People

Rebecca is the lead PI of the ML QuESt Lab. She is an Associate Professor at Oregon State University, with a joint appointment across the School of Electrical Engineering and Computer Science and the Department of Fisheries, Wildlife, and Conservation Sciences. She is also affiliated with the Center for Quantitative Life Sciences and the Collaborative Robotics and Intelligent Systems (CoRIS) Institute. She became interested in interdisciplinary work in machine learning and quantitative ecology during her postdoctoral studies with the Institute for Computational Sustainability and as an NSF SEES Fellow, advised by Tom Dietterich and Matt Betts. Prior to that, she completed her PhD at Carnegie Mellon University with Tom Mitchell.

Laurel is a PhD student and NASA FINESST (Future Investigators in NASA Earth and Space Science Technology) recipient. Laurel's work is at the intersection of deep learning, remote sensing, and ecology. She studies deep learning architectures and various remote sensing products (i.e., satellite imagery datasets). She recieved her M.S. in Computer Science from Oregon State and her B.S. in Electrical Engineering from UC Santa Barbara. Between her undergraduate and graduate studies, Laurel worked at a medical device startup where she designed the system electronics.

Jing is a PhD candidate in computer science, studying on model evaluation in machine learning, specifically developing cross-validation methods for geospatial problems and applying them on birds and housing datasets. Previously, she obtained her M.S. in Computer Science from University of South Carolina, M.A. in Applied Economics from Fudan University, and B.A in Finance from Huazhong University of Science and Technology.

Nahian is a PhD student of computer science. He studies machine learning, with a focus on evaluation, and applications in computational sustainability. He is interested in intuitive and engaging ways of learning about machine learning.

Andrew is an MS student in Computer Science researching machine learning for forecasting and anomaly detection problems. He takes inspiration from ecology and sustainability applications to develop novel learning models, with a particular interest in problems across space and time. Co-advised by Weng-Keen Wong, Andrew is a team member of both the Agriculture for AI (AgAID) Institute and of the Pervasive Personalized Intelligence (PPI) Center. Previously, he earned a BS in Computer Science and Mathematics at Roanoke College, where he also worked as a web developer.

Louise is pursuing an M.S. and a Ph.D. in artificial intelligence at Oregon State University. She received a B.S. in physics, and later a B.S. in computer science, also from Oregon State University. Prior to attending graduate school, Louise worked as a software engineer, developing software to support manufacturing processes and automation.

Annabel is a second-year undergraduate student at Oregon State University studying computer science, with an interest in bioinformatics. Co-mentored by Nahian and Rebecca, she is excited about entering the world of machine learning and data science, and contributing to sustainable engineering in the future.

Fiona is a PhD student in Artificial Intelligence and a recipient of the Provost's Distinguished Graduate Scholarship. She is deeply committed to the cause of researching and building AI/ML systems for social good. Her primary research focus is on the intersection of machine learning and ecology. Prior to this, she obtained her M.S in Computer Science at the University of Washington Bothell and her bachelor’s in Robotics and Automation from PSG College of Technology. She has actively volunteered for a recent social cause using NLP techniques and has worked as a machine learning engineer specializing in building multimodal AI systems and developing quantization techniques for neural networks.

Sara is a master's student in the Wildlife Science program, developing an occupancy model for rare desert bats using a hybrid monitoring approach that incorporates citizen science and professional surveys at a regional scale. She is co-advised by Katie Dugger. Sara received her BS from Oregon State University - Cascades in natural resources fish and wildlife conservation. She serves as a project coordinator at the Northwest Bat Hub on the OSU Cascades campus. In addition to her work with the bat monitoring, she has completed wildlife research internships with the Deschutes National Forest and with Cardiff University at their research center in Malaysia and monitored pygmy rabbits for the Oregon Department of Fish & Wildlife.

Chelsea graduated with a bachelor's degree in Computer Science from Oregon State University in 2023, with a focus on web and mobile application development. During her first year as an undergraduate research assistant at the ML QuESt Lab, she worked on hyperparameter tuning methods and evaluation metrics. Later on, Chelsea interned at Lucidyne Technologies, Inc., where she worked on computer vision applications; Amazon AWS Elemental, where she focused on computer networks and broadcasting services; and Microsoft, where she contributed to containerization methods and data ingestion for Bing's backend processes. After graduating, she accepted a software engineering position at Microsoft's Bing department.

Mark graduated with a masters degree in Computer Science from Oregon State University in 2021 where he studied unsupervised machine learning algorithms and how they can improve species distribution models in the context of community-science collected data. His research centered on biodiversity and he completed parallel coursework in conservation and machine learning to better understand the interdisciplinary challenges of his research problem. After graduation, Mark accepted a role as a Data Scientist at Climate, an agricultural technology company.

Eugene earned a Ph.D. degree in Computer Science from Oregon State University in 2021. During her Ph.D. study, she focused on proposing machine learning frameworks for predicting plant-pollinator interactions and modeling bird species distributions. Following graduation, as a Postdoctoral Research Associate at Brown University, she studied machine learning models to estimate aboveground biomass density using Global Ecosystem Dynamics Investigation (GEDI) data.

Vishnu completed her master's degree in Computer Science, specializing in Machine Learning and Statistics, at Oregon State University in 2021. During her studies, she worked on analyzing over-dispersed count data in species distribution modeling. After graduation, Vishnu joined the Sam's Club AI Labs, Walmart, as an ML Software/Data Engineer, focusing on data pipelines and enhancing the communication aspects of AI systems.

Demetrius earned a bachelor's degree in Computer Science from The University of Texas at El Paso in 2022. He began his journey with our lab in the summer of 2021 as a Research Experience for Undergraduates (REU) student. As a Department of Defense (DOD) SMART Scholar, he went on to serve his DOD commitment at White Sands Missile Range, where he was honored with the DOD Creative Research & Engineering Advancing Technical Equity in STEM (CREATES) Grant for collaboration with New Mexico State University. Following that service, he entered the graduate program at the University of Notre Dame.

Justin Clarke earned his BS in computer science from Oregon State University with a focus on modeling interactions between species in ecological networks. He later interned at NASA’s Ames Research Center where he developed methods to explain decisions made by deep neural networks in UAV navigation. Justin went on to continue his education as an MS/PhD student in computer science at the University of Massachusetts, Amherst, with research focuses on causal inference, explainability, and generalization.

Liqiang earned an MS in computer science, working on connections between statistical models in ecology and class-conditional noise frameworks in machine learning. He continued on to pursue a PhD from Oregon State University as well, focusing on computer vision.