Eric Slyman (they/them)

AI/CS Ph.D Student, Oregon State University

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Hi folks! I’m a Ph.D. student at the intersection of multimodal AI, human-computer interaction, and fairness in the Artificial Intelligence and Computer Science programs at Oregon State University where I’m advised by Stefan Lee and Minsuk Kahng.

My current research focuses on building systems to test and diagnose very large-scale vision and language models, such as CLIP, ViLBERT, LXMERT, and more. I am adapting and extending methodologies from behavioral testing and creating human-in-the-loop systems to allow intuitive ways for users to poke at model failure states and vulnerabilities.

In addition to research, I am also the Co-President of OSU’s AI Graduate Student Association where I organize social and professional events for our AI community and am working to stand up support for students interested in our program from underrepresented backgrounds, such as application reviews.

news

Jun 13, 2022 Joined Adobe as a Research Intern in the Media Intelligence Lab!
Apr 29, 2022 Our paper “Conditional Emulation of Global Precipitation With Generative Adversarial Networks” was accepted at ICLR AI4Earth.
Dec 1, 2021 Our paper “Fine-Grained Classroom Activity Detection from Audio with Neural Networks” was accepted at AAAI AI4EDU 2022.
May 5, 2021 I was invited to the OSU Outstanding Scholars Program and won the Norman & Evelyn Wildish Distinguished Graduate Fellowship!
Apr 25, 2021 I will be attending Oregon State University for a double-major AI/CS Ph.D. this Fall. I’ll be working at the intersection of multimodal AI, explainability, and HCI under co-advisement from Stefan Lee and Minsuk Kahng.

referred works

  1. ICLR
    Conditional Emulation of Global Precipitation With Generative Adversarial Networks
    Alexis Ayala, Chris Drazic, Seth Bassetti,  Eric SlymanBrenna Nieva, Piper Wolters, Kyle Bittner, Claudia TebaldiBen Kravitz, and Brian Hutchinson
    ICLR Workshop on AI for Earth and Space Science 2022
  2. AAAI
    Fine-Grained Classroom Activity Detection from Audio with Neural Networks
    Eric SlymanChris Daw, Morgan Skrabut, Ana Usenko, and Brian Hutchinson
    AAAI Workshop on AI for Education 2022
  3. NOAA
    Conditioned Emulation of Global Climate Models With Generative Adversarial Networks
    Alex Ayala, Chris Drazic,  Eric Slyman, Piper Wolters, Brenna NievaBrian HutchinsonClaudia Tebaldi, and Ben Kravitz
    NOAA Workshop on Leveraging AI in Envrionmental Sciences 2021
  4. W2D2S2
    Fine-Grained Classroom Activity Detection
    Eric SlymanChris Daw, Morgan Skrabut, Ana Usenko, and Brian Hutchinson
    Western Washington Data-driven Discovery Seminar Series 2021