Publications

A selection of peer-reviewed publications in computer vision, machine learning, and AI

Selected Conference Publications

  1. E. Kim, M. Shrestha, R. Foty, T. DeLay, V. Seyfert-Margolis, "Structured Extraction of Real World Medical Knowledge using LLMs for Summarization and Search", IEEE International Conference on Big Data (BigData), pp. 3421-3430, 2024.
  2. Z. Zhang, J. Duan, E. Kim, K. Xu, "Sparse Neurons Carry Strong Signals of Question Ambiguity in LLMs", Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.
  3. E. Kim, M. Daniali, J. Rego, G.T. Kenyon, "The Selectivity and Competition of the Mind's Eye in Visual Perception", International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.
  4. B. Shakibajahromi, E. Kim, D.E. Breen, "Rimeshgnn: A Rotation-Invariant Graph Neural Network for Mesh Classification", IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.
  5. D. Hannan, S.C. Nesbit, X. Wen, G. Smith, Q. Zhang, A. Goffi, V. Chan, M.J. Morris, J.C. Hunninghake, N.E. Villalobos, E. Kim, R.O. Weber, C.J. MacLellan, "Interpretable Models for Detecting and Monitoring Elevated Intracranial Pressure", 21st IEEE International Symposium on Biomedical Imaging (ISBI), 2024.
  6. M. Daniali, E. Kim, "Perception Over Time: Temporal Dynamics for Robust Image Understanding", IEEE Computer Society Conf. Computer Vision and Pattern Recognition, WiCS (CVPR-W), 2023.
  7. E. Kim, J. Rego, Y. Watkins, G. Kenyon, "Modeling Biological Immunity to Adversarial Examples", IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR), 2020. 22% acceptance (1470/6656) [PDF]
  8. Y. Watkins, E. Kim, A. Sornborger, G. Kenyon, "Using Sinusoidally-Modulated Noise as a Surrogate for Slow-Wave Sleep to Accomplish Stable Unsupervised Dictionary Learning in a Spike-Based Sparse Coding Models", IEEE Computer Society Conf. Computer Vision and Pattern Recognition Workshops (CVPR-W), 2020. [PDF]
  9. E. Kim, E. Lawson, K. Sullivan, G. Kenyon, "Spatiotemporal Sequence Memory for Prediction using Deep Sparse Coding", Neuro Inspired Computational Elements Workshop (NICE), 2019. [PDF]
  10. E. Kim, D. Hannan, G. Kenyon, "Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons", IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR), 2018. 29% acceptance (979/3300) [PDF]
  11. E. Kim, K. McCoy, "Multimodal Deep Learning using Images and Text for Information Graphic Classification", ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), 2018. 26% acceptance (28/108) Best Paper Nominee
  12. E. Kim, H. Li, X. Huang, "A Hierarchical Image Clustering Cosegmentation Framework", IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR), 2012. 26% acceptance (465/1776) [PDF]
  13. T. Shen, X. Huang, H. Li, E. Kim, S. Zhang, J. Huang, "A 3D Laplacian-Driven Parametric Deformable Model", IEEE International Conference on Computer Vision (ICCV), 2011. 24% acceptance [PDF]
  14. H. Li, E. Kim, X. Huang, L. He, "Object Matching with a Locally Affine-Invariant Constraint", IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR), 2010. 22.3% acceptance (383/1717) [PDF]

Peer-Reviewed Conference Publications

2025

  1. E. Kim, R. Foty, M. Shrestha, V. Seyfert-Margolis, "Conformal Prediction and Verification of Large Language Model Extractions in EHR Data", Safe, Ethical, Certified, Uncertainty-aware, Robust, and Explainable AI for Health Workshop, AAAI Fall Symposium, 2025.
  2. S. Somers, E. Kim, "Confidence Calibration in Large Language Models for Uncertainty Quantification: Affecting Calibration with Conditional Weight Updates", Safe, Ethical, Certified, Uncertainty-aware, Robust, and Explainable AI for Health Workshop, AAAI Fall Symposium, 2025.
  3. I. Isozaki, M. Shrestha, R. Console, E. Kim, "Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements", Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2025.
  4. M. Shrestha, Y. Ravichandran, E. Kim, "Secure Multiparty Generative AI", Third Workshop on Deployable AI, AAAI-2025, 2025.
  5. C. Onweller, E. Kim, K. McCoy, "Prompting Large Vision Language Models for use as Assistive Chart Summarizers", IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.

