Research Overview

My research is primarily focused around the problem of recognition, including the representations and algorithms supporting solutions to it. I am particularly interested in features and learning-based methods that apply to both vision and language, thus breaking away from the persistent compartmentalization of recognition tasks (something hinted at by David Marr over 30 years ago). This has led to some interesting, and often unconventional approaches that can be applied to a broad set of areas including computer vision, machine learning, human biometrics, and the digital humanities. Specifically, my work is looking at open set recognition, extreme value theory models for visual recognition, biologically-inspired learning algorithms, and stylometry.

Walter J. Scheirer

Curriculum Vitae

PDF Format

Postdoctoral Fellows

Daniel Moreira

Graduate Students

Sophia Abraham

Sreya Banerjee

Zachariah Carmichael

Samuel Grieggs

Jin Huang

Jeffery Kinnison

Derek Prijatelj

Brandon RichardWebster

Bingyu Shen

Rosaura Vidal Mata (Co-Advised with Kevin Bowyer)

William Theisen


Spring 2020: CSE 40567/60567 Computer Security

Fall 2019: CSE 40171 Artificial Intelligence

Spring 2019: CSE 40567/60567 Computer Security

Fall 2018: CSE 40171 Artificial Intelligence

Spring 2018: CSE 40567/44567/60567 Computer Security

Spring 2017: CSE 40567/60567 Computer Security

Spring 2016: CSE 40567/60567 Computer Security

Fall 2015: CSE 40537/60537 Biometrics


Quantitative Intertextuality: Analyzing the Markers of Information Reuse (Springer-Nature) with Christopher W. Forstall

Extreme Value Theory-based Methods for Visual Recognition (Morgan & Claypool Publishers)

Recent Publications (see all)

  1. "Bridging the Gap Between Computational Photography and Visual
    Rosaura G. VidalMata, Sreya Banerjee, Brandon RichardWebster, Michael Albright,
    Pedro Davalos, Scott McCloskey, Ben Miller, Asong Tambo, Sushobhan Ghosh,
    Sudarshan Nagesh, Ye Yuan, Yueyu Hu, Junru Wu, Wenhan Yang, Xiaoshuai Zhang,
    Jiaying Liu, Zhangyang Wang, Hwann-Tzong Chen, Tzu-Wei Huang, Wen-Chi Chin,
    Yi-Chun Li, Mahmoud Lababidi, Charles Otto, Walter J. Scheirer,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    Accepted for Publicatiton in 2020.
  2. "Backdooring Convolutional Neural Networks via Targeted Weight Perturbations,"
    Jacob Dumford, Walter J. Scheirer,
    Proceedings of the IAPR/IEEE International Joint Conference on Biometrics (IJCB),
    September 2020.
  3. "The Next Generation of Human-Drone Partnerships: Co-Designing an Emergency
    Response System,"
    Ankit Agrawal, Sophia Abraham, Benjamin Burger, Chichi Christine, Luke Fraser,
    John Hoeksema, Sara Hwang, Elizabeth Travnik, Shreya Kumar, Walter J. Scheirer,
    Jane Cleland-Huang, Michael Vierhauser,
    Ryan Bauer, Steve Cox,
    Proceedings of the ACM CHI Conference on Human Factors in Computing Systems
    (Honorable Mention Award),
    April 2020.
  4. "An AI Early Warning System to Monitor Online Disinformation, Stop Violence,
    and Protect Elections,"
    Michael Yankoski, Tim Weninger, Walter J. Scheirer,
    Bulletin of the Atomic Scientists,
    March 2020.
  5. "Self-Driving Vehicles: Key Technical Challenges and Progress Off the Road,"
    Michael Milford, Samuel E. Anthony, Walter J. Scheirer,
    IEEE Potentials,
    January-February 2020.
  6. "PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition,"
    Brandon RichardWebster, Samuel E. Anthony, Walter J. Scheirer,
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI),
    September 2019.
  7. "A Neurobiological Evaluation Metric for Neural Network Model Search,"
    Nathaniel Blanchard, Jeffery Kinnison, Brandon RichardWebster, Pouya Bashivan,
    Walter J. Scheirer,
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
    June 2019.
  8. "Image Provenance Analysis at Scale,"
    Daniel Moreira, Aparna Bharati, Joel Brogan, Allan Pinto, Michael Parowski,
    Kevin Bowyer, Patrick Flynn, Anderson Rocha, Walter J. Scheirer,
    IEEE Transactions on Image Processing (T-IP),
    December 2018.
  9. "Visual Psychophysics for Making Face Recognition Algorithms More Explainable,"
    Brandon RichardWebster, So Yon Kwon, Christopher Clarizio, Samuel E. Anthony,
    Walter J. Scheirer,
    Proceedings of the European Conference on Computer Vision (ECCV),
    September 2018.

