Tal Shnitzer

I am a postdoctoral researcher at CSAIL MIT in the Geometric Data Processing Group with Prof. Justin Solomon. I received my PhD in 2020 from the faculty of Electrical and Computer Engineering at the Technion, under the supervision of Prof. Ronen Talmon. In 2013, I received my BSc in Biomedical Engineering and in Electrical and Computer Engineering from the Technion.

My research focuses on geometric methods for high-dimensional data analysis, sensor fusion and biomedical signal processing.

Email / CV / Google Scholar / Github

Publications

	Few-Sample Feature Selection via Feature Manifold Learning David Cohen, Tal Shnitzer, Yuval Kluger, Ronen Talmon ICML, 2023 arXiv / paper / code
	Spatiotemporal analysis using riemannian composition of diffusion operators Tal Shnitzer, Hau-Tieng Wu, Ronen Talmon ACHA Elsevier, 2023 arXiv / code
	Log-Euclidean signatures for intrinsic distances between unaligned datasets Tal Shnitzer, Mikhail Yurochkin, Kristjan Greenewald, Justin Solomon ICML, 2022 arXiv / paper / code
	Graph of graphs analysis for multiplexed data with application to imaging mass cytometry Ya-Wei Lin, Tal Shnitzer, Ronen Talmon, Franz Villarroel-Espindola, Shruti Desai, Kurt Schalper, Yuval Kluger PLoS computational biology, 2021 bioRXiv / paper / code
	Diffusion maps kalman filter for a class of systems with gradient flows Tal Shnitzer, Ronen Talmon, Jean-Jacques Slotine IEEE TSP, 2020 arXiv / paper / code
	Layer- and cell-specific recruitment dynamics during epileptic seizures in vivo Fadi Aeed Tal Shnitzer, Ronen Talmon, Yitzhak Schiller Annals of Neurology, 2019 paper / code
	Diffusion maps particle filter Lukas Forster, Alexander Schmidt, Walter Kellermann, Tal Shnitzer, Ronen Talmon Eusipco, 2019 arXiv / paper
	Recovering hidden components in multimodal data with composite diffusion operators Tal Shnitzer, Mirela Ben-Chen, Leonidas Guibas, Ronen Talmon, Hau-Tieng Wu SIAM Journal on Mathematics of Data Science, 2019 arXiv / paper / code
	Alternating diffusion maps for dementia severity assessment Tal Shnitzer, Maya Rapaport, Noga Cohen, Natalya Yarovinsky, Ronen Talmon, Judith Aharon-Peretz ICASSP, 2017 arXiv / paper
	Direction modulation of muscle synergies in a hand-reaching task Sharon Israely, Gerry Leisman, Chay Machluf, Tal Shnitzer, Eli Carmeli IEEE TNSRE, 2017 arXiv / paper
	Manifold learning with contracting observers for data-driven time-series analysis Tal Shnitzer, Ronen Talmon, Jean-Jacques Slotine IEEE TSP, 2016 arXiv / paper / code

Book Chapters

	Manifold learning for data-driven dynamical system analysis Tal Shnitzer, Ronen Talmon, Jean-Jacques Slotine The Koopman Operator in Systems and Control, 2020 chapter / code
	Diffusion operators for multimodal data analysis Tal Shnitzer, Roy Lederman, Gi-Ren Liu, Ronen Talmon, Hau-Tieng Wu Handbook of Numerical Analysis v20, 2019 chapter

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