Sarath Pattathil is a PhD candidate exploring multiagent learning. This area of research is becoming increasingly more important as artificial-intelligence (AI) technologies are deployed in large-scale societal applications such as transportation, healthcare, and social networks. As a MathWorks Fellow, Sarath seeks to advance dynamic interactions between humans and AI-driven systems and between multiple AI-driven agents. MATLAB is a vital tool in his work, enabling Sarath to design robust models and to achieve optimal system control. Specifically, his research has three focus areas. The first is the study of robustness of multiagent systems to adversarial perturbations, particularly the non-asymptotic analysis of gradient-based algorithms, including the proximal point, extragradient, and optimistic gradient descent ascent methods. The second is exploring control and intervention in the presence of spreading processes among agents, specifically for epidemic modeling and control. Finally, the third is exploring learning in multiagent systems and examining which network architectures enable robust learning, what factors determine that strength, and how it can be replicated and leveraged in future applications.