A Hybrid Approach for Fine-Grained Classification (2018) — 71 citations
• On beamforming with finite rate feedback in multiple-antenna systems (2003) — 932 citations
• In-Band Full-Duplex Wireless: Challenges and Opportunities (2013) — 2,209 citations
• Full-duplex wireless communications using off-the-shelf radios: Feasibility and first results (2010) — 882 citations
• Experiment-Driven Characterization of Full-Duplex Wireless Systems (2011) — 1,427 citations
• Pushing the limits of Full-duplex: Design and Real-time Implementation (2011) — 334 citations
• Design and Characterization of a Full-Duplex Multiantenna System for WiFi Networks (2012) — 542 citations
• DistancePPG: Robust non-contact vital signs monitoring using a camera (2015) — 411 citations
• Renew (2022) — 1,209 citations
• An Axiomatic Theory of Fairness in Network Resource Allocation (2009) — 444 citations
• Passive Self-Interference Suppression for Full-Duplex Infrastructure Nodes (2013) — 872 citations
• Using Predictable Observer Mobility for Power Efficient Design of Sensor Networks (2003) — 461 citations
• Opportunistic media access for multirate ad hoc networks (2002) — 787 citations