Babak Hassibi

27.7k citations
407 papers · 16.6k indexed · 7 hit papers · h-index 55

Babak Hassibi

392 papers receiving 15.8k citations

Hit Papers

The Secrecy Capacity of the MIMO Wire...612199220262003201450010001.5k

Peers

Babak Hassibi
Comparison fields: 5 of 143
  • Computer Networks and Communications 9.5k
  • Electrical and Electronic Engineering 10.9k
  • Signal Processing 1.4k
  • Computational Mechanics 2.3k
  • Artificial Intelligence 3.0k
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Citations per field
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Citations per year

Countries citing papers authored by Babak Hassibi

Since Specialization
Citations

This map shows the geographic impact of Babak Hassibi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Babak Hassibi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Babak Hassibi more than expected).

Fields of papers citing papers by Babak Hassibi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Babak Hassibi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Babak Hassibi. The network helps show where Babak Hassibi may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Babak Hassibi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Babak Hassibi Line = papers co-authored together Babak Hassibi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20242
4 20240
5 20231
6 20214
7 202111
8
Universality in Learning from Linear Measurements
20192
9
Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization
20186
10 20185
11
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering
20186
12
Sequential Coding of Gauss-Markov Sources over Packet-Erasure Channels with Feedback.
20171
13
Crowdsourced Clustering: Querying Edges vs Triangles
201620
14
Regularized Linear Regression: A Precise Analysis of the Estimation Error
201559
15
Asymptotically Exact Denoising in Relation to Compressed Sensing
20134
16
On the Ingleton-Violating Finite Groups and Group Network Codes
20122
17 200724
18
H" ADAPTIVE FILTERING
199522
19
H∞ Optimal Training Algorithms and their Relation to Backpropagation
19946
20
Hoo Optimality Criteria for LMS and Backpropagation
19939

About Babak Hassibi

Babak Hassibi is a scholar working on Computer Networks and Communications, Computational Mechanics and Signal Processing, having authored 407 papers that have together received 16.6k indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (97 papers), Sparse and Compressive Sensing Techniques (88 papers), Advanced Wireless Communication Techniques (87 papers), Advanced MIMO Systems Optimization (56 papers), Wireless Communication Networks Research (45 papers), Wireless Communication Security Techniques (42 papers), Blind Source Separation Techniques (40 papers) and Distributed Sensor Networks and Detection Algorithms (32 papers). The work is most often cited by research in Computer Networks and Communications (9.5k citations), Electrical and Electronic Engineering (10.9k citations) and Signal Processing (1.4k citations). Babak Hassibi has collaborated with scholars based in United States, Saudi Arabia and Israel. Frequent co-authors include Bertrand M. Hochwald, Haris Vikalo, M. Sharif, David G. Stork, Frédérique Oggier, Yindi Jing, T. Kailath, Weiyu Xu, Vijay Gupta and Richard M. Murray. Their work appears in journals such as Nucleic Acids Research, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Automatic Control.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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