Darryl Hannan

Bio

I'm a Data Scientist at Pacific Northwest National Laboratory in the Foundational Data Science Group. I received my PhD from Drexel University as a NSF GRFP Fellow and member of the SPARSE and TAIL labs, and my Master's degree from UNC as a member of the MURGe-Lab. My primary research interests are in vision-language modeling, biologically-inspired learning approaches, and few-shot learning. Some of my recent projects have focused on machine unlearning, zero-shot object detection, and change detection.

News

• January 2026 - Paper Accepted to JMM 2026.
• October 2025 - Joined Pacific Northwest National Laboratory as full time staff.
• September 2025 - Paper Accepted to SPIGM NeurIPS Workshop.
• May 2025 - Paper Accepted at ICIP.
• April 2025 - Paper Accepted at Responsible Generative AI CVPR Workshop.
• March 2025 - Paper Accepted at MORSE CVPR Workshop.
• March 2025 - Paper Accepted at ML4RS ICLR Workshop.
• October 2024 - Joined Pacific Northwest National Laboratory as a Postdoc.
• September 2024 - Graduated from Drexel with Ph.D.
• February 2024 - Paper Accepted at ISBI 2024.
• January 2024 - Paper Accepted at SSIAI 2024.
• June 2023 - Joining Pacific Northwest National Laboratory as part of the National Security Internship Program.
• October 2023 - Paper Accepted at IAAI 2023.
• June 2022 - Joined Drexel University as a PhD Student.

Publications

1. Seeing Beyond Redundancy: Task Complexity's Role in Vision Token Specialization in VLLMs
   Darryl Hannan, John Cooper, Dylan White, and Yijing Watkins
2. Model Editing and Machine Unlearning for Mission Priorities
   JMM 2026
   Scott Mahan, Henry Kvinge, Timothy Doster, Eric Yeats, Darryl Hannan, Yiran Jia, Aaron Jacobson, and Wilson Fearn
3. Saddle-Free Guidance: Improved On-Manifold Sampling without Labels or Additional Training
   Eric Yeats, Darryl Hannan, Wilson Fearn, Timothy Doster, Henry Kvinge, and Scott Mahan
4. A Connection Between Score Matching and Local Intrinsic Dimension
   NeurIPS SPIGM Workshop 2025
   Eric Yeats, Aaron Jacobson, Darryl Hannan, Yiran Jia, Timothy Doster, Henry Kvinge, and Scott Mahan
5. FMG-Det: Foundation Model Guided Robust Object Detection
   ICIP 2025
   Darryl Hannan, Timothy Doster, Henry Kvinge, Adam Attarian, and Yijing Watkins
6. Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization
   CVPR MORSE Workshop 2025
   Darryl Hannan, John Cooper, Dylan White, Henry Kvinge, Timothy Doster, and Yijing Watkins
7. Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge
   CVPR ReGenAI Workshop 2025
   Eric Yeats, Scott Mahan, Darryl Hannan, Timothy Doster, and Henry Kvinge
8. An Analysis of Multimodal Large Language Models for Object Localization in Earth Observation Imagery
   ICLR ML4RS Workshop 2025
   Darryl Hannan, John Cooper, Dylan White, Henry Kvinge, Timothy Doster, and Yijing Watkins
9. The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data
   IJCAI XAI Workshop 2024
   Ximing Wen, Rosina O. Weber, Anik Sen, Darryl Hannan, Steven C. Nesbit, Vincent Chan, Alberto Goffi, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, and Christopher J. MacLellan
10. Interpretable Models for Detecting and Monitoring Elevated Intracranial Pressure
    ISBI 2024
    Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, and Christopher J. MacLellan
11. Event-to-Video Conversion for Overhead Object Detection
    SSIAI 2024
    Darryl Hannan, Ragib Arnab, Gavin Parpart, Garrett T. Kenyon, Edward Kim, and Yijing Watkins
12. MobilePTX: Sparse Coding for Pneumothorax Detection Given Limited Training Examples
    IAAI 2023
    Darryl Hannan, Steven C. Nesbit, Ximing Wen, Glen Smith, Qiao Zhang, Alberto Goffi, Vincent Chan, Michael J. Morris, John C. Hunninghake, Nicholas E. Villalobos, Edward Kim, Rosina O. Weber, and Christopher J. MacLellan
13. StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
    ECCV 2022
    Adyasha Maharana, Darryl Hannan, and Mohit Bansal
14. RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
    NAACL 2022
    Xinya Du, Zixuan Zhang, Sha Li, Pengfei Yu, Hongwei Wang, Tuan Lai, Xudong Lin, Ziqi Wang, Iris Liu, Ben Zhou, Haoyang Wen, Manling Li, Darryl Hannan, Jie Lei, Hyounghun Kim, Rotem Dror, Haoyu Wang, Michael Regan, Qi Zeng, Qing Lyu, Charles Yu, Carl Edwards, Xiaomeng Jin, Yizhu Jiao, Ghazaleh Kazeminejad, Zhenhailong Wang, Chris Callison-Burch, Mohit Bansal, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Martha Palmer, and Heng Ji
15. Improving Generation and Evaluation of Visual Stories via Semantic Consistency
    NAACL 2021
    Adyasha Maharana, Darryl Hannan, and Mohit Bansal
16. ManyModalQA: Modality Disambiguation and QA over Diverse Inputs
    AAAI 2020
    Darryl Hannan, Akshay Jain, and Mohit Bansal
17. Deep Sparse Coding for Invariant Halle Berry Neurons
    CVPR 2018
    Edward Kim, Darryl Hannan, and Garrett Kenyon