Robert Walecki

479 total citations
9 papers, 289 citations indexed

About

Robert Walecki is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Signal Processing. According to data from OpenAlex, Robert Walecki has authored 9 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Experimental and Cognitive Psychology and 2 papers in Signal Processing. Recurrent topics in Robert Walecki's work include Emotion and Mood Recognition (6 papers), Face recognition and analysis (5 papers) and Face and Expression Recognition (5 papers). Robert Walecki is often cited by papers focused on Emotion and Mood Recognition (6 papers), Face recognition and analysis (5 papers) and Face and Expression Recognition (5 papers). Robert Walecki collaborates with scholars based in United Kingdom, United States and Netherlands. Robert Walecki's co-authors include Maja Pantić, Ognjen Rudovic, Vladimir Pavlović, Björn W. Schuller, Jean Kossaifi, Yannis Panagakis, Jie Shen, Fabien Ringeval, Jing Han and Antoine Toisoul and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Image and Vision Computing and IEEE Transactions on Affective Computing.

In The Last Decade

Robert Walecki

9 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robert Walecki United Kingdom	7	198	155	71	62	39	9	289
Renaud Séguier France	9	134 0.7×	159 1.0×	45 0.6×	55 0.9×	43 1.1×	37	277
Yoann Baveye France	5	164 0.8×	170 1.1×	46 0.6×	79 1.3×	68 1.7×	7	301
Fangbing Qu China	7	159 0.8×	150 1.0×	45 0.6×	28 0.5×	62 1.6×	16	265
Spiros Ioannou Greece	5	137 0.7×	133 0.9×	51 0.7×	26 0.4×	43 1.1×	13	233
Furkan Gürpınar Türkiye	5	181 0.9×	205 1.3×	97 1.4×	55 0.9×	32 0.8×	6	337
Enrique Sánchez United Kingdom	8	133 0.7×	134 0.9×	39 0.5×	39 0.6×	36 0.9×	17	262
Behnaz Nojavanasghari United States	5	105 0.5×	108 0.7×	134 1.9×	33 0.5×	45 1.2×	5	285
Christel Chamaret France	9	163 0.8×	280 1.8×	47 0.7×	76 1.2×	106 2.7×	19	432
Mohammad Faridul Haque Siddiqui United States	5	145 0.7×	101 0.7×	52 0.7×	21 0.3×	49 1.3×	9	248
Licai Sun China	11	250 1.3×	140 0.9×	270 3.8×	115 1.9×	29 0.7×	21	482

Countries citing papers authored by Robert Walecki

Since Specialization

Citations

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

Fields of papers citing papers by Robert Walecki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Walecki

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

All Works

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9 of 9 papers shown

Zhang, Yuanzhao, Robert Walecki, Joanne R. Winter, et al.. (2020). Applying Artificial Intelligence Methods for the Estimation of Disease Incidence: The Utility of Language Models. Frontiers in Digital Health. 2. 569261–569261. 6 indexed citations

Kossaifi, Jean, Robert Walecki, Yannis Panagakis, et al.. (2019). SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(3). 1022–1040. 157 indexed citations

Walecki, Robert, et al.. (2017). DeepCoder: Semi-parametric Variational Autoencoders for Facial Action Unit Intensity Estimation.. arXiv (Cornell University). 3 indexed citations

Walecki, Robert, et al.. (2017). DeepCoder: Semi-Parametric Variational Autoencoders for Automatic Facial Action Coding. Spiral (Imperial College London). 3209–3218. 23 indexed citations

Walecki, Robert, Ognjen Rudovic, Vladimir Pavlović, & Maja Pantić. (2017). Copula Ordinal Regression Framework for Joint Estimation of Facial Action Unit Intensity. IEEE Transactions on Affective Computing. 10(3). 297–312. 9 indexed citations

Walecki, Robert, Ognjen Rudovic, Vladimir Pavlović, & Maja Pantić. (2016). Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity. University of Twente Research Information. 4902–4910. 32 indexed citations

Walecki, Robert, Ognjen Rudovic, Vladimir Pavlović, & Maja Pantić. (2016). Variable-state Latent Conditional Random Field models for facial expression analysis. Image and Vision Computing. 58. 25–37. 7 indexed citations

Walecki, Robert, Ognjen Rudovic, Maja Pantić, Vladimir Pavlović, & Jeffrey F. Cohn. (2016). A Framework for Joint Estimation and Guided Annotation of Facial Action Unit Intensity. University of Twente Research Information. 1460–1468. 3 indexed citations

Walecki, Robert, Ognjen Rudovic, Vladimir Pavlović, & Maja Pantić. (2015). Variable-state latent conditional random fields for facial expression recognition and action unit detection. 1–8. 49 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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