Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 16 Peace, Justice and Strong Institutions
Fingerprint
The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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ATD: Trustworthy Artificial Intelligence for Threat Detection
Lerman, G. (PI)
THE NATIONAL SCIENCE FOUNDATION
9/1/24 → 8/31/27
Project: Research project
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Mathematically-Guaranteed Global Solutions to Structure-from-Motion
Lerman, G. (PI)
THE NATIONAL SCIENCE FOUNDATION
8/1/22 → 7/31/26
Project: Research project
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ATD: Robustness, privacy and fairness in threat detection
Lerman, G. (PI)
THE NATIONAL SCIENCE FOUNDATION
9/1/21 → 8/31/24
Project: Research project
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ATD: Threat Detection Problems in Precision Agriculture and Satellite Imaging
Lerman, G. (PI)
THE NATIONAL SCIENCE FOUNDATION
8/15/18 → 7/31/22
Project: Research project
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IMPROVED CONVERGENCE FACTOR OF WINDOWED ANDERSON ACCELERATION FOR SYMMETRIC FIXED-POINT ITERATIONS
Garner, C., Lerman, G. & Zhang, T., 2026, In: SIAM Journal on Numerical Analysis. 64, 5, p. 1891-1922 32 p.Research output: Contribution to journal › Article › peer-review
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Cycle-Sync: Robust Global Camera Pose Estimation through Enhanced Cycle-Consistent Synchronization
Li, S., Shi, Y. & Lerman, G., 2025, 39th Conference on Neural Information Processing Systems, NeurIPS 2025. Neural information processing systems foundation, p. 172957-172991 35 p. (Advances in Neural Information Processing Systems; vol. 38).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Improving Hyperbolic Representations via Gromov-Wasserstein Regularization
Yang, Y., Lee, W., Zou, D. & Lerman, G., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 211-227 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15140 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
4 Link opens in a new tab Scopus citations -
Monotone Generative Modeling via a Gromov-Monge Embedding
Lee, W., Yang, Y., Zou, D. & Lerman, G., 2025, In: SIAM Journal on Mathematics of Data Science. 7, 3, p. 1184-1209 26 p.Research output: Contribution to journal › Article › peer-review
Open Access -
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion ∗
Yu, F., Zhang, T. & Lerman, G., 2024, Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024. IEEE Computer Society, p. 14575-14584 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
5 Link opens in a new tab Scopus citations
Datasets
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Ensemble Riemannian Data Assimilation for High-dimensional Nonlinear Dynamics
Tamang, S. K., Ebtehaj, A., van Leeuwen, P., Lerman, G. & Foufoula, E., Data Repository for the University of Minnesota, May 17 2021
https://hdl.handle.net/11299/220103
Dataset