Grant Wang
Impact in
- Computational Mathematics top 5%
- Tensor decomposition and applications
- Artificial Intelligence top 5%
- Stochastic Gradient Optimization Techniques
- Machine Learning and Algorithms
- Bayesian Methods and Mixture Models
- Advanced Clustering Algorithms Research
Papers in
-
- Advanced Clustering Algorithms Research 3
- Stochastic Gradient Optimization Techniques 3
-
- Sparse and Compressive Sensing Techniques 3
- Co-authors
- Santosh Vempala (5 shared papers)Luis Rademacher (4 shared papers)Amit Deshpande (3 shared papers)Santosh Vempala (3 shared papers)Ravi Kannan (2 shared papers)Chi Cheng (2 shared papers)Margrét V. Bjarnadóttir (1 shared paper)Michael A. C. Kane (1 shared paper)
- Journals
- Operations Research (1 paper)Financial Analysts Journal (1 paper)BMC Medical Informatics and Decision Making (1 paper)Theory of Computing (1 paper)Journal of Computer and System Sciences (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Grant Wang
11 papers receiving 567 citations
Peers
Comparison fields: 5 of 93
- Computational Mathematics 40
- Artificial Intelligence 318
- Health Information Management 39
- Signal Processing 87
- Computational Mechanics 153
Countries citing papers authored by Grant Wang
This map shows the geographic impact of Grant Wang'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 Grant Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant Wang more than expected).
Fields of papers citing papers by Grant Wang
This network shows the impact of papers produced by Grant Wang. 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 Grant Wang. The network helps show where Grant Wang may publish in the future.
Co-authors
The 18 scholars most cited alongside Grant Wang, 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 | 2008 | 138 | |
| 2 | 2004 | 102 | |
| 3 | 2006 | 90 | |
| 4 | 2006 | 73 | |
| 5 | 2006 | 72 | |
| 6 | 2006 | 52 | |
| 7 | 2016 | 44 | |
| 8 | 2005 | 37 | |
| 9 | 2013 | 13 | |
| 10 | 2014 | 6 | |
| 11 | Matrix Approximation and Projective Clustering via Iterative Sampling | 2005 | 3 |
| 12 | 2025 | 0 |
About Grant Wang
Grant Wang is a scholar working on Artificial Intelligence, Computational Mechanics, Computer Vision and Pattern Recognition, Strategy and Management and Health Information Management, having authored 12 papers that have together received 630 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Advanced Clustering Algorithms Research (3 papers), Stochastic Gradient Optimization Techniques (3 papers), Sparse and Compressive Sensing Techniques (3 papers), Complex Network Analysis Techniques (2 papers), Financial Markets and Investment Strategies (2 papers), Financial Reporting and Valuation Research (2 papers) and Auditing, Earnings Management, Governance (2 papers). The work is most often cited by research in Computational Mathematics (40 citations), Artificial Intelligence (318 citations), Health Information Management (39 citations), Signal Processing (87 citations) and Computational Mechanics (153 citations). Grant Wang has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Santosh Vempala, Luis Rademacher, Amit Deshpande, Santosh Vempala, Ravi Kannan, Chi Cheng, Margrét V. Bjarnadóttir, Michael A. C. Kane, Rudra Pandey and Dimitris Bertsimas. Their work appears in journals such as Operations Research, Financial Analysts Journal, BMC Medical Informatics and Decision Making, Theory of Computing and Journal of Computer and System Sciences.
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.