New Research in arXiv / bioRxiv

  1. "The Criminality From Face Illusion,"              
    Kevin Bowyer, Michael King, Walter J. Scheirer,
    June 2020.
  2. "Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in
    Untrimmed Sequences,"
    Rosaura G. VidalMata, Walter J. Scheirer, Hildegard Kuehne,
    January 2020.
  3. "Automatic Discovery of Political Meme Genres with Diverse Appearances,"
    William Theisen, Joel Brogan, Pamela Bilo Thomas, Daniel Moreira, Pascal Phoa,
    Tim Weninger
    , Walter J. Scheirer,
    January 2020.
  4. "Learning Transformation-Aware Embeddings for Image Forensics,"
    Aparna Bharati, Daniel Moreira, Patrick Flynn, Anderson Rocha, Kevin Bowyer,
    Walter J. Scheirer,
    January 2020.
  5. "Dynamic Spatial Verification for Large-Scale Object-Level Image Retrieval,"
    Joel Brogan, Aparna Bharati, Daniel Moreira, Kevin Bowyer, Patrick Flynn,
    Anderson Rocha, Walter J. Scheirer,
    December 2019.
  6. "Report on UG^2+ Challenge Track 1: Assessing Algorithms to Improve Video
    Object Detection and Classification from Unconstrained Mobility Platforms,"
    Sreya Banerjee, Rosaura G. VidalMata, Zhangyang Wang, Walter J. Scheirer,
    July 2019.
  7. "Measuring Human Perception to Improve Handwritten Document Transcription,"
    Samuel Grieggs, Bingyu Shen, Pei Li, Cana Short, Jiaqi Ma, Mihow McKenny,
    Melody Wauke, Brian Price, Walter J. Scheirer,
    April 2019.

Recent Projects (see all)

Unconventional Approaches to Hacking Neural Networks

Unconventional Approaches to Hacking Neural Networks

Spring 2018 - Present

Uncovering new vulnerabilities in neural network-based applications where security is a consideration

Keywords: machine learning, neural networks, face recognition, security, backdoors, exploits
Hardware-Aware Distributed Hyperparameter Optimization

Hardware-Aware Distributed Hyperparameter Optimization

Spring 2017 - Present

Intelligent mapping of hardware resources to model search tasks

Keywords: machine learning, hyperparameters, optimization, distributed computing, connectomics
Computational Models of Zebrafish Sensory Integration

Computational Models of Zebrafish Sensory Integration

Fall 2016 - Present

Modeling neural circuits to explain fish behavior and apply to generalized recognition problems in AI

Keywords: computational neuroscience, zebrafish, sensory integration, data fusion, extreme value theory
Image Restoration and Enhancement for Visual Recognition

Image Restoration and Enhancement for Visual Recognition

Fall 2016 - Present

Work to bridge the gap between computational photography and visual recognition

Keywords: deblurring, denoising, super-resolution, deep learning, object recognition, video
Face Synthesis

Face Synthesis

Fall 2015 - Present

Fast and accurate photo-quality face synthesis for use in face recognition work

Keywords: face synthesis, face recognition, face analysis, computer graphics, data augmentation
Learning-free Segmentation

Learning-free Image Segmentation

Fall 2015 - Present

Image segmentation for settings where machine learning-based approaches are slow and do not generalize

Keywords: image filtering, volumetric segmentation, connectomics, medical imaging, iris recognition
Tools for Neuroscience

Tools for Neuroscience

Fall 2015 - Present

Techniques to help neuroscientists understand neuroanatomy and function

Keywords: connectomics, electron microscopy, two-photon imaging, x-ray tomography, 3D reconstruction
Brain-informed Machine Learning

Brain-informed Machine Learning

Fall 2014 - Present

Applying measurements of neural activity to regularize machine learning models

Keywords: fMRI, psychophysics, classification, deep learning, neural-weights, object recognition
Visual Place Recognition

Visual Place Recognition

Spring 2013 - Present

Condition invariant visual place recognition for robot navigation inspired by vision science

Keywords: robotics, navigation, place recognition, whole image matching, patch matching, calibration
Is good recognition metric?

Good Recognition is Non-metric

Fall 2012 - Spring 2014

A new look at a fundamental question in computer vision: is recognition metric?

Keywords: machine learning, metric learning, recognition, face recognition, object recognition

Psychophysics for Computer Vision

Fall 2012 - Present

Measuring exemplar-by-exemplar dif´Čüculty and the pattern of errors of humans for supervised learning

Keywords: machine learning, psychology, citizen science, psychophysics, face detection, attributes
Open Set Recognition

Open Set Recognition

Spring 2011 - Present

Theory and algorithms that address the difficult problem of training without complete class knowledge

Keywords: machine learning, object recognition, face recognition, support vector machines, 1-vs-set machine
Extreme Value Theory for Visual Recognition

Extreme Value Theory for Visual Recognition

Spring 2008 - Present

The theory and practice of recognition score analysis for prediction and fusion

Keywords: calibration, meta-recognition, score analysis, object recognition, face recognition, attributes
Language and Literature

Language & Literature

Spring 2009 - Present

Machine learning and related statistical methods to improve the process by which intertextuality is studied

Keywords: computational linguistics, intertextuality, sound, stylistics, classics, authorship attribution
Digital Image and Video Forensics

Digital Image and Video Forensics

Spring 2008 - Present

Approaches to steganalysis, forgery detection and sensor fingerprinting

Keywords: forensics, forgery detection, data hiding, source identification, sensor fingerprinting

Recent Talks (see all)