ABOUT
M. Alex O. Vasilescu received her education at the Massachusetts Institute of Technology and the University of Toronto. She was a senior fellow at UCLA's Institute of Pure and Applied Math (IPAM) in 2021 and held positions at the MIT Media Lab from 2005–07, at New York University’s Courant Institute of Mathematical Sciences from 2001–05.
In the early 2000s, Vasilescu pioneered the tensor factor analysis framework for computer vision, computer graphics, and machine learning. She addressed causal inference questions by framing computer graphics and computer vision problems as tensor (multilinear) factor analysis problems, and demonstrated how the causal factors of data formation could be algorithmically disentangled. Causal inference in a tensor framework facilitates the analysis, recognition, synthesis, and interpretability of sensory data. The development of the causal tensor framework has been spearheaded with papers, such as: Human Motion Signatures (2001), TensorFaces (2002), Multilinear Independent Component Analysis (2005), TensorTextures (2004), and Multilinear Projection for Recognition (2007, 2011).
Vasilescu’s work was featured on the cover of Computer World Canada (currently, IT World Canada), and in articles in the New York Times, Washington Times, ACM Tech News, etc. MIT's Technology Review named her as TR100 honoree, and the National Academy of Science co-awarded the KeckFutures Initiative Grant.
Email:
Webpages:
Social links:
Dissertation:
Bibtex:
@phdthesis{Vasilescu09,
author = "Vasilescu, M. Alex O.",
title = "{A} {M}ultilinear ({T}ensor {A}lgebraic {F}ramework for {C}omputer
{G}raphics, {C}omputer {V}ision, and
{M}achine {L}earning",
school = "University of Toronto",
address = "Toronto, Canada",
year = "2009",
}
TWEETS:
CALENDAR:
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March 17, 2022: University of Pennsylvania, Computer and Information Science, “Forward and Inverse Causal Inference in a Tensor Framework”.
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May 3, 2021. Massachusetts Institute of Technology, Center for Biological and Computational Learning Cambridge, MA “Forward and Inverse Causal Inference in a Tensor Framework”.
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Apr. 16, 2021. UC Riverside, Department of Computer Science and Engineering Colloquium, Riverside, CA “Forward and Inverse Causal Inference in a Tensor Framework”.
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March 16, 2021: Speaking at UCLA IPAM Tensor Methods and Emerging Applications to the Physical and Data Sciences
"Generalized Block Multilinear Factor Analysis: Representing Parts and Wholes " -
March 11, 2021: Speaking at UCLA IPAM Tensor Methods and Emerging Applications to the Physical and Data Sciences
"Forward and Inverse Causal Inference with Multilinear Factor Analysis" -
March 8 - June 11, 2021: Senior Fellow of the UCLA's Institute of Pure and Applied Mathematics, and participant in the Tensor Methods and Emerging Applications to the Physical and Data Sciences
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Jan 12, 2021: "CausalX: Causal eXplanations and Block Multilinear Factor Analysis", M.A.O. Vasilescu, E. Kim, X. S. Zeng In the Proceedings of the 2020 25th International Conference on Pattern Recognition (ICPR 2020), Milan, Italy, January 2021, 10736-10743,
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Jan 10, 2021: ICPR 2020 Tutorial: Cause-and-Effect in a Tensor Framework
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Aug 26, 2020: 2020 SIGGRAPH Berthouzoz Women in Research Pannel
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Aug 25, 2020: SIGGRAPH Thesis Fast Forward Co-Chair, with Eftychios Sifakis
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Apr 16, 2020: UCSD/HDSI Intertrack Seminar: "Cause-and-Effect in a Tensor Framework"
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Feb 26, 2020: CS Colloquium at the Pennsylvania State University: "Representing Cause-and-Effect in a Tensor Framework"
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Dec 3, 2019: CS Colloquium at the Courant Institute, New York University: "Representing Cause-and-Effect in a Tensor Framework"
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Nov 11-14 2019: Keynote Lecture - 2019 IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP 2019) Symposium on Tensor Methods for Signal Processing and Machine Learning, in Ottawa, Canada.
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Sep. 16 - 20, 2019: Lecture at SSIMA-International Summer School on Imaging for Medical Applications
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Aug 5, 2019: "Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors ”, M.A.O. Vasilescu, E. Kim, In The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19): Tensor Methods for Emerging Data Science Challenges, August 04-08, 2019, Anchorage, AK. ACM, New York, NY, USA
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Jul 28-Aug 1,2019: Co-Chairing, SIGGRAPH 2019 Thesis Fast Forward with Eftychios Sifakis
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Jun 17, 2019: CVPR 2019 Tutorial:
"Representing Cause-and-Effect in a Tensor Framework"
Organizers: Lieven De Lathauwer, Jean Kossaifi, Alex Vasilescu -
Jun 16-21, 2019: Co-chairing, CVPR 2019 Tutorials with Ali Farhadi
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May 30, 2019: AI Distinguished Lecture Series: “Cause-and-Effect in a Tensor Framework” at MILA, Quebec Artificial Intelligence Institute and Microsoft Research Quebec.
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May 29, 2019: Seminar in the Center for Intelligent Machines at McGill University
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Aug 12-16, 2018: Co-chairing, SIGGRAPH 2018 Thesis Fast-Forward with Eftychios Sifakis
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Mar 1, 2018: Guest Lecture, ECE 211A: Digital Image Processing
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Nov 10, 2017: Distinguished Lecture, SCI, University of Utah, Salt Lake City
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Jul 26, 2017: Keynote Speaker, CVPR: Tensor Methods in Computer Vision, Honolulu, HI
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Jun 22-23, 2017: Reviewer: Washington, DC, National Institute of Health (NIH) proposal reviewing session
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Mar 4-5, 2017: Judge at CNSI, UCL A Inventathon
NEWS:
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March 11, 2021 Looking forward to collaborating with participants of the Tensor Methods and Emerging Applications to the Physical and Data Sciences as a Senior Fellow of the UCLA's Institute of Pure and Applied Mathematics.
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Feb 14, 2020 Co-chairing SIGGRAPH 2020 Thesis Fast Forward with Eftychios Sifakis this summer
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Feb 4, 2020: Panelist: SIGGRAPH 2020 Berthouzoz Women in Research with Mirela Ben-Chen and Olga Sorkine-Hornung.
Organized by Adriana Schultz and Anh Truong. -
Sep 6, 2019 Looking forward to an exciting CVPR 2020: Challenges and Promises of Inferring Emotion from Image and Video program
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Jun 24, 2019: Looking forward to giving a Keynote Lecture at the 2019 IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP 2019) Symposium on Tensor Methods for Signal Processing and Machine Learning, in Ottawa, Canada.
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Jun 15, 2019: To appear Aug. 5, "Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors”, M.A.O. Vasilescu, E. Kim, In The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19): Tensor Methods for Emerging Data Science Challenges, August 04-08, 2019, Anchorage, AK. ACM, New York, NY, USA.
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Jun 5, 2019: Filed US Patent Application No. 62/857,795 “Method, system, storage medium, and data structure for Compositional Hierarchical Tensor Factorization”.
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May 2019: CVPR 2019 Ethics Co-chair (PoC) with Derek Hoiem
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Feb 2019: CVPR tutorial on
"Representing Cause-and-Effect in a Tensor Framework"
was accepted by CVPR 2019. Co-organized with Jean Kossaifi and Lieven De Lathauwer -
Aug 2018: Eftychios Sifakis and I will be co-chairing the
2019 SIGGRAPH Thesis Fast Forward Competition.
Jun 18, 2019: My non-technical interview with CVPR Daily new