Utkarsh Upadhyay
- Transportation top 5%
- Applied Mathematics top 5%
- Point processes and geometric inequalities 2
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- Complex Network Analysis Techniques 3
- Opinion Dynamics and Social Influence 3
- Signal Processing top 10%
- Artificial Intelligence top 10%
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- Culinary Culture and Tourism 2
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- Biochemical Analysis and Sensing Techniques 2
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- Advanced Bandit Algorithms Research 2
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- Energy Harvesting in Wireless Networks 1
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- Peer-to-Peer Network Technologies 1
- Co-authors
- Manuel Gomez-RodriguezLe SongRakshit TrivediHanjun DaiNan DuAbir DeAli ZarezadeBernhard Schölkopf
- Journals
- Proceedings of the National Academy of Sciences (1 paper)SHILAP Revista de lepidopterología (2 papers)Journal of Machine Learning Research (1 paper)
- Partner nations
- IndiaGermanyUnited States
In The Last Decade
Utkarsh Upadhyay
20 papers receiving 489 citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Transportation 81
- Applied Mathematics 92
- Statistical and Nonlinear Physics 65
- Signal Processing 54
- Artificial Intelligence 143
Countries citing papers authored by Utkarsh Upadhyay
This map shows the geographic impact of Utkarsh Upadhyay'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 Utkarsh Upadhyay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Utkarsh Upadhyay more than expected).
Fields of papers citing papers by Utkarsh Upadhyay
This network shows the impact of papers produced by Utkarsh Upadhyay. 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 Utkarsh Upadhyay. The network helps show where Utkarsh Upadhyay may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Utkarsh Upadhyay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 0 | |
| 4 | 2022 | 4 | |
| 5 | 2021 | 7 | |
| 6 | 2021 | 2 | |
| 7 | 2020 | 18 | |
| 8 | 2020 | 1 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 89 | |
| 11 | 2019 | 5 | |
| 12 | Steering Social Activity: A Stochastic Optimal Control Point Of View | 2018 | 11 |
| 13 | Deep Reinforcement Learning of Marked Temporal Point Processes | 2018 | 35 |
| 14 | 2017 | 18 | |
| 15 | 2017 | 12 | |
| 16 | Recurrent Temporal Point Process | 2016 | 1 |
| 17 | Recurrent Marked Temporal Point Processesbreakdown → | 2016 | 279 |
| 18 | Non-Pareto Optimality of MPTCP: Performance Issues and a Possible Solution | 2012 | 9 |
| 19 | 2012 | 19 | |
| 20 | Comparative trials of phototherapy versus photobarb in the management of neonatal hyperbilirubinaemia. | 1976 | 0 |
About Utkarsh Upadhyay
Utkarsh Upadhyay is a scholar working on Transportation, Statistical and Nonlinear Physics and Management Science and Operations Research, having authored 24 papers that have together received 523 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (3 papers), Opinion Dynamics and Social Influence (3 papers), Point processes and geometric inequalities (2 papers), Culinary Culture and Tourism (2 papers), Biochemical Analysis and Sensing Techniques (2 papers), Advanced Bandit Algorithms Research (2 papers), Energy Harvesting in Wireless Networks (1 paper) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Transportation (81 citations), Applied Mathematics (92 citations) and Statistical and Nonlinear Physics (65 citations). Utkarsh Upadhyay has collaborated with scholars based in India, Germany and United States. Frequent co-authors include Manuel Gomez-Rodriguez, Le Song, Rakshit Trivedi, Hanjun Dai, Nan Du, Abir De, Ali Zarezade, Bernhard Schölkopf, Behzad Tabibian and Hamid R. Rabiee. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Journal of Machine Learning Research.
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.