ABOUT M. Alex O. Vasilescu| Tensor Research | UCLA

ABOUT

M. Alex O. Vasilescu received her education at the Massachusetts Institute of Technology and the University of Toronto. She was a research scientist at the MIT Media Lab from 2005–07 and at New York University’s Courant Institute of Mathematical Sciences from 2001–05.

In the early 2000s, Vasilescu introduced the tensor algebraic framework for computer vision, computer graphics, machine learning, and generalized concepts from linear algebra to tensor algebra. She addressed causal inferencing questions by framing computer graphics and computer vision as multilinear problems. This has yielded powerful statistical methods that demonstratively disentangle the causal factors of data formation. Causal inferencing in a tensor framework facilitates the analysis, recognition, synthesis, and interpretability of sensory data. The development of the tensor framework has been spearheaded with premier papers, such as: Human Motion Signatures (2001), TensorFaces(2002), MICA(2005), TensorTextures(2003), 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, etc. MIT's Technology Review named her as TR100 honoree, and the National Academy of Science co-awarded the KeckFutures Initiative Grant .

CV:

Email:

all four initials@cs.ucla.edu

Webpages:

Graphics and Vision Lab

UCLA 48hr-Startup

Quora Profile

Old MIT Media Lab Page

Social links:

Dissertation:

A MULTILINEAR (TENSOR) ALGEBRAIC FRAMEWORK FOR COMPUTER GRAPHICS, COMPUTER VISION, AND MACHINE LEARNING

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",
}

Disseration Committee:

Amnon Shashua
Alan Jepson

Professor Extreme Show-and-Tell:

Sir Giles Brindley, MD, FRCP, FRS

TWEETS:

NEWS:

Feb 14, 2020 Co-chairing SIGGRAPH 2020 Thesis Fast Forward with Eftychios Sifakis this summer
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
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.
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.
Jun 5, 2019: Filed US Patent Application No. 62/857,795 “Method, system, storage medium, and data structure for Compositional Hierarchical Tensor Factorization”.
May 2019: CVPR 2019 Ethics Co-chair (PoC) with Derek Hoiem
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 news

CALENDAR:

Apr 16, 2020: UCSD/HDSI Intertrack Seminar: "Cause-and-Effect in a Tensor Framework"
Feb 26, 2020: CS Colloquium at the Pennsylvania State University: "Representing Cause-and-Effect in a Tensor Framework"
Dec 3, 2019: CS Colloquium at the Courant Institute, New York University: "Representing Cause-and-Effect in a Tensor Framework"
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.
Sep. 16 - 20, 2019: Lecture at SSIMA-International Summer School on Imaging for Medical Applications
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
Jul 28-Aug 1,2019: Co-Chairing, SIGGRAPH 2019 Thesis Fast Forward with Eftychios Sifakis
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
May 30, 2019: AI Distinguished Lecture Series: “Cause-and-Effect in a Tensor Framework” at MILA, Quebec Artificial Intelligence Institute and Microsoft Research Quebec.
May 29, 2019: Seminar in the Center for Intelligent Machines at McGill University
Aug 12-16, 2018: Co-chairing, SIGGRAPH 2018 Thesis Fast-Forward with Eftychios Sifakis
Mar 1, 2018: Guest Lecture, ECE 211A: Digital Image Processing
Nov 10, 2017: Distinguished Lecture, SCI, University of Utah, Salt Lake City
Jul 26, 2017: Keynote Speaker, CVPR: Tensor Methods in Computer Vision, Honolulu, HI
Jun 22-23, 2017: Reviewer: Washington, DC, National Institute of Health (NIH) proposal reviewing session
Mar 4-5, 2017: Judge at CNSI, UCL A Inventathon