Natasha Jaques

3.5k total citations
34 papers, 1.0k citations indexed

About

Natasha Jaques is a scholar working on Experimental and Cognitive Psychology, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Natasha Jaques has authored 34 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Experimental and Cognitive Psychology, 9 papers in Artificial Intelligence and 8 papers in Cognitive Neuroscience. Recurrent topics in Natasha Jaques's work include Emotion and Mood Recognition (5 papers), Mental Health Research Topics (5 papers) and Music Technology and Sound Studies (4 papers). Natasha Jaques is often cited by papers focused on Emotion and Mood Recognition (5 papers), Mental Health Research Topics (5 papers) and Music Technology and Sound Studies (4 papers). Natasha Jaques collaborates with scholars based in United States, Canada and United Kingdom. Natasha Jaques's co-authors include Rosalind W. Picard, Sara Taylor, Akane Sano, Szymon Fedor, Amy Yu, Andrew W. McHill, Elizabeth B. Klerman, Andrew J. K. Phillips, Charles A. Czeisler and Douglas Eck and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SLEEP and Frontiers in Behavioral Neuroscience.

In The Last Decade

Natasha Jaques

29 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Natasha Jaques United States 14 433 233 198 177 162 34 1.0k
Theodora Chaspari United States 17 313 0.7× 201 0.9× 219 1.1× 114 0.6× 113 0.7× 118 1.1k
Xuhai Xu United States 20 178 0.4× 276 1.2× 160 0.8× 179 1.0× 173 1.1× 67 1.1k
Yekta Said Can Türkiye 14 410 0.9× 223 1.0× 106 0.5× 111 0.6× 109 0.7× 43 1.0k
Min Hane Aung United Kingdom 19 565 1.3× 179 0.8× 145 0.7× 505 2.9× 209 1.3× 40 1.5k
Tianxing Li United States 17 452 1.0× 226 1.0× 114 0.6× 377 2.1× 381 2.4× 67 1.8k
Evdokimos Konstantinidis Greece 20 294 0.7× 394 1.7× 103 0.5× 80 0.5× 174 1.1× 89 1.2k
Mashfiqui Rabbi United States 17 429 1.0× 226 1.0× 108 0.5× 644 3.6× 218 1.3× 31 1.7k
Amin Ahsan Ali Bangladesh 16 245 0.6× 93 0.4× 186 0.9× 231 1.3× 234 1.4× 58 1.1k
Oscar Mayora Italy 21 580 1.3× 154 0.7× 192 1.0× 582 3.3× 291 1.8× 87 1.8k
Pablo Paredes United States 15 309 0.7× 190 0.8× 57 0.3× 175 1.0× 50 0.3× 35 842

Countries citing papers authored by Natasha Jaques

Since Specialization
Citations

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

Fields of papers citing papers by Natasha Jaques

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natasha Jaques

This figure shows the co-authorship network connecting the top 25 collaborators of Natasha Jaques. A scholar is included among the top collaborators of Natasha Jaques 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 Natasha Jaques. Natasha Jaques 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.
2.
Holder, J., Natasha Jaques, & Mehran Mesbahi. (2025). Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems. Proceedings of the AAAI Conference on Artificial Intelligence. 39(25). 26516–26524.
3.
Canny, John, et al.. (2024). Moral Foundations of Large Language Models. 17737–17752. 12 indexed citations
4.
Jaques, Natasha, et al.. (2024). Impossibility theorems for feature attribution. Proceedings of the National Academy of Sciences. 121(2). e2304406120–e2304406120. 24 indexed citations
5.
Looff, Peter de, Remko A. Duursma, Matthijs L. Noordzij, et al.. (2022). Wearables: An R Package With Accompanying Shiny Application for Signal Analysis of a Wearable Device Targeted at Clinicians and Researchers. Frontiers in Behavioral Neuroscience. 16. 856544–856544. 7 indexed citations
6.
Wang, Su, Vighnesh Birodkar, Aleksandra Faust, et al.. (2022). Less is More: Generating Grounded Navigation Instructions from Landmarks. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15407–15417. 24 indexed citations
7.
Gür, İzzeddin, Natasha Jaques, Yingjie Miao, et al.. (2022). Environment Generation for Zero-Shot Compositional Reinforcement Learning. arXiv (Cornell University). 34. 4 indexed citations
8.
Ndousse, Kamal, et al.. (2020). Learning Social Learning. arXiv (Cornell University).
9.
Ndousse, Kamal, Douglas Eck, Sergey Levine, & Natasha Jaques. (2020). Emergent Social Learning via Multi-agent Reinforcement Learning. arXiv (Cornell University). 7991–8004. 4 indexed citations
10.
Dennis, Michael D., Natasha Jaques, Eugene Vinitsky, et al.. (2020). Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. arXiv (Cornell University). 33. 13049–13061. 8 indexed citations
11.
Ghandeharioun, Asma, Judy Hanwen Shen, Natasha Jaques, et al.. (2019). Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems. DSpace@MIT (Massachusetts Institute of Technology). 32. 13658–13669. 10 indexed citations
12.
Jaques, Natasha, et al.. (2018). Learning via social awareness: improving sketch representations with facial feedback. arXiv (Cornell University). 2 indexed citations
13.
Jaques, Natasha, Ognjen Rudovic, Sara Taylor, Akane Sano, & Rosalind W. Picard. (2017). Predicting Tomorrow’s Mood, Health, and Stress Level using Personalized Multitask Learning and Domain Adaptation. International Joint Conference on Artificial Intelligence. 17–33. 38 indexed citations
14.
Taylor, Sara, et al.. (2017). Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health. IEEE Transactions on Affective Computing. 11(2). 200–213. 152 indexed citations
15.
Jaques, Natasha, Shixiang Gu, Dzmitry Bahdanau, et al.. (2017). Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control. Apollo (University of Cambridge). 1645–1654. 39 indexed citations
16.
Jaques, Natasha, Shixiang Gu, Richard E. Turner, & Douglas Eck. (2016). Tuning Recurrent Neural Networks with Reinforcement Learning. arXiv (Cornell University). 24 indexed citations
17.
Jaques, Natasha, Sara Taylor, Asaph Azaria, et al.. (2015). Predicting students' happiness from physiology, phone, mobility, and behavioral data. PubMed. 2015. 222–228. 85 indexed citations
18.
Sano, Akane, Amy Yu, Andrew W. McHill, et al.. (2015). Prediction of Happy-Sad mood from daily behaviors and previous sleep history. PubMed. 2015. 6796–6799. 31 indexed citations
19.
Sano, Akane, Andrew J. K. Phillips, Amy Yu, et al.. (2015). Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones. PubMed. 2015. 1–6. 158 indexed citations
20.
Conati, Cristina, et al.. (2013). Understanding Attention to Adaptive Hints in Educational Games: An Eye-Tracking Study. International Journal of Artificial Intelligence in Education. 23(1-4). 136–161. 45 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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