| 2025 | ICML | DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation. | Yunbei Zhang, Akshay Mehra, Shuaicheng Niu, Jihun Hamm |
| 2025 | MICCAI | SOFA: Deep Learning Framework for Simulating and Optimizing Atrial Fibrillation Ablation. | Yunsung Chung, Chanho Lim, Ghassan Bidaoui, Christian Massad, Nassir Marrouche, Jihun Hamm |
| 2025 | WACV | Enhancing Skin Disease Diagnosis: Interpretable Visual Concept Discovery with SAM. | Xin Hu, Janet Wang, Jihun Hamm, Rie Roselyne Yotsu, Zhengming Ding |
| 2025 | WACV | OT-VP: Optimal Transport-Guided Visual Prompting for Test-Time Adaptation. | Yunbei Zhang, Akshay Mehra, Jihun Hamm |
| 2024 | CVPR | Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport. | Akshay Mehra, Yunbei Zhang, Jihun Hamm |
| 2024 | CVPR | Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation. | Janet Wang, Yunbei Zhang, Zhengming Ding, Jihun Hamm |
| 2024 | MICCAI | From Majority to Minority: A Diffusion-Based Augmentation for Underrepresented Groups in Skin Lesion Analysis. | Janet Wang, Yunsung Chung, Zhengming Ding, Jihun Hamm |
| 2024 | WACV | On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization. | Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm |
| 2023 | MICCAI | FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation. | Yunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm |
| 2022 | ECCV | A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness. | Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao |
| 2022 | IJCAI | Online Evasion Attacks on Recurrent Models: The Power of Hallucinating the Future. | Byunggill Joe, Insik Shin, Jihun Hamm |
| 2021 | ACML | Penalty Method for Inversion-Free Deep Bilevel Optimization. | Akshay Mehra, Jihun Hamm |
| 2021 | CVPR | How Robust Are Randomized Smoothing Based Defenses to Data Poisoning? | Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm |
| 2019 | NDSS | Statistical Privacy for Streaming Traffic. | Xiaokuan Zhang, Jihun Hamm, Michael K. Reiter, Yinqian Zhang |
| 2018 | ICML | K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning. | Jihun Hamm, Yung-Kyun Noh |
| 2017 | ICASSP | Enhancing utility and privacy with noisy minimax filters. | Jihun Hamm |
| 2017 | ICASSP | Crowd-ML: A library for privacy-preserving machine learning on smart devices. | Jihun Hamm, Jackson Luken, Yani Xie |
| 2016 | ICML | Learning privately from multiparty data. | Jihun Hamm, Yingjun Cao, Mikhail Belkin |
| 2015 | AISTATS | Preserving Privacy of Continuous High-dimensional Data with Minimax Filters. | Jihun Hamm |
| 2015 | ICDCS | Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices. | Jihun Hamm, Adam C. Champion, Guoxing Chen, Mikhail Belkin, Dong Xuan |
| 2015 | WACV | Qualitative Tracking Performance Evaluation without Ground-Truth. | Bohyung Han, Jihun Hamm |
| 2013 | MICCAI | FLOOR: Fusing Locally Optimal Registrations. | Dong Hye Ye, Jihun Hamm, Benoit Desjardins, Kilian M. Pohl |
| 2012 | MICCAI | Regional Manifold Learning for Deformable Registration of Brain MR Images. | Dong Hye Ye, Jihun Hamm, Dongjin Kwon, Christos Davatzikos, Kilian M. Pohl |
| 2011 | WACV | Personalized video summarization with human in the loop. | Bohyung Han, Jihun Hamm, Jack Sim |
| 2009 | MICCAI | Efficient Large Deformation Registration via Geodesics on a Learned Manifold of Images. | Jihun Hamm, Christos Davatzikos, Ragini Verma |