Anuroop Sriram
- Materials Chemistry top 10%
- Artificial Intelligence top 5%
- Renewable Energy, Sustainability and the Environment top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- C. Lawrence ZitnickZachary W. UlissiAbhishek DasMuhammed ShuaibiSiddharth GoyalBrandon M. WoodJavier Heras‐DomingoQiantong Xu
- Topics
- Machine Learning in Materials Science (4 papers)Advanced MRI Techniques and Applications (3 papers)COVID-19 epidemiological studies (2 papers)
- Partner nations
- United StatesIsraelAustria
In The Last Decade
Anuroop Sriram
13 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Materials Chemistry 582
- Artificial Intelligence 239
- Renewable Energy, Sustainability and the Environment 189
- Radiology, Nuclear Medicine and Imaging 183
- Computational Theory and Mathematics 138
Countries citing papers authored by Anuroop Sriram
This map shows the geographic impact of Anuroop Sriram'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 Anuroop Sriram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anuroop Sriram more than expected).
Fields of papers citing papers by Anuroop Sriram
This network shows the impact of papers produced by Anuroop Sriram. 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 Anuroop Sriram. The network helps show where Anuroop Sriram may publish in the future.
Co-authorship network of co-authors of Anuroop Sriram
This figure shows the co-authorship network connecting the top 25 collaborators of Anuroop Sriram. A scholar is included among the top collaborators of Anuroop Sriram 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 Anuroop Sriram. Anuroop Sriram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capturebreakdown → | 51 |
| 3 | Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRIbreakdown → | 69 |
| 4 | The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalystsbreakdown → | 174 |
| 5 | 21 | |
| 6 | 10 | |
| 7 | Open Catalyst 2020 (OC20) Dataset and Community Challengesbreakdown → | 440 |
| 8 | Face Mask Attendance System Based on Image Recognition | 1 |
| 9 | 12 | |
| 10 | 171 | |
| 11 | 128 | |
| 12 | Prediction of deaths caused by covid-19 using machine learning | 1 |
| 13 | 1 | |
| 14 | 154 |
About Anuroop Sriram
Anuroop Sriram is a scholar working on Modeling and Simulation, Health Information Management and Geochemistry and Petrology, having authored 14 papers that have together received 1.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (4 papers), Advanced MRI Techniques and Applications (3 papers) and COVID-19 epidemiological studies (2 papers). The work is most often cited by research in Modeling and Simulation (108 citations), Catalysis (118 citations) and Materials Chemistry (582 citations). Anuroop Sriram has collaborated with scholars based in United States, Israel and Austria. Frequent co-authors include C. Lawrence Zitnick, Zachary W. Ulissi, Abhishek Das, Muhammed Shuaibi, Siddharth Goyal, Brandon M. Wood, Javier Heras‐Domingo, Qiantong Xu, Ronan Collobert and Gabriel Synnaeve. Their work appears in journals such as Radiology, ACS Catalysis and Magnetic Resonance in Medicine.
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.