Team

Nadia is a visionary entrepreneur with a passion for leveraging AI to solve complex environmental problems. As the Founder of Mudder AI, she leads the company’s strategic direction. Nadia is currently pursuing a Ph.D. at the Yale School of the Environment. She holds a master’s degree in Natural Resources and Environmental Law from the University of Denver, a law degree from the University of Florida, and an undergraduate degree from UC Berkeley. She serves as Women Techmakers Ambassador.

Tarek is a renowned researcher with a Ph.D. in Geosciences from Texas Tech University and extensive expertise in geospatial analysis and modeling, GIS, remote sensing, and data analysis. He is an effective communicator, a successful lecturer and mentor, and the author of multiple research papers. As a licensed sUAV remote pilot by the FAA, Tarek brings his vast knowledge and experience to develop cutting-edge AI solutions at Mudder AI, addressing complex environmental challenges.

Weixi is a talented marketing professional and the VP of Marketing at Mudder AI. She completed a joint Master’s degree in the MESc program at the Yale School of the Environment and the MPH program at the Yale School of Public Health. At Mudder AI, Weixi leverages her interdisciplinary background in environmental science and public health to develop effective marketing strategies that communicate the company’s mission and the value of its AI-driven solutions to target audiences.

Alex Wong is an Assistant Professor in the Department of Computer Science and director of the Vision Laboratory at Yale University. Alex’s research focuses on machine learning, computer vision, and robotics, including multi-sensor fusion for 3D reconstruction, robust vision under adverse conditions, unsupervised learning, and medical image analysis. Alex received his Ph.D. in Computer Science from UCLA in 2019, where he completed a post-doctoral research position. He was previously an Adjunct Professor at Loyola Marymount University. His work has been recognized with awards at NeurIPS 2011 and ICRA 2019.

Rex Ying is an Assistant Professor in the Department of Computer Science at Yale University. His research focuses on algorithms for graph neural networks, geometric embeddings, explainable models, and multi-modal foundation models involving relational reasoning. Rex is the author of widely used GNN algorithms such as GraphSAGE, PinSAGE, and GNNExplainer. He has also worked on applications of graph learning in various domains, developed billion-scale graph embedding services at Pinterest, and created a graph-based anomaly detection algorithm at Amazon. Rex obtained his Ph.D. in Computer Science at Stanford University.