Dana Lahat

1.4k total citations · 1 hit paper
11 papers, 830 citations indexed

About

Dana Lahat is a scholar working on Signal Processing, Computational Mechanics and Analytical Chemistry. According to data from OpenAlex, Dana Lahat has authored 11 papers receiving a total of 830 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Signal Processing, 5 papers in Computational Mechanics and 5 papers in Analytical Chemistry. Recurrent topics in Dana Lahat's work include Blind Source Separation Techniques (8 papers), Spectroscopy and Chemometric Analyses (5 papers) and Sparse and Compressive Sensing Techniques (3 papers). Dana Lahat is often cited by papers focused on Blind Source Separation Techniques (8 papers), Spectroscopy and Chemometric Analyses (5 papers) and Sparse and Compressive Sensing Techniques (3 papers). Dana Lahat collaborates with scholars based in France, Israel and United States. Dana Lahat's co-authors include Christian Jutten, Tülay Adalı, J.-F. Cardoso, Cédric Févotte, M. Le Jeune and Vincent Y. F. Tan and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Signal Processing and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Dana Lahat

11 papers receiving 803 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects

2015 754 citations Dana Lahat, Tülay Adalı et al. Proceedings of the IEEE profile →

Peers

Dana Lahat

AI

SP

CVPR

CN

AC

Shujian Yu China

Fengxi Song China

Feng Zhao China

Nandakishore Kambhatla United States

Stefan Westberg United States

Cheong Hee Park South Korea

GE Hinton Canada

Brian C. Van Essen United States

Cairong Zou China

Zhonglong Zheng China

Shujian Yu China

Dana Lahat

341 ×1.4

AI

143 ×0.8

SP

321 ×1.9

CVPR

76 ×0.8

CN

49 ×0.7

AC

Citations per year, relative to Dana Lahat Dana Lahat (= 1×) peers Shujian Yu

Countries citing papers authored by Dana Lahat

Since Specialization

Citations

This map shows the geographic impact of Dana Lahat'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 Dana Lahat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dana Lahat more than expected).

Fields of papers citing papers by Dana Lahat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dana Lahat. 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 Dana Lahat. The network helps show where Dana Lahat may publish in the future.

Co-authorship network of co-authors of Dana Lahat

This figure shows the co-authorship network connecting the top 25 collaborators of Dana Lahat. A scholar is included among the top collaborators of Dana Lahat based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dana Lahat. Dana Lahat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Lahat, Dana, et al.. (2021). Positive Semidefinite Matrix Factorization: A Connection With Phase Retrieval and Affine Rank Minimization. IEEE Transactions on Signal Processing. 69. 3059–3074. 1 indexed citations

2.

Lahat, Dana & Cédric Févotte. (2020). Positive Semidefinite Matrix Factorization Based on Truncated Wirtinger Flow. 1035–1039. 1 indexed citations

3.

Lahat, Dana & Cédric Févotte. (2020). Positive Semidefinite Matrix Factorization: A Link to Phase Retrieval And A Block Gradient Algorithm. HAL (Le Centre pour la Communication Scientifique Directe). 4 indexed citations

4.

Lahat, Dana & Christian Jutten. (2018). Joint Independent Subspace Analysis: Uniqueness and Identifiability. IEEE Transactions on Signal Processing. 67(3). 684–699. 6 indexed citations

5.

Lahat, Dana & Christian Jutten. (2016). Joint Independent Subspace Analysis Using Second-Order Statistics. IEEE Transactions on Signal Processing. 64(18). 4891–4904. 20 indexed citations

6.

Lahat, Dana, Tülay Adalı, & Christian Jutten. (2015). Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects. Proceedings of the IEEE. 103(9). 1449–1477. 754 indexed citations breakdown →

7.

Lahat, Dana, et al.. (2014). Blind Separation of Multi-Dimensional Components via Subspace Decomposition: Performance Analysis. IEEE Transactions on Signal Processing. 62(11). 2894–2905. 5 indexed citations

8.

Cardoso, J.-F., et al.. (2012). Identifiability Of Second-Order Multidimensional Ica. INFM-OAR (INFN Catania). 1875–1879. 3 indexed citations

9.

Lahat, Dana, et al.. (2012). Second-Order Multidimensional ICA: Performance Analysis. IEEE Transactions on Signal Processing. 60(9). 4598–4610. 32 indexed citations

10.

Lahat, Dana, et al.. (2011). Multidimensional ICA and its performance analysis applied to CMB observations. 2005. 3724–3727. 1 indexed citations

11.

Lahat, Dana, et al.. (2009). ICA of correlated sources mismodeled as uncorrelated: performance analysis. 489–492. 3 indexed citations

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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