Tomas F. Yago Vicente short CV

1. Tom´as F. Yago Vicente, PhD. (AKA TFY Vicente)
Email: tyagovicente@cs.stonybrook.edu LinkedIn: www.linkedin.com/in/tyagovicente
Google Scholar: https://scholar.google.com/citations?user=Gt2MLBkAAAAJ (Citations: 282, h-index: 9)
PhD Scientist with a strong background in Computer Vision and Machine Learning. Dissertation work
focused on developing e cient methods that combine illumination and image formation domain knowledge
with extensive use of machine learning techniques for solving problems such illumination estimation,
shadow detection and shadow removal. Expertise on learning from large-scale, weakly labeled data
and high-performance coding(parallelization/GPU acceleration). Special emphasis on graphical models,
support vector machines, kernel ridge regression, feature learning, kernel learning and optimization and
deep learning. Industry experience on Computer Vision, Machine Learning, Augmented Reality(AR) and
Medical Imaging.
EDUCATION
MS, PhD in Computer Science
Stony Brook University, State University of New York, NY, USA (2017,2018).
PhD Advisors: Dimitris Samaras and Minh Hoai.
Dissertation: ”Large-Scale Weakly-Supervised Shadow Detection”
BSc+MEng in Computer Engineering
University of Zaragoza, Zaragoza, Spain (2008).
MEng Thesis Advisors: Juan Antonio Magallon, Jean-Yves Herv´e (University of Rhode Island).
MEng Thesis: ”Compliant Animation of Dynamic Objects in a Game Engine”
EMPLOYMENT
Applied Scientist Amazon Visual Search & AR, Palo Alto CA (May 2018-Present).
Software Development Intern/ Applied Scientist A9, Palo Alto CA (Summer 2017).
Research Intern Siemens Healthcare, Malvern PA (Summer 2016).
Research Assistant Computer Vision Lab, Stony Brook University (2011 - Present).
Teaching Assistant Dept. of Computer Science, Stony Brook University (2010, 2012).
Courses taught: 532 Databases, 525 Intro to Robotics, 527 Intro to Computer Vision.
Research Assistant 3D Group for Interactive Visualization, Univ. of Rhode Island (2007-10).
ACADEMIC PUBLICATIONS
”Large scale shadow annotation and detection using lazy annotation and stacked CNNs”, L. Hou, T.F.Y
Vicente, , M. Hoai, D. Samaras, TPAMI 2019.
”A+ D Net: Training a Shadow Detector with Adversarial Shadow Attenuation”, H. Le,T.F.Y Vicente,
V Nguyen, M. Hoai, D. Samaras, ECCV 2018.
”Shadow Detection with Conditional Generative Adversarial Networks”, V. Nguyen, T.F.Y Vicente, M.
Zhao, M. Hoai, D. Samaras, ICCV 2017. (Oral presentation: 2.1% acceptance rate)
”Leave-One-Out Kernel Optimization for Shadow Detection And Removal”, T.F.Y Vicente, M. Hoai,
D. Samaras, TPAMI 2017.
”Large-Scale Training of Shadow Detectors with Noisily-Annotated Shadow Examples”, T.F.Y Vicente,
L. Hou, C-P. Yu, M. Hoai, D. Samaras, ECCV 2016.
”Noisy Label Recovery for Shadow Detection on Unknown Domains”, T.F.Y Vicente, M. Hoai, D.
Samaras, CVPR 2016.
”Texture Classification for Rail Surface Condition Evaluation”, K. Ma, T.F.Y Vicente, D. Samaras, M.
Petrucci and D. Magnus, WACV 2016.

2. ”Leave-One-Out Kernel Optimization for Shadow Detection”, T.F.Y Vicente, M. Hoai, D. Samaras,
ICCV 2015. (Oral presentation: 3.3% acceptance rate)
”Simulating Multiple Object Tracking Performance using a Kalman Filter Model”, G. Zelinsky, A. Sher-
man and T.F.Y Vicente, VSS 2015.
”Single Image Shadow Removal via Neighbor Based Region Relighting”, T.F.Y Vicente and D. Samaras,
ECCV-CPCV 2014.
”Replacing the Spotlight with a Kalman Filter: a Prediction Error Model of Multiple Object Tracking”,
A. Sherman, T.F.Y Vicente, and G. Zelinsky, VSS 2014.
”Single Image Shadow Shadow Detection using Multiple Cues in a Supermodular MRF”, T.F.Y Vicente,
C-P. Yu and D. Samaras, BMVC 2013.
”Illumination Estimation from Shadow Borders”, A. Panagopoulos, T.F.Y Vicente and D. Samaras,
ICCV-CPCV 2011.
”Using a Game Engine to Integrate Experimental, Field, and Simulation Data for Science Education:
You Are the Scientist”, J-Y. Herv´e, B. Mullen, T.F.Y Vicente, C. Allen, C. Morace, and I. Otternes,
GSTF JoC 2010.
”Casual Gaming as Means to Raise Awareness of Vector Borne Disease Risks”, T.F.Y Vicente, B.
Mullen, T. Mather, and J-Y. Herv´e, CGAT 2010.
PATENTS AND INDUSTRY PUBLICATIONS
”Photorealistic Texturing for Automatic Large-Scale Reconstruction of 3D Models”, T.F.Y Vicente, K.
Hillesland, A. Dhua, and S. Vedula, Amazon Computer Vision Conference 2019
”Canonical Views and Two-Stage Texturing for Photorealistic 3D Models”, T.F.Y Vicente, A. Dhua,
R. Grzeszczuk, Amazon Computer Vision Conference 2017
”Photorealistic three dimensional texturing using canonical views and a two-stage approach”, T. F. Y.
Vicente, R Grzeszcsuk, ASK Dhua. US Patent 10,515,477
COMMUNITY SERVICE
Journal Reviewer for: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Com-
puter Vision and Image Understanding (CVIU), and IEEE Transactions on Cybernetics.
Conference Reviewer for: Special Interest Group on Computer Graphics and Interactive Techniques
Conference (SIGGRAPH), IEEE International Conference on Robotics and Automation (ICRA), and
International Conference on Pattern Recognition (ICPR)
AWARDS AND ACHIEVEMENTS
Awarded Oral Presentation at ICCV 2017 Italy, Top 2.1% (45/2143), Watch@Youtube.com
Doctoral Consortium Attendance and Travel Award CVPR 2016 Las Vegas, USA
Awarded Oral Presentation at ICCV 2015 Chile, Top 3.3% (56/1698), Watch@VideoLectures.net
Student Grant Accommodation ECCV 2014 Switzerland
Special Computer Science Department Fellowship 2010 Stony Brook University USA
EU-Erasmus Programme Scholarship 2006 Royal Institute of Technology (KTH) Sweden
PROGRAMMING AND TECHNICAL SKILLS
Languages: Python, Matlab, C++, C, Unity3D, LATEX.
Skills: Computer Vision, Machine Learning, Image Processing, Computational Photography, Robotics,
Medical Imaging, Deep Learning, Augmented Reality.