Smith Students Assess How Deeply Federal Spending Impacts the State of Maryland

A joint report from Maryland’s Comptroller and Smith School researchers reveals $150 billion in recent federal spending in the state. Students, guided by professors Liu Yang, Vojislav Maksimovic and Kislaya Prasad, gained valuable experience in data analysis and government collaboration.

Smith School & Microsoft: AI-Powered Healthcare Innovation

Exposure to experiential learning opportunities, leveraging cutting-edge technology and engaging with industry leaders are major components of the student experience at the University of Maryland’s Robert H. Smith School of Business. This spring, Master of Science in Information Systems (MSIS) students got that and more through a unique partnership with Microsoft.

Smith School’s AI Collaboration with Google Sets New Standard in Credit Risk Evaluation

Smith Master of Quantitative Finance students partnered with Google to build AI-driven credit risk ratings for banks and fintechs, analyzing 25,000+ financial documents. Their work showcases how AI and financial expertise can transform credit assessment and industry forecasting.

AI in Action: Students Deliver Ethical, Practical Solutions for Local Businesses

Professors Balaji Padmanabhan and Tejwansh (Tej) Singh Anand led the Smith School’s AI in Business Case Competition, where 120+ students tackled real-world problems using AI. Multidisciplinary teams developed innovative, ethical solutions for industry clients, showcasing critical skills and creativity.

Smith Fraternities Compete in ESG-Focused Case Challenge

Seventy members from professional business fraternities at UMD competed in the Center for Social Value Creation’s ESG-focused pledging case competition. Phi Chi Theta’s team won, showcasing innovative solutions. The event featured alumni judges and engaged an audience of 150 students.

Smith Faculty Awarded Grants for Innovative Teaching Practices

Smith’s Teaching/Learning Innovation Grant supports Cliff Rossi’s experiential learning project, where students analyze climate risk impacts on mortgages using machine learning. The project develops industry-relevant skills, preparing students for top finance roles and advancing climate-risk insights in housing.