Daniel McDuff

11.3k total citations · 2 hit papers
154 papers, 6.4k citations indexed

About

Daniel McDuff is a scholar working on Experimental and Cognitive Psychology, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Daniel McDuff has authored 154 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Experimental and Cognitive Psychology, 52 papers in Biomedical Engineering and 41 papers in Cognitive Neuroscience. Recurrent topics in Daniel McDuff's work include Non-Invasive Vital Sign Monitoring (52 papers), Heart Rate Variability and Autonomic Control (31 papers) and Emotion and Mood Recognition (30 papers). Daniel McDuff is often cited by papers focused on Non-Invasive Vital Sign Monitoring (52 papers), Heart Rate Variability and Autonomic Control (31 papers) and Emotion and Mood Recognition (30 papers). Daniel McDuff collaborates with scholars based in United States, United Kingdom and Japan. Daniel McDuff's co-authors include Rosalind W. Picard, Ming‐Zher Poh, Rana el Kaliouby, Mary Czerwinski, Javier Hernandez, Ethan B. Blackford, Justin R. Estepp, Jeffrey F. Cohn, Thibaud Sénéchal and Ashish Kapoor and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Daniel McDuff

144 papers receiving 6.1k 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.

Non-contact, automated cardiac pulse measurements using video imaging and blind source separation

2010 1.1k citations Daniel McDuff, Rosalind W. Picard et al. profile →
Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam

2010 1.1k citations Daniel McDuff, Rosalind W. Picard et al. profile →

Peers

Daniel McDuff

BE

CCM

ECP

CN

SURGE

Ming‐Zher Poh United States

Bert Arnrich Germany

Ioannis Pavlidis United States

Ilkka Korhonen Finland

Tiago H. Falk Canada

M. Murugappan Malaysia

Manolis Tsiknakis Greece

Hasan Ayaz United States

Brenda K. Wiederhold United States

Kristof Van Laerhoven Germany

Ming‐Zher Poh United States

Daniel McDuff

2.6k ×0.8

BE

2.3k ×0.9

CCM

427 ×0.3

ECP

1.3k ×1.0

CN

734 ×0.7

SURGE

Citations per year, relative to Daniel McDuff Daniel McDuff (= 1×) peers Ming‐Zher Poh

Countries citing papers authored by Daniel McDuff

Since Specialization

Citations

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

Fields of papers citing papers by Daniel McDuff

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel McDuff

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

McDuff, Daniel, Zeinab Esmaeilpour, Anthony Z. Faranesh, et al.. (2026). Insulin resistance prediction from wearables and routine blood biomarkers. Nature.

2.

Park, Yoobin, Darwin A. Guevarra, Peggy Callahan, et al.. (2025). Promoting Prosociality via Micro-acts of Joy: A Large-Scale Well-Being Intervention Study. 1–28.

3.

Galatzer‐Levy, Isaac R., Daniel McDuff, & Matteo Malgaroli. (2025). The Capability of Large Language Models to Measure and Differentiate Psychiatric Conditions Through O-Shot Learning. Biological Psychiatry. 97(9). S62–S62.

4.

Andalibi, Nazanin, Luke Stark, Daniel McDuff, et al.. (2024). What should we do with Emotion AI? Towards an Agenda for the Next 30 Years. 98–101.

5.

Hernandez, Javier, Vedant Das Swain, Jina Suh, et al.. (2024). Triple Peak Day: Work Rhythms of Software Developers in Hybrid Work. IEEE Transactions on Software Engineering. 51(2). 344–354. 3 indexed citations

6.

Malgaroli, Matteo & Daniel McDuff. (2024). An overview of diagnostics and therapeutics using large language models. Journal of Traumatic Stress. 37(5). 754–760. 5 indexed citations

7.

Hernandez, John, et al.. (2024). What Are the Odds? Language Models Are Capable of Probabilistic Reasoning. 11712–11733. 1 indexed citations

8.

McDuff, Daniel, Allen Jiang, Felicia Cordeiro, et al.. (2023). The Google Health Digital Well-Being Study: Protocol for a Digital Device Use and Well-Being Study. JMIR Research Protocols. 13. e49189–e49189. 3 indexed citations

9.

McDuff, Daniel, et al.. (2023). Video-based sympathetic arousal assessment via peripheral blood flow estimation. Biomedical Optics Express. 14(12). 6607–6607. 3 indexed citations

10.

Ma, Shuang, Zhaoyang Zeng, Daniel McDuff, & Yale Song. (2021). Contrastive Learning of Global and Local Video Representations. Neural Information Processing Systems. 34. 15 indexed citations

11.

Chen, Kezhen, Qiuyuan Huang, Yonatan Bisk, Daniel McDuff, & Jianfeng Gao. (2021). KB-VLP: Knowledge Based Vision and Language Pretraining. International Conference on Machine Learning. 3 indexed citations

12.

Liu, Xin, Josh Fromm, Shwetak Patel, & Daniel McDuff. (2020). Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement. Neural Information Processing Systems. 33. 19400–19411. 2 indexed citations

13.

Nowara, Ewa M., Daniel McDuff, & Ashok Veeraraghavan. (2020). Systematic analysis of video-based pulse measurement from compressed videos. Biomedical Optics Express. 12(1). 494–494. 14 indexed citations

14.

Zolyomi, Annuska, Andrew Begel, John Tang, et al.. (2019). Managing Stress: The Needs of Autistic Adults in Video Calling. Computer Supported Cooperative Work (CSCW). 11 indexed citations

15.

Shi, Lei, John Tang, Ed Cutrell, et al.. (2019). Accessible Video Calling: Enabling Nonvisual Perception of Visual Conversation Cues. Computer Supported Cooperative Work (CSCW).

16.

Hernandez, Javier, Daniel McDuff, Karen S. Quigley, Pattie Maes, & Rosalind W. Picard. (2018). Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation. IEEE Journal of Biomedical and Health Informatics. 23(5). 1920–1927. 18 indexed citations

17.

Ma, Shuang, Daniel McDuff, & Yale Song. (2018). Neural TTS Stylization with Adversarial and Collaborative Games. International Conference on Learning Representations. 12 indexed citations

18.

Czerwinski, Mary, Chelsey R. Wilks, Kael Rowan, et al.. (2017). Machine learning for Precise Targeting of a Mobile Dialectical Behavior Therapy Skills Training Application. Human Factors in Computing Systems. 2 indexed citations

19.

Fridman, Lex, et al.. (2016). Driver frustration detection from audio and video in the wild. OPUS (Augsburg University). 1354–1360. 22 indexed citations

20.

Kaliouby, Rana el, Jeffrey F. Cohn, Daniel McDuff, & Rosalind W. Picard. (2014). Predicting Ad Liking and Purchase Intent: Large-Scale Analysis of Facial Responses to Ads. DSpace@MIT (Massachusetts Institute of Technology). 1 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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