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The PDF is probably easier to read.

General

Full Name Eric Slyman
Email slymane[at]oregonstate[dot]edu
Pronouns they/he
Links

Education

  • 2021 - 2026
    Ph.D., Artificial Intelligence & Computer Science
    Oregon State University (4.00/4.00 GPA)
    Department of Electrical Engineering & Computer Science
  • 2015 - 2020
    B.S./M.S., Computer Science
    Western Washington University (4.00/4.00 GPA)
    Department of Computer Science
    Accelerated Master's Fast Track Program

Papers

Talks

  • 2023
    Bias Discovery in Vision-and-Language Artificial Intelligence
    • OSU Graduate Engineering Research Showcase
    • Invited to OSU Spring Board of Directors Meeting
    • Invited to ARCS Foundation Luncheon
  • 2021
    Corruption Tolerant Audiovisual Embeddings for Person Verification
    Computing@PNNL Colloquium
  • 2021
    Fine-Grained Classroom Activity Detection
    Western Washington Data-Driven Discovery Seminar Series
  • 2019
    Few-Shot Image Segmentation Through Object Recognition
    Computer@PNNL Colloquium
  • 2019
    Machine Learning for Classroom Analysis
    WWU Distinguished Lecture Series

Research

  • 2021 -
    Graduate Fellow
    Oregon State University
    Department of Electrical Engineering & Computer Science
    Advised by Stefan Lee & Minsuk Kahng (previous)
    • Evaluated common Vision and Language (ViL) model pruning and quantization techniques for induced fairness disparities
    • Constructed dashboards to expose representational biases in ViL models trained on large web-crawled data
    • Developed interactive ViL clustering algorithms to aid in the creation of semantically aligned subgroups
  • 2022/23
    Research Intern
    Adobe
    Media Intelligence Lab
    Advised by Kushal Kafle & Scott Cohen
    • Proposed a novel fair deduplication algorithm to mitigate subgroup disparities induced by dataset pruning
    • Developed an interactive interface enabling users to rapidly develop behavioral tests for ViL models
    • Coded expert judgments of model performance to determine generally expected model competencies
    • Trained LAION-scale CLIP models distributed on 100+ GPUs
  • 2021
    Post-Master's Research Associate
    Pacific Northwest National Laboratory
    Data Science & Analytics Group
    Advised by Karl Pazdernik & Tim Doster
    • Researched robust audiovisual fusion for person verification with varying modality corruptions
    • Developed a differentiable rendering pipeline over PyTorch 3D for discovering natural adversarial examples
    • Participated in STEM outreach with PNNL STEM Ambassadors as a public science communicator
  • 2017 - 2020
    Graduate Research Assistant
    Western Washington University
    Department of Computer Science
    Advised by Brian Hutchinson
    • Researched fine-grained classroom activity detection from audio
    • Researched spatio-temporal generative adversarial Earth system model (ESM) emulation
    • Investigated ImageNet error via iterative unsupervised clustering to expose low-performing subgroups
  • 2019
    Research Intern, National Security Internship Program (NSIP)
    Pacific Northwest National Laboratory
    Data Science & Analytics Group
    Advised by Andrew Avila
    • Researched few-shot object detection and segmentation for large scale image sort and summary
    • Developed an algorithm to produce learned image attention masks for use in few-shot image classification
    • Utilized Prototypical Nets, Feature Pyramid Nets (FPN), Single-Shot Object Detectors (SSD, YOLOv3, RetinaNet)

Professional

  • 2023 -
    Graduate Teaching Assistant
    Oregon State University
    Department of Electrical Engineering & Computer Science
    • CS 567 Lab Studies in Software Engineering & HCI
    • AI 434 Machine Learning & Data Mining
  • 2020
    AI Marketing Engineering Intern
    NVIDIA
    • Owned technical marketing research for Jarvis ConvAI framework to inform product positioning
    • Performed hands-on analysis of SOTA ConvAI models in order to identify their strengths and weaknesses
    • Surveyed literature of ConvAI technologies including 100+ NLU/NLP, ASR, and TTS papers, for key stakeholders
  • 2019 - 2020
    Graduate Teaching Assistant
    Western Washington University
    Department of Computer Science
    • CS 597 Deep Learning
    • CS 301 Formal Languages
    • CS 241 Data Structures
    • CS 141 Computer Programming I
    • CS 102 Computer-Mediated Communications
  • 2016 - 2019
    Student Manager
    Western Washington University
    Student Technology Center
    • Organizing and running workshops on technologies such as Alexa skills, home automation, and Adobe Creative Cloud
    • Interfacing with other academic and private entities, such as Amazon Education, to facilitate student learning
    • Training staff in interpersonal communication skills and teaching methods

Service

  • 2022 -
    Conference & Journal Reviewing
    Various
    • CVPR 2022
    • NeurIPS 2023
    • TMLR 2023
    • CHI 2022
    • AAAI 2022
  • 2023 -
    Co-President
    Oregon State University
    AI Graduate Student Association
    • Elected leadership position in club of 200+ graduate EECS students
    • Organized application mentoring for underserved students applying to the AI program
  • 2020 - 2022
    Early Career Professional Mentor
    Western Washington University
    CS/M Scholars Program
    Invited mentor for a NSF funded program supporting women, underrepresented minorities, and first generation students in pursuit of degrees in computer science and math

Honors/Awards

  • 2024
    Selected for Featured Program in State of Diversity at Oregon State
    Oregon State University
  • 2023
    International Conference on Computer Vision (ICCV) DEI Grant
    CvF/IEEE
  • 2022
    Intern Code Quality Jam, Category Winner and 2nd Best Overall
    Adobe
  • 2022
    Edith McDougall Scholarship
    Oregon State University
  • 2021
    Norman & Evelyn Wildish Distinguished Graduate Fellowship
    Oregon State University
  • 2019/21
    Academic Excellence in Computer Science Award
    Western Washington university
  • 2021
    Alumni Division Winner, WWU Hackathon
    ACM
  • 2019/2020
    Track Global Fellowship in Computer Science
    Western Washington university
  • 2020
    Travel Grant, ACM FAccT
    ACM
  • 2019
    Travel Grant, NeurIPS
    Western Washington university
  • 2019
    Academic Honors, Magna Cum Laude
    Western Washington university
  • 2019
    Susan Brown Advancing Technology Education Scholarship
    Western Washington university
  • 2019
    Distinguished Speaker, Scholars Week
    Western Washington university
  • 2018
    Best Presentation, WWU Hackathon
    ACM

Coursework

AI/ML Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Causal Inference, Intelligent Agents
HCI/VIS Human-Computer Interaction, Inclusive Design, Visual Analytics, Scientific Data Visualization, Social & Ethical Issues in AI, Experimental Design

Skills

Languages Python, JavaScript, C++, Java, R, MATLAB, SQL
AI Tools TensorFlow, PyTorch, Keras, OpenCV, scikit-learn, NLTK, spaCy
VIS Tools D3.js, Tableau, ggplot2, matplotlib, seaborn
Other Git, Docker, AWS, GCP, Azure, Jupyter, RStudio, VSCode, PyCharm, IntelliJ, Eclipse, NetBeans, MATLAB, Unity, Unreal Engine