Jie Gao

Research activity per year

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1 Similar Profiles

5 Active
13 Finished

ATD: Algorithms and Geometric Methods for Community and Anomaly Detection and Robust Learning in Complex Networks
Luo, F. (PI) & Gao, J. (CoPI)
National Science Foundation
8/1/23 → 7/31/26
Rutgers, The State University
Project: Research
Unravel machine learning blackboxes -- A general, effective and performance-guaranteed statistical framework for complex and irregular inference problems in data science
Xie, M. (PI) & Gao, J. (CoPI)
National Science Foundation
7/1/23 → 6/30/26
Rutgers, The State University
Project: Research
Collaborative Research: AF: Small: Promoting Social Learning Amid Interference in the Age of Social Media
Gao, J. (PI)
National Science Foundation
10/1/22 → 9/30/25
Rutgers, The State University
Project: Research
CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process
Gao, J. (PI)
National Science Foundation
9/1/22 → 8/31/26
Rutgers, The State University
Project: Research
Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care
Gao, J. (PI)
National Science Foundation
10/1/21 → 9/30/26
Rutgers, The State University
Project: Research

115 Conference contribution
28 Article
14 Paper
8 Conference article
More

Approximating Metric Magnitude of Point Sets
Andreeva, R., Ward, J., Skraba, P., Gao, J. & Sarkar, R., Apr 11 2025, In: Proceedings of the AAAI Conference on Artificial Intelligence. 39, 15, p. 15374-15381 8 p.
Research output: Contribution to journal › Conference article › peer-review
Low Sensitivity Hopsets
Ashvinkumar, V., Bernstein, A., Deng, C., Gao, J. & Wein, N., Feb 11 2025, 16th Innovations in Theoretical Computer Science Conference, ITCS 2025. Meka, R. (ed.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 13. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 325).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Community detection in the human connectome: Method types, differences and their impact on inference
Brooks, S. J., Jones, V. O., Wang, H., Deng, C., Golding, S. G. H., Lim, J., Gao, J., Daoutidis, P. & Stamoulis, C., Apr 2024, In: Human Brain Mapping. 45, 5, e26669.
Research output: Contribution to journal › Article › peer-review

Open Access
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees
Hao, G. Y., Huang, H., Wang, H., Gao, J. & Wang, H., Mar 25 2024, Technical Tracks 14. Wooldridge, M., Dy, J. & Natarajan, S. (eds.). 11 ed. Association for the Advancement of Artificial Intelligence, p. 12286-12294 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 11).
Rutgers, The State University
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms
Deng, C., Gao, J., Lu, K., Luo, F., Sun, H. & Xin, C., 2024, In: Advances in Neural Information Processing Systems. 37
Rutgers, The State University
Research output: Contribution to journal › Conference article › peer-review

Jie Gao

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Collaborations and top research areas from the last five years

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ATD: Algorithms and Geometric Methods for Community and Anomaly Detection and Robust Learning in Complex Networks

Unravel machine learning blackboxes -- A general, effective and performance-guaranteed statistical framework for complex and irregular inference problems in data science

Collaborative Research: AF: Small: Promoting Social Learning Amid Interference in the Age of Social Media

CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process

Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care

Approximating Metric Magnitude of Point Sets

Low Sensitivity Hopsets

Community detection in the human connectome: Method types, differences and their impact on inference

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees

Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms

Jie Gao

Fingerprint

Collaborations and top research areas from the last five years

Projects

Research output