2024

  1. D. Hannan, R. Arnab, G. Parpart, G.T. Kenyon, E. Kim, Y. Watkins, "Event-To-Video Conversion for Overhead Object Detection", IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2024.
  2. X. Wen, R.O. Weber, A. Sen, D. Hannan, S.C. Nesbit, V. Chan, A. Goffi, M. Morris, J.C. Hunninghake, N.E. Villalobos, E. Kim, "The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data", International Joint Conferences on Artificial Intelligence Workshop on Explainable Artificial Intelligence (XAI), IJCAI Workshop, 2024.

2023

  1. J. Rego, Y. Watkins, G.T. Kenyon, E. Kim, M. Teti, "A Novel Model of Primary Visual Cortex Based on Biologically Plausible Sparse Coding", Applications of Machine Learning, SPIE Optical Engineering + Applications, 2023.
  2. C. Wang, J. Duan, C. Xiao, E. Kim, M. Stamm, K. Xu, "Semantic Adversarial Attacks via Diffusion Models", British Machine Vision Conference (BMVC), 2023.
  3. A. O'Brien, R. Weber, E. Kim, "Basis Learning for Dynamical Systems in the Presence of Incomplete Scientific Knowledge", International Conference on Artificial Intelligence and Knowledge Discovery (AIKE), 2023.
  4. A. O'Brien, R. Weber, E. Kim, "Investigating Causally Augmented Sparse Learning as a Tool for Meaningful Classification", International Conference on Artificial Intelligence and Knowledge Discovery (AIKE), 2023.
  5. D. Hannan, S. Nesbit, X. Wen, G. Smith, Q. Zhang, A. Goffi, V. Chan, M. Morris, J. Hunninghake, N. Villalobos, E. Kim, R. Weber, C. MacLellan, "MobilePTX: Sparse Coding for Pneumothorax Detection Given Limited Training Examples", Association for the Advancement of Artificial Intelligence (AAAI), IAAI, 2023.
  6. A. O'Brien, R. Weber, E. Kim, "Investigating SINDy as a Tool for Causal Discovery in Time Series Signals", International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.

2022

  1. C. Onweller, A. O'Brien, K. McCoy, E. Kim, "Distributional Semantics of Line Charts for Trend Classification", International Symposium on Visual Computing (ISVC), 2022.
  2. E. Kim, T. Ha, G.T. Kenyon, "Sparse Kernel Transfer Learning", International Symposium on Visual Computing (ISVC), 2022.
  3. S. Nesbit, A. O'Brien, J. Rego, G. Parpart, C. Gonzalez, G.T. Kenyon, E. Kim, T. Stewart, Y. Watkins, "Think Fast: Time Control in Varying Paradigms of Spiking Neural Networks", International Conference on Neuromorphic Systems (ICONS), 2022.
  4. G. Parpart, C. Gonzalez, T. Stewart, E. Kim, J. Rego, A. O'Brien, S. Nesbit, G.T. Kenyon, Y. Watkins, "Dictionary Learning with Accumulator Neurons", International Conference on Neuromorphic Systems (ICONS), 2022.
  5. A. O'Brien, E. Kim, "Toward Multi-Agent Algorithmic Recourse: Challenges from a Game Theoretic Perspective", Florida AI Research Society (FLAIRS), 2022.

