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I'm currently a PostDoctoral Research Associate at the McGovern Institute for Brain Research and the Center for Brains, Minds and Machines working with Tomaso Poggio at MIT.

I was previously a PostDoctoral Research Fellow with Talia Konkle at Harvard University where we worked on understanding the mechanisms of foveation in humans and machines (Pre-print coming soon!)

I completed my PhD in Dynamical Neuroscience at the Vision and Image Understanding Lab at UCSB, where I am supervised by Miguel Eckstein. My previous experience includes working with Manjunath at the Center for BioImage Informatics at UCSB and with Devi Parikh at the Computer Vision and Machine Perception Lab at Virginia Tech. I have a B.S. in Mechatronics Engineering (Robotics) from Universidad Nacional de Ingenieria in Lima, Peru where I was advised by Alberto Coronado and Elizabeth Villota. At UCSB, I was also affiliated with the Institute for Collaborative Biotechnologies.

During my PhD, I worked on towards answering the question of: 'Are biologically inspired human vision models necessary for advanced computer & robot vision? And if so, what aspects should be borrowed and ignored from visual psychology?' More specifically my focus was on understanding the human mechanisms of foveation and peripheral processing, as well as the inverse problem of how advanced computer vision systems may benefit from such peripheral representations. My quest towards answering the two previous questions has led me to perform research at the intersection of vision science, computer vision and machine learning.

You can download my CV here: CV.

You can also find me on Google Scholar, LinkedIn, GitHub, StackOverflow, Author Influence Graph / Semantic Scholar, Neurotree.

In another life I am an Artist. I was informally trained during long conversations at The Biscuit by John Tarzian. I'll be having a small art show at the Somerville Open Studio in May, 2020. I am also a proud owner of a Lamborghini

contact: deza {at} mit . edu

Recent & Upcoming Talks:

Talk at the Rosenholtz lab at MIT's CSAIL in Summer of 2017 on Peripheral Representations for Artificial Perception Systems.
Talk at Universidad Nacional de Ingenieria (my alma mater) in Lima, Peru in January 2018 about Peripheral Representations for Artificial Perception Systems.
Talk on Peripheral Representations at the SIAM Applied Mathematics Seminar of UCSB in March 2018.
I will be giving a talk at Redwood Center for Theoretical Neuroscience in March 2018 on Peripheral Representations for computational models of Human and Machine Perception.
Talk at Harvard's Konkle Lab: "Peripheral Representations for Human and Machine Perception" (October 2018)!
Talk at Columbia's Zuckerman Institute: "Probing for Visual Metamerism via Foveated Style Transfer" (October 2018)!
Talk on Visual Metamerism at Google Machine Perception in Mountain View in January 2019!

  • Talk on Exploring the role of Foveation witih Deep Neural Networks at NVIDIA (October 2019), Wolfe lab (Harvard Medical School, February 2020) and Anzellotti Lab (Boston College, April 2020)

Recently I have reviewed for / will be reviewing :

  • ICLR 2021
  • NeurIPS 2020
  • ECCV 2020 (Computer Vision, Generative Models)
  • ICML 2020 (Neuroscience, Computer Vision, Deep Learning, Learning Theory)
  • CVPR 2019 & 2020 (Computer Vision)
  • ICCV 2019 (Computer Vision and Representational Learning)
  • CASE 2019 (Robotics),
  • NeurIPS (formerly NIPS) 2019 (Perception, Neuroscience & Deep Learning)
  • CCN 2019 (Cognitive Computational Neuroscience)
  • AAAI 2020

Other news [2020]:

  • I will be TA'ing the relatively new class: "9.58 Projects in the Science of Intelligence" for the new 6-9 course major with Yena Han at MIT in Fall 2020.

Recently received the Harvard Brain Initiative (HBI) Young Scientist Travel Award!

I'm currently co-organizing with Joshua Peterson, Apurva Ratan Murty and Thomas Griffiths, the 1st Shared Visual Representations in Human and Machine Intelligence (SVRHM) Workshop @ NeurIPS 2019.





