I’m a Postdoctoral Research Assistant at Pacific Northwest National Laboratory in the Foundational Data Science Group. I recieved my PhD from Drexel University as a NSF GRFP Fellow and member of the SPARSE and TAIL labs. My primary research interests are in language-vision tasks, neuromorphic computing, and biologically-inspired learning approaches. I recieved my Master’s degree from UNC as a member of the MURGe-Lab.
News
- September 2024 - Graduated from Drexel with Ph.D.
- February 2024 - Paper Accepted at ISBI 2024
- January 2024 - Paper Accepted at SSIAI 2024
- June 2023 - I will be 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
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
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
Event-to-Video Conversion for Overhead Object Detection
SSIAI 2024
Darryl Hannan, Ragib Arnab, Gavin Parpart, Garrett T. Kenyon, Edward Kim, and Yijing Watkins
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
StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
ECCV 2022
Adyasha Maharana, Darryl Hannan, and Mohit Bansal
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
Improving Generation and Evaluation of Visual Stories via Semantic Consistency
NAACL 2021
Adyasha Maharana, Darryl Hannan, and Mohit Bansal
ManyModalQA: Modality Disambiguation and QA over Diverse Inputs
AAAI 2020
Darryl Hannan, Akshay Jain, and Mohit Bansal
Deep Sparse Coding for Invariant Halle Berry Neurons
CVPR 2018
Edward Kim, Darryl Hannan, and Garrett Kenyon