2021

  1. Y. Alparslan, E. Moyer, I. Isozaki, D. Schwartz, A. Dunlop, S. Dave, E. Kim, "Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems", International Joint Conference on Neural Networks (IJCNN), 2021.
  2. E. Kim, C. Onweller, A. O'Brien, K. McCoy, "The Interpretable Dictionary in Sparse Coding", Association for the Advancement of Artificial Intelligence, Explainable Agency in Artificial Intelligence Workshop (AAAI Workshop), 2021. 61% acceptance (26/42)

2020

  1. E. Kim, C. Onweller, K. McCoy, "Information Graphic Summarization using a Collection of Multimodal Deep Neural Networks", International Conference on Pattern Recognition (ICPR), 2020. 43% acceptance (1411/3250) [PDF]
  2. D. Schwartz, Y. Alparslan, E. Kim, "Regularization and Sparsity for Adversarial Robustness and Stable Attribution", International Symposium on Visual Computing (ISVC), 2020. 67% acceptance (118/175) [PDF]
  3. J. Carter, J. Rego, D. Schwartz, V. Bhandawat, E. Kim, "Learning Spiking Neural Network Models of Drosophila Olfaction", International Conference on Neuromorphic Systems (ICONS), pp. 1-5, 2020. [PDF]
  4. J. Marharjan, B. Mitchell, V.W.S. Chan, E. Kim, "Guided Ultrasound Imaging using a Deep Regression Network", Ultrasonic Imaging and Tomography, SPIE Medical Imaging, 2020. [PDF]

2019

  1. E. Kim, J. Yarnall, P. Shah, G. Kenyon, "A Neuromorphic Sparse Coding Defense to Adversarial Images", International Conference on Neuromorphic Systems (ICONS), 2019. [PDF]

2017

  1. E. Kim, S. Mente, A. Keenan, V. Gehlot, "Digital Pathology Data for Improved Deep Neural Network Classification", Imaging Informatics for Healthcare, Research, and Applications, SPIE Medical Imaging, 2017. [PDF]

2016

  1. E. Kim, C. Moritz, "Enhancing the Communication Spectrum in Collaborative Virtual Environments", 12th International Symposium on Visual Computing (ISVC), 2016. 36% acceptance, oral (80/220) [PDF]
  2. E. Kim, S. Vangala, "Deep Action Unit Classification using a Binned Intensity Loss and Semantic Context Model", 23rd International Conference on Pattern Recognition (ICPR), 2016. 56% acceptance (673/1200) [PDF]
  3. E. Kim, S. Vangala, "Vinereactor: Crowdsourced Spontaneous Facial Expression Data", International Conference on Multimedia Retrieval (ICMR), 2016. 50% acceptance (36/72)
  4. E. Kim, M. Corte-Real, Z. Baloch, "A Deep Semantic Mobile Application for Thyroid Cytopathology", SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 2016. (oral presentation) [PDF]

2015

  1. T. Xu, E. Kim, X. Huang, "Adjustable AdaBoost Classifier and Pyramid Features for Image-based Cervical Cancer Diagnosis", International Symposium on Biomedical Imaging (ISBI), 2015. 54% acceptance (390/714), Top 18%, oral Nominated Best Student Paper [PDF]
  2. E. Kim, Z. Baloch, C. Kim, "Computer Assisted Detection and Analysis of Tall Cell Variant Papillary Thyroid Carcinoma in Histological Images", SPIE Medical Imaging: Digital Pathology, 2015. (oral presentation) [PDF]
  3. T. Xu, X. Huang, E. Kim, L. Rodney Long, S. Antani, "Multi-test Cervical Cancer Diagnosis with Missing Data Estimation", SPIE Medical Imaging: Computer Aided Diagnosis, 2015. (oral presentation) [PDF]

2014

  1. S. Bouloutian, E. Kim, "Artificial Intelligence Gaming Assistant for Google Glass", International Symposium on Visual Computing (ISVC), 2014. 46% acceptance (129/280) [PDF]

2011

  1. E. Kim, X. Huang, J. Heflin, "Finding VIPS - A Visual Image Persons Search Using A Content Property Reasoner and Web Ontology", IEEE International Conference on Multimedia & Expo (ICME), 2011. 29% acceptance (223/744), Top 8%, oral [PDF]
  2. E. Kim, S. Antani, X. Huang, L.R. Long, D. Demner-Fushman, "Using Relevant Regions in Image Search and Query Refinement for Medical CBIR", SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 2011. (oral presentation) [PDF]

2010

  1. E. Kim, T. Shen, X. Huang, "A Parallel Cellular Automata with Label Priors for Interactive Brain Tumor Segmentation", 23rd IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2010. 45% acceptance (81/178), oral [PDF]
  2. E. Kim, X. Huang, G. Tan, L.R. Long, S. Antani, "A Hierarchical SVG Image Abstraction Layer for Medical Imaging", SPIE Medical Imaging: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 2010. (oral presentation) [PDF]

