Personal profile
Research interests
My research involves interactions between partial differential equations (PDE), numerical schemes, applied probability, and computer science. I am interested in both the rigorous analysis of PDE, and the development and implementation of algorithms. It is exciting when mathematical analysis and insights can lead to more efficient algorithms. A continuing theme in my current research is finding continuum limits for discrete combinatorial problems. I am particularly interested when these continuum limits involve solving nonlinear PDEs, and have applications in science and engineering.
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Collaborations and top research areas from the last five years
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Math-DT: Advancing the Mathematical Foundations for Dynamic Digital Twinning of Next-Generation Mobile Wireless Networks
Calder, J. (PI) & Lu, Y. (CoI)
THE NATIONAL SCIENCE FOUNDATION
1/1/25 → 12/31/27
Project: Research project
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MoDL: Analytical Foundations for Deep Learning and Inference over Graphs
Calder, J. (PI)
THE NATIONAL SCIENCE FOUNDATION
7/1/22 → 6/30/26
Project: Research project
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CAREER: Harnessing the continuum for big data: Partial differential equations, calculus of variations and machine learning
Calder, J. (PI)
THE NATIONAL SCIENCE FOUNDATION
7/1/20 → 6/30/26
Project: Research project
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Geometric Analysis for Classification and Reassembly of Broken Bones
Olver, P. J. (PI) & Calder, J. (CoI)
THE NATIONAL SCIENCE FOUNDATION
9/1/18 → 8/31/21
Project: Research project
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Numerical solution of a PDE arising from prediction with expert advice
Calder, J., Drenska, N. & Mosaphir, D., Feb 1 2026, In: European Journal of Applied Mathematics. 37, 1, p. 96-122 27 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Attraction-repulsion swarming: A generalized framework of t-SNE via force normalization and tunable interactions
Lu, J. & Calder, J., Jun 5 2025, In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 383, 2298, 20240234.Research output: Contribution to journal › Article › peer-review
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Continuous data assimilation for hydrodynamics: Consistent discretization and application to moment recovery
Lu, J., Qi, K., Wang, L. & Calder, J., Oct 1 2025, In: Journal of Computational Physics. 538, 114199.Research output: Contribution to journal › Article › peer-review
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PDEs for machine learning
Calder, J., Cheng, X., Oberman, A. & Ruthotto, L., Sep 2025, In: Research in Mathematical Sciences. 12, 3, 51.Research output: Contribution to journal › Editorial › peer-review
Open Access -
Predictive Display for Teleoperation Based on Vector Fields Using Lidar-Camera Fusion
Sharma, G., Calder, J. & Rajamani, R., Dec 2025, In: International Journal of Computer Vision. 133, 12, p. 8315-8331 17 p.Research output: Contribution to journal › Article › peer-review
Open Access2 Link opens in a new tab Scopus citations
Datasets
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GraphLearning Python Package
Calder, J., ZENODO, 2022
DOI: 10.5281/zenodo.5850940, https://zenodo.org/record/5850940
Dataset