I am a PhD student in the College of Information and Computer Sciences at the University of Massachusetts Amherst, supervised by Prof. Subhransu Maji in the Computer Vision Lab. Previously, I was a graduate research assistant at the University of the Philippines working on 3D reconstruction under the supervision of Prof. Rowel Atienza, where I also got my master’s degree in Electrical Engineering. I obtained my bachelor’s degree in Electronics and Communications Engineering from the same univeristy.

My current research involves using ML and computer vision to monitor water and sediment movements in Earth’s rivers using satellite images. My other research interests are explainable AI, multitask learning, understanding relationships between computer vision tasks, and applying computer vision for remote sensing applications.

News

• 2024-05 Passed PhD Portfolio with Distinction! (Awarded to select PhD students meeting a high standard of completion, voted by faculty)
• 2024-03 Task2Box paper accepted at CVPR 2024 as a Highlight (11.9% of accepted papers)!
• 2023-10 COSE paper presented in VIPriors at ICCV 2023
• 2022-09 Started PhD CS at University of Massachusetts Amherst
• 2020-06 REIN accepted (oral presentation) at CVPR 2020 workshop
• 2018-01 Started MS Electrical Engineering at University of the Philippines

Publications

(* means equal contribution)

	WildSAT: Learning Satellite Image Representations from Wildlife Observations Rangel Daroya, Elijah Cole, Oisin Mac Aodha, Grant Van Horn, Subhransu Maji arXiv 2024 arXiv We show satellite image representations can be improved using wildlife observations
	Improving Satellite Imagery Masking using Multi-task and Transfer Learning Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons, Punwath Prum, Tamlin Pavelsky, John Gardner, Colin J Gleason, Subhransu Maji arXiv 2024 arXiv We show a multi-task model for predicting water, cloud, cloud shadow, terain shadow, and snow/ice simultaneously from satellite images
	Task2Box: Box Embeddings for Modeling Asymmetric Task Relationships Rangel Daroya, Aaron Sun, Subhransu Maji CVPR 2024 (Highlight: 11.9% of accepted papers) project page / CVPR24 / arXiv We present a method for modeling asymmetric relationships between vision tasks using box embeddings
	COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification Rangel Daroya*, Aaron Sun*, Subhransu Maji ICCVW 2023 project page / ICCVW23 / arXiv We propose metrics related to the consistency and sensitivity of saliency maps on image classification tasks to assess the performance of different explainable AI methods on a variety of models and datasets
	REIN: Flexible mesh generation from point clouds Rangel Daroya, Rowel Atienza, Rhandley Cajote CVPRW 2020 CVPRW20 We present a method for generating a mesh from a sparse point cloud with an arbitrary number of points