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Mohammad Javad Latifi
Research Associate
Dartmouth College, Department of Mathematics
Office:
Kemeny 209Research Interest:
Mathematical Physics, Data Science, Inverse ProblemsEmail:
mohammad.javad.latifi.jebelli@dartmouth.eduTeaching:
Math 23 - Differential EquationsPublications
Conversations with Flaschka: Kac–Moody groups and Verblunsky coefficients , MJ Latifi, Doug Pickrell, Physica D: Nonlinear Phenomena, Vol 445, 2023. Lattice models and super telescoping formula, MJ Latifi, under review. Exponential of the S^1 trace of the free field and Verblunsky coefficients, MJ Latifi, Doug Pickrell, Rocky Mountain J. Math. 52(3), 2022. Numerical implementation of generalized V-line transforms on 2D vector fields and their inversions, MJ Latifi, Gaik Ambartsoumian, Rohit Kumar Mishra (preprint) Inversion and Symmetries of the Star Transform, G Ambartsoumian, MJ Latifi, The Journal of Geometric Analysis, 31 (2021), pp 11270-11291. Generalized V-line transforms in 2D vector tomography, G Ambartsoumian, MJ Latifi, RK Mishra, Inverse Problems, Vol.36 (10),2020. The V-line transform with some generalizations and cone differentiation, G Ambartsoumian, MJ Latifi, Inverse Problems, Vol.35 (3),2019. Inversion of the star transform, Gaik Ambartsoumian, MJ Latifi, in Tomographic Inverse Problems: Theory and Applications, Oberwolfach Reports, EMS, 2019. Graph Spanners: A Tutorial Review, MJ Latifi, Reyan Ahmed, Alon Efrat, Keaton Hamm, Stephen Kobourov, Faryad Darabi Sahneh, Richard Spence, Computer Science Review, 2020. Approximation algorithms and an integer program for multi-level graph spanners, MJ Latifi, Reyan Ahmed, Keaton Hamm, Stephen Kobourov, FD Sahneh, Richard Spence. Analysis of Experimental Algorithms, SEA 2019. A General Framework for Multi-level Subsetwise Graph Sparsifiers , with Reyan Ahmed, Keaton Hamm, Stephen Kobourov, Faryad Darabi Sahneh, Richard Spence. See Google Scholar page for more.
Check out My CV.
Some Visualizations that I made for my vector calculus students at University of Arizona.
Radars and Autonomous Cars at Lunewave:
In the summer of 2019, I was involved in a cool project at lunewave working on Radars and Autonomous Cars. During this period, I worked on algorithms to track and classify objects. I implemented a C++ GUI software for the analysis and visualization of the Radar data. Here is a video demonstration of the software where you can match the classified cars in the point cloud data with the camera video.
Orthogonal Polynomials on \( S^1 \) and Verblunsky Correspondence
Above animation visualizes the 5th orthogonal polynomial on the circle with respect to the background measure \( d\mu = (1-cos \theta) \frac{d\theta}{2\pi} \). This polynomial can be seen as a section of a fiber bundle on \( S^1 \) with the fiber being the set of complex numbers.
In my current project, we study a new family of measures \( d\mu = (1-cos \theta)^a \frac{d\theta}{2\pi} \) establishing the corresponding Verblunsky sequence and orthogonal polynomials.
