Ali Taylan Cemgil

3.7k total citations · 1 hit paper
149 papers, 1.9k citations indexed

About

Ali Taylan Cemgil is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ali Taylan Cemgil has authored 149 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Signal Processing, 69 papers in Artificial Intelligence and 39 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ali Taylan Cemgil's work include Speech and Audio Processing (64 papers), Music and Audio Processing (54 papers) and Blind Source Separation Techniques (27 papers). Ali Taylan Cemgil is often cited by papers focused on Speech and Audio Processing (64 papers), Music and Audio Processing (54 papers) and Blind Source Separation Techniques (27 papers). Ali Taylan Cemgil collaborates with scholars based in Türkiye, United Kingdom and Netherlands. Ali Taylan Cemgil's co-authors include Bert Kappen, Simon Godsill, Umut Şimşekli, David Barber, Beyza Ermiş, Peter Desain, Evrim Acar, Hilbert J. Kappen, Tuomas Virtanen and Henkjan Honing and has published in prestigious journals such as Nature Medicine, Bioinformatics and PLoS ONE.

In The Last Decade

Ali Taylan Cemgil

140 papers receiving 1.7k citations

Hit Papers

Generative models improve... 2024 2026 2024 10 20 30 40 50

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ali Taylan Cemgil Türkiye 20 989 601 524 198 161 149 1.9k
Taiji Suzuki Japan 22 240 0.2× 422 0.7× 947 1.8× 313 1.6× 52 0.3× 96 1.8k
Prateek Jain India 20 285 0.3× 637 1.1× 422 0.8× 709 3.6× 53 0.3× 97 2.0k
Zuyuan Yang China 19 300 0.3× 539 0.9× 295 0.6× 245 1.2× 27 0.2× 64 1.2k
Dacheng Tao United Kingdom 14 254 0.3× 2.2k 3.6× 846 1.6× 228 1.2× 54 0.3× 23 2.8k
Yanning Shen United States 17 261 0.3× 171 0.3× 427 0.8× 374 1.9× 55 0.3× 74 1.2k
Fanhua Shang China 26 251 0.3× 1.2k 2.0× 741 1.4× 744 3.8× 23 0.1× 99 2.1k
Arif Mahmood Pakistan 28 216 0.2× 1.7k 2.9× 887 1.7× 130 0.7× 95 0.6× 121 2.7k
M. Mao United States 7 421 0.4× 1.1k 1.8× 1.6k 3.1× 115 0.6× 57 0.4× 18 2.6k
Zhihui Lai China 35 385 0.4× 2.4k 4.1× 942 1.8× 788 4.0× 43 0.3× 130 3.4k

Countries citing papers authored by Ali Taylan Cemgil

Since Specialization
Citations

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

Fields of papers citing papers by Ali Taylan Cemgil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali Taylan Cemgil. 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 Ali Taylan Cemgil. The network helps show where Ali Taylan Cemgil may publish in the future.

Co-authorship network of co-authors of Ali Taylan Cemgil

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Taylan Cemgil. A scholar is included among the top collaborators of Ali Taylan Cemgil 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 Ali Taylan Cemgil. Ali Taylan Cemgil is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Stutz, David, Ali Taylan Cemgil, Abhijit Guha Roy, et al.. (2025). Evaluating medical AI systems in dermatology under uncertain ground truth. Medical Image Analysis. 103. 103556–103556.
2.
Cemgil, Ali Taylan, et al.. (2023). Modeling Hierarchical Seasonality Through Low-Rank Tensor Decompositions in Time Series Analysis. IEEE Access. 11. 85770–85784. 2 indexed citations
3.
Ruiz, Francisco J. R., Michalis K. Titsias, Ali Taylan Cemgil, & Randal Douc. (2021). Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains. arXiv (Cornell University). 1 indexed citations
4.
Cemgil, Ali Taylan, et al.. (2020). Adversarially Robust Representations with Smooth Encoders. International Conference on Learning Representations. 5 indexed citations
5.
Cemgil, Ali Taylan, et al.. (2020). Negatif olmayan gürültü giderici değişimli oto-kodlayıcılar kullanarak tek kanaldan kaynak ayrıştırma için zayıf etiket denetimi. MEF University Institutional Repository (MEF University). 2 indexed citations
6.
Whiteley, Nick, et al.. (2019). Parallelizing particle filters with butterfly interactions. Scandinavian Journal of Statistics. 47(2). 361–396. 4 indexed citations
7.
Cemgil, Ali Taylan, et al.. (2019). Estimating Network Flow Length Distributions via Bayesian Nonnegative Tensor Factorization. Wireless Communications and Mobile Computing. 2019. 1–17. 1 indexed citations
8.
Sankur, Bülent, et al.. (2017). A Bayesian change point model for detecting SIP-based DDoS attacks. Digital Signal Processing. 77. 48–62. 26 indexed citations
9.
Sankur, Bülent, et al.. (2017). A real-time SIP network simulation and monitoring system. SoftwareX. 8. 21–25. 4 indexed citations
10.
Ermiş, Beyza, et al.. (2014). Liver CT Annotation via Generalized Coupled Tensor Factorization.. CLEF (Working Notes). 421–427. 5 indexed citations
11.
Şimşekli, Umut, Beyza Ermiş, Ali Taylan Cemgil, & Evrim Acar. (2013). Optimal weight learning for Coupled Tensor Factorization with mixed divergences. Research at the University of Copenhagen (University of Copenhagen). 1–5. 12 indexed citations
12.
Şimşekli, Umut & Ali Taylan Cemgil. (2012). Score guided musical source separation using Generalized Coupled Tensor Factorization. European Signal Processing Conference. 2639–2643. 18 indexed citations
13.
Şimşekli, Umut, et al.. (2012). Large scale polyphonic music transcription using randomized matrix decompositions. European Signal Processing Conference. 2020–2024. 5 indexed citations
14.
Cemgil, Ali Taylan, et al.. (2011). Generalised Coupled Tensor Factorisation. Neural Information Processing Systems. 24. 2151–2159. 46 indexed citations
15.
Nielsen, Jesper Kjær, Mads Græsbøll Christensen, Ali Taylan Cemgil, Simon Godsill, & Søren Holdt Jensen. (2010). Bayesian interpolation in a dynamic sinusoidal model with application to packet-loss concealment. VBN Forskningsportal (Aalborg Universitet). 2010. 239–243. 3 indexed citations
16.
Cemgil, Ali Taylan. (2009). Bayesian Inference for Nonnegative Matrix Factorisation Models. Computational Intelligence and Neuroscience. 2009(1). 785152–785152. 225 indexed citations
17.
Cemgil, Ali Taylan. (2004). Polyphonic Pitch Identification and Bayesian Inference. The Journal of the Abraham Lincoln Association. 2004. 2 indexed citations
18.
Cemgil, Ali Taylan & Bert Kappen. (2001). Tempo tracking and rhythm quantization by sequential Monte Carlo. Radboud Repository (Radboud University). 14. 1361–1368. 5 indexed citations
19.
Cemgil, Ali Taylan & Bert Kappen. (2001). Bayesian real-time adaptation for interactive performance systems. Radboud Repository (Radboud University). 2001. 147–150. 1 indexed citations
20.
Desain, Peter, et al.. (1999). Robust Time-quantization for Music, from Performance to Score. Journal of the Audio Engineering Society. 2 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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