1 citations · 2 across the 11 of their papers we have counts for
11 papers
A Mixture of Experts Foundation Model for Scanning Electron Microscopy Image Analysis
Sk Miraj Ahmed, Yuewei Lin, Chuntian Cao +9
Scanning Electron Microscopy (SEM) is indispensable in modern materials science, enabling high-resolution imaging across a wide range of structural, chemical, and functional invest…
Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference
Sk Miraj Ahmed, Xi Yu, Yunqi Li +2
Accurate biodiversity identification from large-scale field data is a foundational problem with direct impact on ecology, conservation, and environmental monitoring. In practice, t…
A Certified Unlearning Approach without Access to Source Data
Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury +1
With the growing adoption of data privacy regulations, the ability to erase private or copyrighted information from trained models has become a crucial requirement. Traditional unl…
Plug-and-Play Transformer Modules for Test-Time Adaptation
Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy +4
Parameter-efficient tuning (PET) methods such as LoRA, Adapter, and Visual Prompt Tuning (VPT) have found success in enabling adaptation to new domains by tuning small modules with…
FLASH: Federated Learning Across Simultaneous Heterogeneities
Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy +4
The key premise of federated learning (FL) is to train ML models across a diverse set of data-owners (clients), without exchanging local data. An overarching challenge to this date…
CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
Sk Miraj Ahmed, Fahim Faisal Niloy, Xiangyu Chang +3
Adapting to dynamic data distributions is a practical yet challenging task. One effective strategy is to use a model ensemble, which leverages the diverse expertise of different mo…