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Shahar Kovalsky

I am an Assistant Professor of Mathematics at the University of North Carolina at Chapel Hill.

Previously, I was a Phillip Griffiths Assistant Research Professor at the Department of Mathematics of Duke University, where I worked with Prof. Ingrid Daubechies at the Rhodes Information Initiative at Duke (iID).

I completed my PhD under the supervision of Prof. Ronen Basri and Prof. Yaron Lipman at the Weizmann Institute of Science, Israel.

My research is in optimization, discrete computational geometry, computer graphics and vision, machine learning, and their applications in other venues in science, including biology and medicine.

Email: shaharko (at) unc.edu


Publications

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Lifting Simplices to Find Injectivity

Xingyi Du, Noam Aigerman, Qingnan Zhou, Shahar Kovalsky, Yajie Yan, Danny M. Kaufman and Tao Ju
ACM SIGGRAPH 2020

Abstract PDF PDF (high res) Project Code Dataset
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Weakly Supervised Instance Learning for Thyroid Malignancy Prediction from Whole Slide Cytopathology Images

David Dov, Shahar Kovalsky, Serge Assaad, Avani Pendse, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin
Medical Image Analysis 2020

Abstract Paper arXiv
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Non-Convex Planar Harmonic Maps

Shahar Kovalsky, Noam Aigerman, Ingrid Daubechies, Michael Kazhdan, Jianfeng Lu and Stefan Steinerberger
Submitted

Abstract arXiv
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Application of a Machine Learning Algorithm to Predict Malignancy in Thyroid Cytopathology

Danielle Elliott Range, David Dov, Shahar Kovalsky, Ricardo Henao, Lawrence Carin and Jonathan Cohen
Cancer Cytopathology 2020

Abstract Paper Extended Abstract (ASC)
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Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration

Nadav Dym and Shahar Kovalsky
International Conference on Computer Vision (ICCV) 2019
(* oral presentation)

Abstract arXiv Code (GitHub)
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Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images

David Dov, Shahar Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao and Lawrence Carin
Machine Learning for Healthcare (MLHC) 2019

Abstract arXiv
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Gaussian Process Landmarking on Manifolds

Tingran Gao, Shahar Kovalsky, and Ingrid Daubechies
SIAM Journal on Mathematics of Data Science 2019

Abstract Paper arXiv
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ariaDNE: A Robustly Implemented Algorithm for Dirichlet Normal Energy

Shan Shan, Shahar Kovalsky, Julie Winchester, Doug Boyer and Ingrid Daubechies
Methods in Ecology and Evolution 2019

Abstract Paper Project Code (GitHub)
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Gaussian Process Landmarking for Three-Dimensional Geometric Morphometrics

Tingran Gao, Shahar Kovalsky, Doug Boyer, and Ingrid Daubechies
SIAM Journal on Mathematics of Data Science 2018

Abstract Paper arXiv Code (GitHub)
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Geometric Optimization via Composite Majorization

Anna Shtengel, Roi Poranne, Olga Sorkine-Hornung, Shahar Kovalsky and Yaron Lipman
ACM SIGGRAPH 2017

Abstract PDF PDF (high res) Code (GitHub)
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Spherical Orbifold Tutte Embeddings

Noam Aigerman, Shahar Kovalsky and Yaron Lipman
ACM SIGGRAPH 2017

Abstract PDF PDF (high res)
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Accelerated Quadratic Proxy for Geometric Optimization

Shahar Kovalsky, Meirav Galun and Yaron Lipman
ACM SIGGRAPH 2016

Abstract PDF PDF (high res) Project (+code)
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Point Registration via Efficient Convex Relaxation

Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Kovalsky and Yaron Lipman
ACM SIGGRAPH 2016

Abstract PDF PDF (high res) Code (zip)
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Learning 3D Deformation of Animals from 2D Images

Angjoo Kanazawa, Shahar Kovalsky, Ronen Basri and David Jacobs
Eurographics 2016 (Günter Enderle best paper award)

Abstract PDF Code (GitHub)
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Large-Scale Bounded Distortion Mappings

Shahar Kovalsky, Noam Aigerman, Ronen Basri and Yaron Lipman
ACM SIGGRAPH Asia 2015

Abstract PDF PDF (high res) Project (+code) Slides
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Identification of Structured LTI MIMO State-Space Models

Chengpu Yu, Michel Verhaegen, Shahar Kovalsky and Ronen Basri
IEEE Conference on Decision and Control (CDC) 2015

Abstract PDF
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Tight Relaxation of Quadratic Matching

Itay Kezurer*, Shahar Kovalsky*, Ronen Basri and Yaron Lipman
Computer Graphics Forum (Proc. of SGP) 2015 (best paper award)
(* equal contributors)

Abstract PDF Slides
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A Global Approach for Solving Edge-Matching Puzzles

Shahar Kovalsky, Daniel Glasner and Ronen Basri
SIAM J. Imaging Sciences, Vol. 8, Issue 2, 2015

Abstract PDF
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Controlling Singular Values with Semidefinite Programming

Shahar Kovalsky*, Noam Aigerman*, Ronen Basri and Yaron Lipman
ACM SIGGRAPH 2014
(* equal contributors)

Abstract PDF PDF (high res) Project (+code) Slides
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Global Motion Estimation from Point Matches

Mica Arie-Nachimson, Shahar Kovalsky, Ira Kemelmacher-Shlizerman, Amit Singer and Ronen Basri
3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012

Abstract PDF
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Strongly Consistent Estimation of the Sample Distribution of Noisy Continuous-Parameter Fields

Shahar Kovalsky, Guy Cohen, and Joseph M. Francos
IEEE Transactions on Information Theory, 2011

Abstract PDF
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Decoupled Linear Estimation of Affine Geometric Deformations and Non-Linear Intensity Transformations of Images

Shahar Kovalsky, Guy Cohen, Rami Hagege and Joseph M. Francos
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2010

Abstract PDF
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Registration of Joint Geometric and Radiometric Image Deformations in the Presence of Noise

Shahar Kovalsky, Guy Cohen and Joseph M. Francos
IEEE Workshop on Statistical Signal Processing (SSP), 2007

Abstract PDF
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Registration of Joint Geometric and Radiometric Image Deformations

Shahar Kovalsky, Rami Hagege and Joseph M. Francos
IASTED International Conference on Signal and Image Processing (SIP), 2007

Abstract PDF

Teaching

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Mathematics of Machine Learning

Duke (MATH 466): 2019
Website
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Math Everywhere

Duke (MATH 181): 2018, 2019, 2020
Website
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Minicourse: Convex Majorization with Applications

Duke (MATH 790-90): 2017
Slides

Others

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Computational Aspects of Mappings

Tutorial given at the IGS 2016 summer school (with Noam Aigerman)
Slides (Powerpoint) Slides (PDF)
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Mappings

Tutorial given at the SGP 2015 graduate school (with Roi Poranne)
Part A (Roi Poranne) Part B (Shahar Kovalsky)
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Tour of Image Denoising

Tutorial given at the Weizmann Institute of Science 2011 (with Alon Faktor)
Slides (Powerpoint) Slides (PDF)