Congratulations to our labmate, Meilun Zhou, for accepting an internship at The Air Force Research Laboratory! Meilun will be working as a SMART Scholar Intern and he will build upon the research that he conducted during last summer’s internship. This… Read More
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Congratulations To Xiaolei Guo For Accepting An Internship at Meta/Facebook!
Congratulations to our labmate, Xiaolei Guo, for accepting an internship at Meta/Facebook! Xiaolei will be working as a Machine Learning Software Engineer Intern on the instagram recommendation team. Great job, Xiaolei!
Congratulations To Mira Saldanha For Accepting An Internship at The Johns Hopkins University Applied Physics Laboratory!
Congratulations to our labmate, Mira Saldanha, for accepting an internship at The Johns Hopkins University Applied Physics Laboratory! Mira will be working as a Data Science Intern in a project involving multimodal machine learning. Great job, Mira!
Congratulations To Luke Saleh For Accepting An Internship at Johnson & Johnson – Ethicon!
Congratulations to our labmate, Luke Saleh, for accepting an internship at Johnson & Johnson – Ethicon! Luke will be working as a Data Science and Engineering Intern and will be working with electrical data/development of digital products. Great job, Luke!… Read More
Congratulations To Justin Rossiter For Accepting An Internship at CACI International!
Congratulations to our labmate, Justin Rossiter, for accepting an internship at CACI International! Justin will be working as a Signal Processing and Data Analysis Engineer Intern and will be working on application of signal processing and data analysis techniques on… Read More
Congratulations To Anthony Khoury For Accepting An Internship at Apple!
Congratulations to our labmate, Anthony Khoury, for accepting an internship at Apple! Anthony will be working as a Software Engineering Intern in developing tools for the battery qualification team. Great job, Anthony!
Capturing long-tailed individual tree diversity using an airborne imaging and a multi-temporal hierarchical model
Abstract: Measuring forest biodiversity using terrestrial surveys is expensive and can only capture common species abundance in large heterogeneous landscapes. In contrast, combining airborne imagery with computer vision can generate individual tree data at the scales of hundreds of thousands… Read More
Welcome New Undergraduate Research Assistant Anthony Khoury!
The Machine Learning and Sensing Lab is excited to welcome our newest lab member, Anthony Khoury! Anthony is a senior Computer Engineering student currently working on the Navy Project and he is very interested in Machine Learning and its impact… Read More
Spatial and Texture Analysis of Root System distribution with Earth mover’s Distance (STARSEED)
Abstract: Root system architectures are complex and challenging to characterize effectively for agronomic and ecological discovery. We propose a new method, Spatial and Texture Analysis of Root System distribution with Earth mover’s Distance (STARSEED), for comparing root system distributions that… Read More
Congratulation to Aditya Dutt for publishing his new paper: Contrastive learning based MultiModal Alignment Network
Congratulations to our labmates and collaborators: Aditya Dutt, Alina Zare, and Paul Gader! Their paper, “Shared Manifold Learning Using a Triplet Network for Multiple Sensor Translation and Fusion with Missing Data”, was recently accepted to IEEE Journal of Selected Topics… Read More