Mohammed Alsobay is a PhD candidate in the Information Technology group at MIT Sloan, where his research focuses on the design and analysis of systems in which humans and algorithmic agents interact, with the goal of achieving collective outcomes that exceed what is achievable by either type of agent on its own. In parallel, he explores how adaptive experimentation and virtual labs can be used to improve and scale social science research. Prior to MIT, Mohammed built and led the data science team at Mozn, tackling challenges across a wide array of fields including fraud detection, Arabic language processing, and financial risk management. He holds a B.S. in Chemical Engineering from MIT, an M.S. in Applied Math and Computational Science from KAUST, and is a recipient of the KAUST Gifted Student Program (KGSP) undergraduate scholarship.