Krishna Muvva (Veera Venkata Ram Murali Krishna Rao Muvva), is a Ph.D. candidate in the School of Computing and a Master's student in the Biological Systems Engineering department at the University of Nebraska - Lincoln. His research, which draws inspiration from avian intelligence, intricately combines traditional control systems with advanced deep learning techniques to enhance the perceptual and control systems of unmanned aerial vehicles (UAVs). His significant contributions to the field are documented in his publications at AIAA and IEEE conferences. Additionally, he serves as the chair of the IEEE Nebraska Computer Chapter, further underscoring his leadership and expertise in his field.
Volants are extraordinary creatures. We can observe amazing phenomena in their flight, such as the precision of bald eagles in stormy conditions, the innate migration of Arctic terns without GPS, the meticulous docking of hummingbirds, and the exceptional vision-based tracking of falcons. Volants achieve this intelligence not because they are experts in fluid dynamics,control systems, or computer vision; they succeed via a continuous learning process and the strong integration of perception and control modules. My career goal is to harness these extraordinary capabilities to overcome the current limitations in aerial systems. I believe that integrating traditional methodologies with machine and deep learning can offer solutions for designing and deploying robust aerial robots. My published work in prestigious conferences such as AIAA and IEEE supports this approach.