Pre-Prints Code/Data/Demo
Scrambled_Frog.png Arturo Deza, Qianli Liao, Andrzej Banburski, Tomaso Poggio. Hierarchically Local Tasks and Deep Convolutional Networks. ArXiv, 2020. Under review as a conference paper, and currently CBMM Memo #109.
Tweet10_crop.png Arturo Deza, Talia Konkle. Emergent Properties of Foveated Perceptual Systems. ArXiv, 2020. Under review as a conference paper, and presented at the non-archival venue of VSS (Vision Sciences Society). VSS-Poster VSS Video Poster Walkthrough
Publications Code/Data/Demo
640x640_s0.5_a1_o0.5_iter_50.png Arturo Deza, Yi-Chia Chen , Bria Long, Talia Konkle. Accelerated Texforms: Alternative Methods for Generating Unrecognizable Object Images with Preserved Mid-Level Features. Cognitive Computational Neuroscience (CCN), 2019. Code Poster
template_SCORCH_CVPR.png Arturo Deza, Amit Surana, Miguel P. Eckstein. Assessment of Faster R-CNN in Man-Machine collaborative search. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Coming soon!
Foveated_Storke.png Arturo Deza, Aditya Jonnalagadda, Miguel P. Eckstein. Towards Metamerism via Foveated Style Transfer International Conference on Learning Representations (ICLR), 2019. Code Poster
Peripheral_Representations.png Arturo Deza. Peripheral Representations: From Perception to Visual Search PhD Thesis , 2018.
d_prime_heatmaps.png Arturo Deza, Jeffrey R. Peters, Grant S. Taylor, Amit Surana, Miguel P. Eckstein. Attention Allocation Aid for Visual Search. Conference on Human Factors in Computing Systems (CHI), 2017. Video
Piranhas_img.png Arturo Deza, Miguel P. Eckstein, Can Peripheral Representations Improve Clutter Metrics on Complex Scenes? Neural Information Processing Systems (NIPS), 2016 NIPS Poster Spotlight Video Video Demo Code
grumpy_cat.jpg Arturo Deza, Devi Parikh, Understanding Image Virality. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. Virality Website
Software
Foveal_Colors.png Arturo Deza, Emre Akbas , Miguel P. Eckstein. Piranhas Toolkit: Peripheral Architectures for Natural, Hybrid and Artificial Systems GitHub
Posters and Workshops
Philosoraptor.png Arturo Deza, Devi Parikh, Understanding Image Virality. IEEE CVPR Scene Understanding Worshop (SUNw) nvidia_pic.png Nvidia Best Poster Award, 2015.
VSS_2015.JPG Arturo Deza, Emre Akbas. , Miguel P. Eckstein, Scene Context and Set Size effects in Search. Vision Sciences Society (VSS) - Visual Search, 2015.
Conference & Symposium Talks (The first author delivered each talk)
AAAD.png Amit Surana, Jeff Peters, Arturo Deza, Grant S. Taylor ,Luca Bertuccelli, Francesco Leonardi , Miguel P. Eckstein. Optimal User Attention Allocation in a Multi-tasking Environment. American Controls Conference (ACC) Workshop, 2016.
148.jpg Arturo Deza, Grant S. Taylor , Miguel P. Eckstein, The Influence of Visual Clutter on Search Guidance with Complex Scenes. Vision Sciences Society (VSS) - Visual Search, 2016
Cosyne.png Miguel P. Eckstein, Arturo Deza,Emre Akbas. Spatial Attention with synthetic cues and real scenes. Cosyne, 2016.
Miscellaneous
cuda_logo.png NeuroSurfer (internet alterego) [Solved] Titan X for CUDA 7.5 login-loop error [Ubuntu 14.04] , Nvidia Forums CUDA Drivers for Linux

News:

  • I joined UTRC (United Technologies Research Center) as a Deep Learning Intern over the summer (2017)!
  • Reviewer of ICCV workshop: https://sites.google.com/site/mbcc2017w/home
  • I will be giving a talk at the Instituto de Matematicas and Ciencias Afines Research Center in Lima, Peru in December on my research.
  • I will be giving a talk at the Mechanical Engineering Department of Universidad Nacional de Ingenieria (my alma mater) in Lima, Peru about my research in December.
  • I will be giving a talk at the Telecommunications Research Center (INICTEL) in Lima, Peru about my research.
  • I am currently serving as an assigned reviewer for IUI 2017.
  • I have server as a volunteer reviewer for NIPS 2016.
  • I am currently organizing the Human and Machine Perception Seminar as part of the Dynamical Neuroscience weekly seminar class.

Ranking of conference proceedings and journals in Artificial Intelligence related fields: Computer Vision, AI and Machine Learning, Robotics, Computer Graphics, Human-Computer Interaction.
Ranking of conference proceedings and journals in Neuroscience related fields: Neurology, Life Sciences

"Give me a computer, a piano and a surfboard, and I will live happy for the rest of my life" .