2009

  1. E. Kim, W. Wang, H. Li, X. Huang, "A Parallel Annealing Method For Automatic Color Cervigram Image Segmentation", Medical Image Computing and Computer Assisted Intervention (MICCAI-GRID), 2009. (oral presentation) [PDF]

Journal Publications

  1. L. Robinson, A. Feting, I. Isozaki, V. Seyfert-Margolis, M. Jay, E. Kim, C. Cairns, "Time-varying Effects of COVID-19 Vaccination on Symptomatic and Asymptomatic Infections in a Prospective University Cohort in the USA", British Medical Journal (BMJ) Open, Vol. 15, Issue 2, e084408, 2025.
  2. S. Tripathi, K. Gabriel, P.K. Tripathi, E. Kim, "Large Language Models Reshaping Molecular Biology and Drug Development", Journal of Chemical Biology and Drug Design, Vol. 103, Issue 6, 2024.
  3. M. Daniali, P. Galer, D. Lewis-Smith, S. Parthasarathy, E. Kim, D. Salvucci, J. Miller, S. Haag, I. Helbig, "Enriching Representation Learning using 53 Million Patient Notes through Human Phenotype Ontology Embedding", Artificial Intelligence in Medicine, Vol. 139, 2023.
  4. S. Tripathi, A. Augustin, E. Kim, "Longitudinal Neuroimaging Data Classification for Early Detection of Alzheimer's Disease using Ensemble Learning Models", TechRxiv, 2022.
  5. S. Tripathi, A. Augustin, F. Dako, E. Kim, "Turing Test Inspired Method for Analysis of Biases Prevalent in Artificial Intelligence-Based Medical Imaging", AI and Ethics, 2023.
  6. S. Tripathi, A. Augustin, E. Moyer, A. Zavalny, S. Dheer, R. Sukumaran, B. Gorski, D. Schwartz, F. Dako, E. Kim, "RadGenNets: Deep Learning-Based Radiogenomics Model For Gene Mutation Prediction In Lung Cancer", Informatics in Medicine Unlocked, 2022.
  7. S. Tripathi, A. Augustin, R. Sukumaran, S. Dheer, E. Kim, "HematoNet: Expert Level Classification of Bone Marrow Cytology Morphology in Hematological Malignancy with Deep Learning", Artificial Intelligence in the Life Sciences, December 2022.
  8. T. Xu, H. Zhang, C. Xin, E. Kim, L.R. Long, Z. Xue, S. Antani, X. Huang, "Multi-feature Based Benchmark for Cervical Dysplasia Classification Evaluation", Pattern Recognition, September 2016.
  9. J. Park, E. Kim, R. Werner, "Inpatient Hospital Charge Variability of U.S. Hospitals", Journal of Internal Medicine, May 2015. [PDF]
  10. D. Song, E. Kim, X. Huang, J. Patruno, H. Munoz-Avila, J. Heflin, L. Rodney Long, S. Antani, "Multi-modal Entity Coreference for Cervical Dysplasia Diagnosis", IEEE Transactions on Medical Imaging, Vol. 34, No. 1, pp. 229-245, January 2015. [PDF]
  11. E. Kim, X. Huang, G. Tan, "Markup SVG - An Online Content Aware Image Abstraction and Annotation Tool", IEEE Transactions on Multimedia, Vol. 13, Issue 5, October 2011. [PDF]

Books and Book Chapters

  1. G. Bebis, Z. Yin, E. Kim, J. Bender, K. Subr, B.C. Kwon, J. Zhao, D. Kalkofen, "Advances in Visual Computing: 15th International Symposium", International Symposium on Visual Computing (ISVC) 2020, San Diego, CA, USA, Proceedings, Part II, Vol. 12510, Springer Nature, 2020.
  2. E. Kim, X. Huang, "A Data Driven Approach to Cervigram Image Analysis and Classification", Color Medical Image Analysis, Lecture Notes in Computational Vision and Biomechanics, Volume 6, 2013. [PDF]