Christina Lee
- Artificial Intelligence
- Computational Mechanics
- Computer Networks and Communications
- Information Systems
- Computer Vision and Pattern Recognition
- Co-authors
- Devavrat ShahChase RobertsNathan KilloranThomas R. BromleyJosh IzaacMaria SchuldAnthony HayesOlivia Di Matteo
- Topics
- Recommender Systems and Techniques (1 paper)Complexity and Algorithms in Graphs (1 paper)Quantum Information and Cryptography (1 paper)
- Journals
- arXiv (Cornell University)DSpace@MIT (Massachusetts Institute of Technology)International Conference on Artificial Intelligence and Statistics
- Partner nations
- United StatesCanadaSouth Korea
In The Last Decade
Christina Lee
4 papers receiving 19 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 7
- Computational Mechanics 5
- Computer Networks and Communications 4
- Information Systems 4
- Computer Vision and Pattern Recognition 4
Countries citing papers authored by Christina Lee
This map shows the geographic impact of Christina Lee'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 Christina Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christina Lee more than expected).
Fields of papers citing papers by Christina Lee
This network shows the impact of papers produced by Christina Lee. 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 Christina Lee. The network helps show where Christina Lee may publish in the future.
Co-authorship network of co-authors of Christina Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Christina Lee. A scholar is included among the top collaborators of Christina Lee 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 Christina Lee. Christina Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | Reducing Crowdsourcing to Graphon Estimation, Statistically. | 3 |
| 3 | Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering | 13 |
| 4 | Solving for a Single Component of the Solution to a Linear System, Asynchronously | 1 |
About Christina Lee
Christina Lee is a scholar working on Information Systems, Management Science and Operations Research and Computational Theory and Mathematics, having authored 4 papers that have together received 22 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (1 paper), Complexity and Algorithms in Graphs (1 paper) and Quantum Information and Cryptography (1 paper). The work is most often cited by research in Computational Mathematics (1 citation), Statistics and Probability (4 citations) and Computer Science Applications (2 citations). Christina Lee has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Devavrat Shah, Chase Roberts, Nathan Killoran, Thomas R. Bromley, Josh Izaac, Maria Schuld, Anthony Hayes, Olivia Di Matteo and Asuman Ozdaglar. Their work appears in journals such as arXiv (Cornell University), DSpace@MIT (Massachusetts Institute of Technology) and International Conference on Artificial Intelligence and Statistics.
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.