Shiv Vitaladevuni

2.4k total citations
29 papers, 1.0k citations indexed

About

Shiv Vitaladevuni is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shiv Vitaladevuni has authored 29 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 10 papers in Signal Processing. Recurrent topics in Shiv Vitaladevuni's work include Music and Audio Processing (9 papers), Speech Recognition and Synthesis (9 papers) and Speech and Audio Processing (5 papers). Shiv Vitaladevuni is often cited by papers focused on Music and Audio Processing (9 papers), Speech Recognition and Synthesis (9 papers) and Speech and Audio Processing (5 papers). Shiv Vitaladevuni collaborates with scholars based in United States, Israel and Switzerland. Shiv Vitaladevuni's co-authors include Dmitri B. Chklovskii, Prem Natarajan, Rohit Prasad, Louis K. Scheffer, Sankaran Panchapagesan, Viktor Rozgić, Spyros Matsoukas, Ronen Basri, Ming Sun and Björn Hoffmeister and has published in prestigious journals such as Current Biology, Current Opinion in Neurobiology and IEEE Transactions on Medical Imaging.

In The Last Decade

Shiv Vitaladevuni

29 papers receiving 967 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shiv Vitaladevuni United States 17 368 344 255 210 161 29 1.0k
Youngser Park United States 13 274 0.7× 91 0.3× 49 0.2× 210 1.0× 382 2.4× 36 1.2k
Yoonsuck Choe United States 14 306 0.8× 122 0.4× 43 0.2× 468 2.2× 143 0.9× 108 924
Andrew Saxe United Kingdom 16 561 1.5× 352 1.0× 84 0.3× 485 2.3× 51 0.3× 39 1.3k
Jarmo Hurri Finland 11 214 0.6× 395 1.1× 289 1.1× 318 1.5× 37 0.2× 23 875
Ryan Prenger United States 7 290 0.8× 289 0.8× 166 0.7× 1.2k 5.7× 100 0.6× 16 1.6k
Pietro Berkes United States 12 295 0.8× 118 0.3× 143 0.6× 1.2k 5.9× 286 1.8× 19 1.6k
Péter Földiák United Kingdom 15 661 1.8× 347 1.0× 249 1.0× 1.5k 7.4× 344 2.1× 28 2.1k
A. Ravishankar Rao United States 15 160 0.4× 636 1.8× 157 0.6× 290 1.4× 35 0.2× 36 1.3k
Yichuan Tang United States 12 404 1.1× 288 0.8× 74 0.3× 407 1.9× 123 0.8× 28 1.0k
Lijuan Duan China 19 250 0.7× 420 1.2× 95 0.4× 321 1.5× 65 0.4× 95 1.1k

Countries citing papers authored by Shiv Vitaladevuni

Since Specialization
Citations

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

Fields of papers citing papers by Shiv Vitaladevuni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiv Vitaladevuni

This figure shows the co-authorship network connecting the top 25 collaborators of Shiv Vitaladevuni. A scholar is included among the top collaborators of Shiv Vitaladevuni 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 Shiv Vitaladevuni. Shiv Vitaladevuni 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.
Liu, Hongyi, Yuriy Mishchenko, Thibaud Sénéchal, et al.. (2020). Metadata-Aware End-to-End Keyword Spotting. OpenBU (Boston University). 3 indexed citations
2.
Mishchenko, Yuriy, et al.. (2019). Low-Bit Quantization and Quantization-Aware Training for Small-Footprint Keyword Spotting. 706–711. 16 indexed citations
3.
Kao, Chieh-Chi, Ming Sun, Yixin Gao, Shiv Vitaladevuni, & Chao Wang. (2019). Sub-Band Convolutional Neural Networks for Small-Footprint Spoken Term Classification. 2195–2199. 12 indexed citations
4.
Sun, Ming, David Snyder, Yixin Gao, et al.. (2017). Compressed Time Delay Neural Network for Small-Footprint Keyword Spotting. 3607–3611. 71 indexed citations
5.
Panchapagesan, Sankaran, Ming Sun, Spyros Matsoukas, et al.. (2016). Multi-Task Learning and Weighted Cross-Entropy for DNN-Based Keyword Spotting. 760–764. 89 indexed citations
6.
Mairesse, François, Paul Raccuglia, & Shiv Vitaladevuni. (2016). Search-based Evaluation from Truth Transcripts for Voice Search Applications. 985–988. 1 indexed citations
7.
Sun, Ming, et al.. (2015). Model Shrinking for Embedded Keyword Spotting. 369–374. 14 indexed citations
8.
Hu, Tao, Juan Nunez-Iglesias, Shiv Vitaladevuni, et al.. (2013). Electron Microscopy Reconstruction of Brain Structure Using Sparse Representations Over Learned Dictionaries. IEEE Transactions on Medical Imaging. 32(12). 2179–2188. 10 indexed citations
9.
Vitaladevuni, Shiv, Pradeep Natarajan, Shuang Wu, et al.. (2013). Scene image categorization and video event detection using Naive Bayes Nearest Neighbor. 140–147. 3 indexed citations
10.
Saleem, Shirin, Rohit Prasad, Shiv Vitaladevuni, et al.. (2012). Automatic Detection of Psychological Distress Indicators and Severity Assessment from Online Forum Posts. International Conference on Computational Linguistics. 2375–2388. 17 indexed citations
11.
Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2012). BBNVISER : BBN VISER TRECVID 2012 Multimedia Event Detection and Multimedia Event Recounting Systems.. TRECVID. 13 indexed citations
12.
Natarajan, Prem, Shuang Wu, Shiv Vitaladevuni, et al.. (2012). Multimodal feature fusion for robust event detection in web videos. 1298–1305. 132 indexed citations
13.
Rivera-Alba, Marta, Shiv Vitaladevuni, Yuriy Mishchenko, et al.. (2012). Wiring Economy and Volume Exclusion Determine Neuronal Placement in the Drosophila Brain. Current Biology. 22(2). 172–172. 4 indexed citations
14.
Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2011). BBN VISER TRECVID 2011 Multimedia Event Detection System. Journal of International Crisis and Risk Communication Research. 25 indexed citations
15.
Rivera-Alba, Marta, Shiv Vitaladevuni, Yuriy Mishchenko, et al.. (2011). Wiring Economy and Volume Exclusion Determine Neuronal Placement in the Drosophila Brain. Current Biology. 21(23). 2000–2005. 137 indexed citations
16.
Vitaladevuni, Shiv, Pradeep Natarajan, Rohit Prasad, & Prem Natarajan. (2011). Efficient Orthogonal Matching Pursuit using sparse random projections for scene and video classification. 2011. 2312–2319. 16 indexed citations
17.
Vitaladevuni, Shiv & Ronen Basri. (2010). Co-clustering of image segments using convex optimization applied to EM neuronal reconstruction. 2203–2210. 38 indexed citations
18.
Chklovskii, Dmitri B., Shiv Vitaladevuni, & Louis K. Scheffer. (2010). Semi-automated reconstruction of neural circuits using electron microscopy. Current Opinion in Neurobiology. 20(5). 667–675. 123 indexed citations
19.
Veeraraghavan, Ashok, Shiv Vitaladevuni, Lou Scheffer, et al.. (2010). Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction. 1767–1774. 16 indexed citations
20.
Vitaladevuni, Shiv, Vili Kellokumpu, & Larry S. Davis. (2008). Action recognition using ballistic dynamics. 1–8. 38 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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