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.
Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support
20161.2k citationsAmbuj Tewari, Susan A. Murphy et al.profile →
Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.
2015388 citationsPredrag Klasnja, Eric B. Hekler et al.Health Psychologyprofile →
Citations per year, relative to Ambuj Tewari Ambuj Tewari (= 1×)
peers
Joseph Jay Williams
Countries citing papers authored by Ambuj Tewari
Since
Specialization
Citations
This map shows the geographic impact of Ambuj Tewari'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 Ambuj Tewari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ambuj Tewari more than expected).
This network shows the impact of papers produced by Ambuj Tewari. 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 Ambuj Tewari. The network helps show where Ambuj Tewari may publish in the future.
Co-authorship network of co-authors of Ambuj Tewari
This figure shows the co-authorship network connecting the top 25 collaborators of Ambuj Tewari.
A scholar is included among the top collaborators of Ambuj Tewari 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 Ambuj Tewari. Ambuj Tewari is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tewari, Ambuj, et al.. (2018). Active Learning for Non-Parametric Regression Using Purely Random Trees. Neural Information Processing Systems. 31. 2537–2546.6 indexed citations
7.
Ramaswamy, Harish G., Clayton Scott, & Ambuj Tewari. (2016). Mixture proportion estimation via kernel embedding of distributions. International Conference on Machine Learning. 2052–2060.18 indexed citations
8.
Ramaswamy, Harish G., Ambuj Tewari, & Shivani Agarwal. (2015). Convex Calibrated Surrogates for Hierarchical Classification. International Conference on Machine Learning. 3. 1852–1860.4 indexed citations
9.
Klasnja, Predrag, Eric B. Hekler, Saul Shiffman, et al.. (2015). Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.. Health Psychology. 34(Suppl). 1220–1228.388 indexed citations breakdown →
10.
Yang, Eunho, Ambuj Tewari, & Pradeep Ravikumar. (2013). On robust estimation of high dimensional generalized linear models. International Joint Conference on Artificial Intelligence. 1834–1840.3 indexed citations
Saha, Ankan & Ambuj Tewari. (2011). Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback. International Conference on Artificial Intelligence and Statistics. 636–642.19 indexed citations
13.
Ravikumar, Pradeep, Ambuj Tewari, & Eunho Yang. (2011). On NDCG Consistency of Listwise Ranking Methods. International Conference on Artificial Intelligence and Statistics. 15. 618–626.39 indexed citations
Sridharan, Karthik & Ambuj Tewari. (2010). Convex games in banach spaces. Conference on Learning Theory. 1–13.9 indexed citations
16.
Kakade, Sham M., Shai Shalev‐Shwartz, & Ambuj Tewari. (2009). Applications of strong convexity--strong smoothness duality to learning with matrices. arXiv (Cornell University).22 indexed citations
17.
Kakade, Sham M., Karthik Sridharan, & Ambuj Tewari. (2008). On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization. ScholarlyCommons (University of Pennsylvania). 21. 793–800.107 indexed citations
18.
Bartlett, Peter L., Varsha Dani, Thomas P. Hayes, et al.. (2008). High-probability regret bounds for bandit online linear optimization. QUT ePrints (Queensland University of Technology). 335–342.32 indexed citations
19.
Kakade, Sham M. & Ambuj Tewari. (2008). On the Generalization Ability of Online Strongly Convex Programming Algorithms. Neural Information Processing Systems. 21. 801–808.56 indexed citations
20.
Tewari, Ambuj & Peter L. Bartlett. (2007). Optimistic linear programming gives logarithmic regret for irreducible MDPs. QUT ePrints (Queensland University of Technology).22 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.