We’re excited to celebrate the successful completion of the Earth and Space Research and Northeastern University partnership, showcased last week at the NU Expo. Through this collaboration, ESR scientists (Kathleen Dohan and Michael Town) mentored two student teams, nine students total, on applied machine learning projects that connect data science directly to real-world Earth system challenges.
Project 1: Integrated Machine Learning Modeling of Atmospheric Drivers for Understanding and Predicting Energy Transfer
This ML/AI project focused on predicting snow surface temperatures at Summit, Greenland using only local meteorology and cloud properties. The work supports improved understanding and prediction of melt conditions in one of the most rapidly changing regions of the cryosphere.
Students: Cheng-Wen (Eric) Hsu, Ya (Jaelyn) Ji, Zerui Li, Mohit Chhabria, Surya Shivam
Project 2: Ocean Current Forecasting using Machine Learning
This ML/AI project used regional meteorology and ocean current data to produce 1–3 day forecasts of ocean currents off the west coast of Washington. Applications include regional fisheries, coastal planning, and understanding pollution transport pathways.
Students: Ming-Hsiang Lee (Thomas), Qing Wen, Shuxin Yang, Laxmi Bhutani
We are incredibly proud of the students for tackling complex, interdisciplinary problems and translating machine learning techniques into actionable environmental insights. This partnership highlights the power of mentorship, applied data science, and collaboration between research organizations and universities.
Thank you to Northeastern University and all involved for a fantastic collaboration. We look forward to what comes next!
