Research
I develop efficient, explainable, and structure-aware machine learning methods across computer vision, signal processing, geoscience, healthcare, and large language models.
Full list: Google Scholar|† first author|* corresponding author
Media
Research Topics
Geospatial AI
How can efficient learning map palms, monitor mining, and track environmental change at scale?
Geospatial AI
How can efficient learning map palms, monitor mining, and track environmental change at scale?
AwakeForest: An Interactive Geospatial Platform for Large-Scale Forest Imagery|[IJCAI Demo'26]|Preprint
Learning Where to Embed: Noise-Aware Positional Embedding for Query Retrieval in Small-Object Detection|[ICMR'26]|Paper|Preprint|Code
Center-guided Classifier for Semantic Segmentation of Remote Sensing Images|[TGRS'26]|Paper|Preprint
From Orthomosaics to Raw UAV Imagery: Enhancing Palm Detection and Crown-Center Localization|[IGARSS'26]|Preprint
MoSAiC: Multi-Modal Multi-Label Supervision-Aware Contrastive Learning for Remote Sensing|[arXiv'25]|Preprint
Efficient Localization and Spatial Distribution Modeling of Canopy Palms Using UAV Imagery|[TGRS'25]|Paper|Preprint
Detection and Geographic Localization of Natural Objects in the Wild: A Case Study on Palms|[IJCAI'25, Oral]|Paper
PalmProbNet: A Probabilistic Approach to Understanding Palm Distributions in Ecuadorian Tropical Forest via Transfer Learning|[ACMSE'24]|Paper|Preprint
Change Detection of Amazonian Alluvial Gold Mining Using Deep Learning and Sentinel-2 Imagery|[RS'22]|Paper
Label-Efficient Hyperspectral Learning
How can spatial structure and geometry help us learn from hyperspectral images with few or no labels?
Label-Efficient Hyperspectral Learning
How can spatial structure and geometry help us learn from hyperspectral images with few or no labels?
Superpixel-Level Hypergraph Regularized Multi-View Clustering for Hyperspectral Images|[JSTARS'26]|Paper
Superpixel-based and Spatially-regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering|[TGRS'24]|Paper|Preprint
Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images|[RS'23]|Paper
Unsupervised Spatial-Spectral Hyperspectral Image Reconstruction and Clustering With Diffusion Geometry|[WHISPERS'22]|Preprint
Unsupervised Detection of Ash Dieback Disease Using Diffusion-Based Hyperspectral Image Clustering|[IGARSS'22]|Paper|Preprint
Classification of Hyperspectral Images Using SVM With Shape-Adaptive Reconstruction and Smoothed Total Variation|[IGARSS'22]|Paper
Medical Imaging and Signals
How can we reconstruct medical images and analyze biomedical signals with limited annotations?
Medical Imaging and Signals
How can we reconstruct medical images and analyze biomedical signals with limited annotations?
Latent Motion Profiling for Annotation-free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos|[MICCAI'25, Oral]|Paper
A Deep Learning Framework for Fetal Heart Tracking in Ultrasound Videos: Toward Enhanced Congenital Heart Defects Detection|[FIMH'25]|Paper
A Method for Cardiovascular Disorder Identification via Prototype-Driven Biomedical Signal Evaluation|[US Patent App., filed '25]
Accurate Detection and Instance Segmentation of Unstained Living Adherent Cells in Differential Interference Contrast Images|[CIBM'24]|Paper
Method for Accurate Segmentation of Unstained Living Adherent Cells in Differential Interference Contrast Images|[US Patent, filed '23; published '25]|Patent
LLM Compression and Interpretability
How can low-rank/SVD methods make LLMs more efficient, and how can we explain their decisions?
LLM Compression and Interpretability
How can low-rank/SVD methods make LLMs more efficient, and how can we explain their decisions?